<?xml version="1.0" encoding="UTF-8"?>
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    <title>llm</title>
    <link rel="self" type="application/atom+xml" href="https://links.biapy.com/guest/tags/9/feed"/>
    <updated>2026-07-26T18:23:29+00:00</updated>
    <id>https://links.biapy.com/guest/tags/9/feed</id>
            <entry>
            <id>https://links.biapy.com/links/13409</id>
            <title type="text"><![CDATA[colibrì]]></title>
            <link rel="alternate" href="https://justvugg.github.io/colibri/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13409"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[a 744-billion-parameter mind, on your desk
 tiny engine, immense model.

Run GLM-5.2 — 744B Mixture-of-Experts — on hardware you already own. Pure C, zero dependencies, experts staged just-in-time across VRAM, RAM and disk. The galaxy behind this text is real: the model&amp;#039;s measured expert atlas.

- [colibrì @ GitHub](https://github.com/JustVugg/colibri).]]>
            </summary>
            <updated>2026-07-24T13:12:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13406</id>
            <title type="text"><![CDATA[Frugon]]></title>
            <link rel="alternate" href="https://frugon.rodiun.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13406"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your LLM bill is leaking.

Free, local, open-source LLM cost analyzer - see where your LLM bill leaks, on your machine.

Most teams run every call on their most expensive model. Frugon reads your real logs locally and shows which calls a cheaper model handles just as well, and which to leave alone. No upload. No telemetry.

- [Frugon @ GitHub](https://github.com/Rodiun/frugon).]]>
            </summary>
            <updated>2026-07-24T13:08:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13384</id>
            <title type="text"><![CDATA[Petals]]></title>
            <link rel="alternate" href="https://petals.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13384"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run LLMs at home, BitTorrent-style.

 You load a part of the model, then join a network of people serving its other parts. Single‑batch inference runs at up to 6 tokens/sec for Llama 2 (70B) and up to 4 tokens/sec for Falcon (180B) — enough for chatbots and interactive apps. 

- [Petals @ GitHub](https://github.com/bigscience-workshop/petals).]]>
            </summary>
            <updated>2026-07-23T11:49:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13379</id>
            <title type="text"><![CDATA[Hugging Bay]]></title>
            <link rel="alternate" href="https://huggingbay.xyz/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13379"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open AI Artifact Metadata.

Hugging Bay publishes open AI catalog metadata, source provenance, license records, neutral hosted-file inventory, answer packs, and recorded hashes. Canonical bundle verification and runtime readiness remain unknown.]]>
            </summary>
            <updated>2026-07-23T06:34:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13378</id>
            <title type="text"><![CDATA[Mesh LLM]]></title>
            <link rel="alternate" href="https://meshllm.cloud/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13378"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Distributed AI/LLM for the people. Share compute privately or publicly to power your agents and chat. 

Mesh LLM pools GPUs and memory across machines and exposes the result as one OpenAI-compatible API at http://localhost:9337/v1. Start one node, add more nodes later, and let the mesh decide whether a model runs locally, routes to a peer, or uses Skippy stage splits for models that are too large for one box.

- [Mesh LLM @ GitHub](https://github.com/Mesh-LLM/mesh-llm).]]>
            </summary>
            <updated>2026-07-23T06:34:13+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13369</id>
            <title type="text"><![CDATA[agtop]]></title>
            <link rel="alternate" href="https://github.com/ldegio/agtop" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13369"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[top-style TUI for monitoring AI coding agent sessions.

Your window into what your AI coding agents are doing, sitting in the terminal, where you run them. agtop is a top-style terminal dashboard that tracks every Claude Code and Codex session on your machine: spend, token usage, context pressure, CPU load, tool invocations, and more. All in one place, live.]]>
            </summary>
            <updated>2026-07-23T05:53:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13359</id>
            <title type="text"><![CDATA[Nativ]]></title>
            <link rel="alternate" href="https://blaizzy.github.io/nativ/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13359"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run AI locally on your Mac.

 Local AI, native to your Mac. Chat, serve, monitor, and connect MLX models from one macOS app. 

- [Nativ @ GitHub](https://github.com/Blaizzy/nativ).]]>
            </summary>
            <updated>2026-07-21T12:13:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13341</id>
            <title type="text"><![CDATA[LoopGain]]></title>
            <link rel="alternate" href="https://loopgain.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13341"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[cost control for AI agent loops.
Your AI agent loops don&amp;#039;t know when to stop. LoopGain does.

When an agent keeps checking and revising its own work, it often spins on a problem it can&amp;#039;t solve — or talks itself into an answer worse than one it already had. LoopGain watches the loop as it runs, stops it at the right iteration, and keeps the best version, not the last. 

- [LoopGain @ GitHub](https://github.com/loopgain-ai/loopgain).]]>
            </summary>
            <updated>2026-07-20T12:16:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13340</id>
            <title type="text"><![CDATA[ReactBench]]></title>
            <link rel="alternate" href="https://www.reactbench.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13340"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[ReactBench is an evaluation for coding agents on realistic React work. Models can pass every test in today’s benchmarks and still write React that fails in production. Tests verify behavior, but they miss React performance, accessibility, and quality issues.

- [ReactBench @ GitHub](https://github.com/millionco/reactbench).]]>
            </summary>
            <updated>2026-07-20T12:14:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13318</id>
            <title type="text"><![CDATA[llm-wiki]]></title>
            <link rel="alternate" href="https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13318"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Related contents:

- [Karpathy&amp;#039;s LLM Wiki @ Hermes Agent&amp;#039;s GitHub](https://github.com/NousResearch/hermes-agent/blob/main/skills/research/llm-wiki/SKILL.md).
- [Episode 675: Sloppy Agent Roasting @ Linux Unplugged](https://linuxunplugged.com/675).]]>
            </summary>
            <updated>2026-07-16T05:43:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13241</id>
            <title type="text"><![CDATA[Otari Gateway]]></title>
            <link rel="alternate" href="https://otari.ai/docs/gateway" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13241"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Otari Gateway is the open-source gateway that puts a single OpenAI-compatible API in front of many LLM providers.

Run it in your own infrastructure. Use it standalone, or connect it to otari.ai for hosted routing, authentication, and usage reporting.

- [Otari Gateway @ GitHub](https://github.com/mozilla-ai/otari).]]>
            </summary>
            <updated>2026-07-08T06:05:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13238</id>
            <title type="text"><![CDATA[Wayfinder]]></title>
            <link rel="alternate" href="https://github.com/itsthelore/wayfinder-router" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13238"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Simple CLI tool for deterministic routing of queries between local and hosted LLM models.

A fast, offline hard-or-easy call on every prompt — scored deterministically, with no model call. Route the easy ones to your small/local model and the hard ones to your big one, or compose any model-router behind it.]]>
            </summary>
            <updated>2026-07-07T05:52:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13226</id>
            <title type="text"><![CDATA[claude-real-video]]></title>
            <link rel="alternate" href="https://github.com/HUANGCHIHHUNGLeo/claude-real-video" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13226"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Let Claude (or any LLM) actually watch a video — scene-aware, deduplicated frames + transcript, from a URL or local file. Runs locally, MIT.]]>
            </summary>
            <updated>2026-07-06T11:33:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13225</id>
            <title type="text"><![CDATA[jamesob&amp;#039;s guide to running SOTA LLMs locally]]></title>
            <link rel="alternate" href="https://github.com/jamesob/local-llm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13225"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Everything I know about running LLMs locally]]>
            </summary>
            <updated>2026-07-06T11:32:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13224</id>
            <title type="text"><![CDATA[Talos worker]]></title>
            <link rel="alternate" href="https://usetalos.xyz/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13224"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[GPU worker client for the Talos network. Pairs with your Talos account, serves open-model inference jobs over a WebSocket, and reports uptime for payouts. 

- [Talos worker @ GitHub](https://github.com/jmerelnyc/Talos).]]>
            </summary>
            <updated>2026-07-06T11:31:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13191</id>
            <title type="text"><![CDATA[Ornith-1.0]]></title>
            <link rel="alternate" href="https://github.com/deepreinforce-ai/Ornith-1" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13191"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Aloha! 🌺 Ornith-1.0 is a self-improving open-source models for agentic coding.

 Today, we are introducing Ornith-1.0, a self-improving family of open-source models specially for agentic coding tasks. Ornith-1.0 spans the full spectrum, from compact 9B Dense models suitable for edge device deployment to 397B MoE frontier-scale models optimized for maximum performance, with variants including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Built on top of pretrained Gemma 4 and Qwen 3.5, it achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks. 

Related contents:

- [Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding](https://deep-reinforce.com/ornith_1_0.html).
- [Ornith 1.0, l’IA open source qui dépasse Claude Opus 4.7 @ IT-Connect :fr:](https://www.it-connect.fr/ornith-1-0-ia-open-source-qui-depasse-claude-opus-4-7/).]]>
            </summary>
            <updated>2026-07-03T06:37:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13178</id>
            <title type="text"><![CDATA[OpenWiki]]></title>
            <link rel="alternate" href="https://github.com/langchain-ai/openwiki" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13178"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[OpenWiki is a CLI that writes and maintains documentation for your codebase, built specifically for agents.]]>
            </summary>
            <updated>2026-07-02T12:13:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13173</id>
            <title type="text"><![CDATA[Headroom]]></title>
            <link rel="alternate" href="https://headroomlabs-ai.github.io/headroom/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13173"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Context Optimization Layer for LLM Applications

Compress everything your AI agent reads. Same answers, fraction of the tokens.
 Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. 

- [Headroom @ GitHub](https://github.com/headroomlabs-ai/headroom).

Related contents:

- [MCP : les serveurs et outils à connaître en 2026 @ Camille Roux :fr:](https://www.camilleroux.com/mcp-serveurs-outils/).]]>
            </summary>
            <updated>2026-07-02T06:06:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13165</id>
            <title type="text"><![CDATA[OmniRoute]]></title>
            <link rel="alternate" href="https://omniroute.online/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13165"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Free AI Gateway for Multi-Provider LLMs.

 Never stop coding. Free AI gateway: one endpoint, 231+ providers (50+ free), connect Claude Code, Codex, Cursor, Cline &amp;amp; Copilot to FREE Claude/GPT/Gemini. RTK+Caveman stacked compression saves 15-95% tokens, smart auto-fallback, MCP/A2A, multimodal APIs, Desktop/PWA. 

- [OmniRoute @ GitHub](https://github.com/diegosouzapw/OmniRoute).]]>
            </summary>
            <updated>2026-07-01T11:35:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13153</id>
            <title type="text"><![CDATA[OpenFugu]]></title>
            <link rel="alternate" href="https://github.com/trotsky1997/OpenFugu" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13153"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open reimplementation of Sakana Fugu — the &amp;#039;one model to command them all&amp;#039; LLM orchestrator. Read → run → train → serve. 

An open, runnable reverse-engineering of Sakana AI&amp;#039;s Fugu — the &amp;quot;one model to command them all&amp;quot; LLM orchestrator.

Fugu is sold as a single model; it is really a policy over models — a tiny coordinator that, per query, routes work to a pool of frontier LLMs and returns one answer. Sakana&amp;#039;s product and trained weights are closed. OpenFugu rebuilds the mechanism from the two papers + released artifacts, verifies it against real weights, trains a Conductor of our own, and serves it behind one OpenAI-compatible endpoint. Four stages, all working: read → run → train → serve.]]>
            </summary>
            <updated>2026-06-29T10:49:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13152</id>
            <title type="text"><![CDATA[⚡ Godcoder]]></title>
            <link rel="alternate" href="https://github.com/eli-labz/Godcoder" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13152"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Godcoder doesn&amp;#039;t just use a harness. It writes one, improves it, and optimizes it — autonomously, in real time.

 A local-first, open-source coding agent for your desktop. Bring your own LLM key; your code stays on your machine and only ever leaves to the model provider. The AI Agent builds its own Harness.]]>
            </summary>
            <updated>2026-06-29T10:48:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13150</id>
            <title type="text"><![CDATA[Osmantic Deployment System (ODS)]]></title>
            <link rel="alternate" href="https://github.com/Light-Heart-Labs/ODS" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13150"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn your PC, Mac, or Linux box into an AI server. LLM inference, chat UI, voice, agents, workflows, RAG, and image generation. 

Related contents:

- [Dream Server - Un serveur IA complet chez vous en une commande @ Korben :fr:](https://korben.info/dream-server-ia-locale-auto-hebergee.html).]]>
            </summary>
            <updated>2026-06-29T08:53:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13123</id>
            <title type="text"><![CDATA[Persona]]></title>
            <link rel="alternate" href="https://www.persona-chat.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13123"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The VanillaJS Agent UI Library.
 Create agentic front-end experiences for the web in VanillaJS™️. Lightweight, extensible, and WebMCP-native. 

Persona helps you create agentic front-end experiences for the web, in pure JS. Lightweight, extensible, and WebMCP-native.

- [Person @ GitHub](https://github.com/runtypelabs/persona).]]>
            </summary>
            <updated>2026-06-26T11:43:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13120</id>
            <title type="text"><![CDATA[Strix]]></title>
            <link rel="alternate" href="https://www.strix.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13120"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Autonomous Security for the AI Era.

Open-source AI hackers to find and fix your app’s vulnerabilities. 
Strix are autonomous AI agents that act just like real hackers - they run your code dynamically, find vulnerabilities, and validate them through actual proof-of-concepts. Built for developers and security teams who need fast, accurate security testing without the overhead of manual pentesting or the false positives of static analysis tools.

- [Strix @ GitHub](https://github.com/usestrix/strix).

Related contents:

- [Strix : le pentester IA open-source à l&amp;#039;épreuve de la souveraineté @ DevSecOps :fr:](https://blog.stephane-robert.info/post/strix-pentester-ia-souverainete/).]]>
            </summary>
            <updated>2026-06-26T09:52:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13103</id>
            <title type="text"><![CDATA[AirLLM]]></title>
            <link rel="alternate" href="https://github.com/lyogavin/airllm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13103"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AirLLM 70B inference with single 4GB GPU.

AirLLM optimizes inference memory usage, allowing 70B large language models to run inference on a single 4GB GPU card without quantization, distillation and pruning. And you can run 405B Llama3.1 on 8GB vram now.]]>
            </summary>
            <updated>2026-06-24T11:45:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13095</id>
            <title type="text"><![CDATA[llama.vscode]]></title>
            <link rel="alternate" href="https://github.com/ggml-org/llama.vscode" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13095"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[VS Code extension for LLM-assisted code/text completion.

Local LLM-assisted text completion, chat with AI and agentic coding extension for VS Code.

Related contents:

- [5 AI Extensions to Help Improve Your VS Code Experience @ The New Stack](https://thenewstack.io/5-ai-extensions-to-help-improve-your-vs-code-experience/).]]>
            </summary>
            <updated>2026-06-23T06:26:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13093</id>
            <title type="text"><![CDATA[Shard]]></title>
            <link rel="alternate" href="https://github.com/leyten/shard" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13093"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Pipeline-parallel LLM inference across GPUs on separate machines.

Pipeline-parallel LLM inference across GPUs on separate machines. A model too large for any single card is split into contiguous blocks of layers — one shard per GPU — and a request is served by streaming activations through the shards in order. No datacenter, no single host, and no node ever holds the whole model.]]>
            </summary>
            <updated>2026-06-23T06:23:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13008</id>
            <title type="text"><![CDATA[Agent Substrate]]></title>
            <link rel="alternate" href="https://github.com/agent-substrate/substrate/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13008"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Agent substrate is a system built on top of Kubernetes which manages agent-like workloads to achieve higher scale and efficiency than Kubernetes alone can offer, with lower latency. It builds on top of Kubernetes features like Pods and Pod autoscaling, but takes the Kubernetes control-plane out of the critical path to achieve lower latency.

Related contents:

- [Agent substrate can power agents on Kubernetes with kagent @ Solo.io](https://www.solo.io/blog/agent-substrate-powers-kubernetes-agents-with-kagent).]]>
            </summary>
            <updated>2026-06-12T11:43:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12999</id>
            <title type="text"><![CDATA[Apache Burr]]></title>
            <link rel="alternate" href="https://burr.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12999"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure. 

Apache Burr (incubating) makes it easy to develop applications that make decisions (chatbots, agents, simulations, etc...) from simple python building blocks.

Apache Burr works well for any application that uses LLMs, and can integrate with any of your favorite frameworks. Burr includes a UI that can track/monitor/trace your system in real time, along with pluggable persisters (e.g. for memory) to save &amp;amp; load application state.

- [Apache Burr @ GitHub](https://github.com/apache/burr).]]>
            </summary>
            <updated>2026-06-11T12:13:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12997</id>
            <title type="text"><![CDATA[PromptZero]]></title>
            <link rel="alternate" href="https://github.com/openbashok/promptzero" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12997"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Zero trace. Full answer. — Transparent Claude API proxy that anonymizes PII and sensitive data before it leaves your environment. From pentesters, to pentesters. 

PromptZero applies Zero Trust principles to LLM interactions. A local, transparent proxy that detects and replaces sensitive data — identities, infrastructure, secrets, client material — in your prompts before they leave your environment, and restores the real values in the response. Never trust the API. Always verify what crosses the boundary. Your data stays home.

Related contents:

- [\#80 - Patch Tuesday record et messagerie Tchap compromise @ Erreur 403 :fr:](https://newsletter.erreur403.fr/p/erreur-403-80-patch-tuesday-record-et-messagerie-tchap-compromise).]]>
            </summary>
            <updated>2026-06-11T07:31:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12974</id>
            <title type="text"><![CDATA[Lathe]]></title>
            <link rel="alternate" href="https://github.com/devenjarvis/lathe" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12974"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An experiment in using LLMs to teach you, rather than think for you.

Lathe generates hands-on, multi-part technical tutorials on demand, with skills tuned to make content approachable. Then you work through them yourself, by hand, in a local UI built from the ground up for pleasant learning. (Just like we did it in the stone age 😎)]]>
            </summary>
            <updated>2026-06-09T11:58:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12939</id>
            <title type="text"><![CDATA[tokenspeed]]></title>
            <link rel="alternate" href="https://mikeveerman.github.io/tokenspeed/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12939"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[feel LLM tokens-per-second.

tokenspeed is a tiny terminal toy that streams fake tokens at any rate you set, so you can see what those numbers actually look like.

- [tokenspeed @ GitHub](https://github.com/MikeVeerman/tokenspeed).]]>
            </summary>
            <updated>2026-06-05T09:28:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12920</id>
            <title type="text"><![CDATA[mnemo]]></title>
            <link rel="alternate" href="https://github.com/zaydmulani09/mnemo" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12920"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Local-first AI memory layer for any LLM. Persistent knowledge graph, entity extraction, semantic retrieval. Works with Ollama, OpenAI, Anthropic, or any OpenAI-compatible backend. 

mnemo is a sidecar service that watches every conversation you feed it, extracts named entities and relationships using an LLM, builds a persistent knowledge graph in SQLite, and injects relevant context back into future prompts — automatically, in under 50ms. It works with Ollama (fully local, free), OpenAI, Anthropic, or any OpenAI-compatible API. It ships as a single static binary with zero cloud dependency.]]>
            </summary>
            <updated>2026-06-04T11:39:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12910</id>
            <title type="text"><![CDATA[oMLX]]></title>
            <link rel="alternate" href="https://omlx.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12910"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM inference, optimized for your Mac.
Local AI, no more waiting on your Mac.

 LLM inference server with continuous batching &amp;amp; SSD caching for Apple Silicon — managed from the macOS menu bar.

macOS-native MLX server with smart caching. Claude Code, OpenClaw, and Cursor respond in 5 seconds, not 90. 

- [oMLX  @ GitHub](https://github.com/jundot/omlx).

Related contents:

- [\#133 - News Juin 2026, Bun passe à Rust, npm verrouille les scripts et SEO pour l&amp;#039;IA @ Double Slash :fr:](https://double-slash.dev/podcasts/news-jun26/)]]>
            </summary>
            <updated>2026-06-04T05:51:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12908</id>
            <title type="text"><![CDATA[Kimi WebBridge]]></title>
            <link rel="alternate" href="https://www.kimi.com/features/webbridge" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12908"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A browser extension for AI agents. It clicks, fills, navigates, and extracts. Tedious work, on autopilot.

Related contents:

- [\#133 - News Juin 2026, Bun passe à Rust, npm verrouille les scripts et SEO pour l&amp;#039;IA @ Double Slash :fr:](https://double-slash.dev/podcasts/news-jun26/)]]>
            </summary>
            <updated>2026-06-04T05:47:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12904</id>
            <title type="text"><![CDATA[Headroom]]></title>
            <link rel="alternate" href="https://headroom-docs.vercel.app/docs" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12904"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. 

Headroom is the context optimization layer for LLM applications. Compress tool outputs, DB results, file reads, and RAG results before they reach the model. Same answers, fraction of the tokens.

- [Headroom @ GitHub](https://github.com/chopratejas/headroom).

Related contents:

- [Un ingénieur de Netflix crée une appli pour alléger ses factures d&amp;#039;IA, puis l&amp;#039;ouvre à tout le monde @ Korben :fr:](https://korben.info/un-ingenieur-de-netflix-cree-une-appli-pour-alleger-ses-factures-dia-puis-louvre-a-tout-le-monde.html).
- [Netflix wiz creates app to slash AI bills, then open sources it @ The Register](https://www.theregister.com/ai-ml/2026/05/31/netflix-wiz-creates-app-to-slash-ai-bills-then-open-sources-it/5248702).]]>
            </summary>
            <updated>2026-06-08T08:24:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12897</id>
            <title type="text"><![CDATA[Scira AI]]></title>
            <link rel="alternate" href="https://scira.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12897"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Research anything. Do anything.

Research at the speed of thought. The agentic research platform that plans, retrieves, and cites — so you can think faster.

 Scira (Formerly MiniPerplx) is a minimalistic AI-powered search engine that helps you find information on the internet and cites it too. Powered by Vercel AI SDK!]]>
            </summary>
            <updated>2026-06-02T07:34:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12896</id>
            <title type="text"><![CDATA[LLMKube]]></title>
            <link rel="alternate" href="https://llmkube.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12896"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Kubernetes for Local LLMs.

A Kubernetes operator for self-hosted LLM inference. vLLM, llama.cpp, TGI, NVIDIA, Apple Silicon.

- [LLMKube @ GitHub](https://github.com/defilantech/llmkube).

Related contents:

- [Run LLMs on Kubernetes with LLMKube @ That DevOps Guy&amp;#039;s YouTube](https://www.youtube.com/watch?v=xdMtc8jm88Q).]]>
            </summary>
            <updated>2026-06-02T06:48:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12894</id>
            <title type="text"><![CDATA[KeyLedger]]></title>
            <link rel="alternate" href="https://links.biapy.com/bookmarklet/show" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12894"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Unified TUI for inventory, health-check, and track every API key issued across your AI providers. 

A unified view of every API key across all your AI providers — with health scoring, snapshot diffs, and encrypted credential storage.

KeyLedger is an interactive terminal dashboard that gives you a unified view of every API key issued across your AI providers — with health scoring, snapshot diffs, and encrypted credential storage.]]>
            </summary>
            <updated>2026-06-02T06:42:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12831</id>
            <title type="text"><![CDATA[whichllm]]></title>
            <link rel="alternate" href="https://github.com/Andyyyy64/whichllm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12831"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Find the best local LLM that actually runs on your hardware.

Auto-detects your GPU/CPU/RAM and ranks the top models from HuggingFace that fit your system.

 Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly.]]>
            </summary>
            <updated>2026-05-25T06:19:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12828</id>
            <title type="text"><![CDATA[Orthrus]]></title>
            <link rel="alternate" href="https://github.com/chiennv2000/orthrus" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12828"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fast, lossless LLM inference via dual-view diffusion decoding. 
Memory-Efficient Parallel Token Generation via Dual-View Diffusion.

Official implementation and model checkpoints for Orthrus, a dual-architecture framework that unifies the exact generation fidelity of autoregressive Large Language Models (LLMs) with the high-speed parallel token generation of diffusion models.]]>
            </summary>
            <updated>2026-05-25T06:15:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12795</id>
            <title type="text"><![CDATA[Lemonade]]></title>
            <link rel="alternate" href="https://lemonade-server.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12795"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Refreshingly simple local chat.
 Local AI for Text, Images, and Speech

The omni-modal alternative to cloud AI. Automatically optimized for your GPU and NPU. Open source, community driven, and private.

- [Lemonade @ GitHub](https://github.com/lemonade-sdk/lemonade).

Related contents:

- [Lemonade - L&amp;#039;IA locale sur NPU AMD, GPU et Mac @ Korben :fr:](https://korben.info/lemonade-sdk-serveur-llm-local-npu-amd.html).]]>
            </summary>
            <updated>2026-05-20T09:41:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12788</id>
            <title type="text"><![CDATA[Dream Server]]></title>
            <link rel="alternate" href="https://github.com/Light-Heart-Labs/DreamServer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12788"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Local AI anywhere, for everyone — LLM inference, chat UI, voice, agents, workflows, RAG, and image generation. No cloud, no subscriptions. 

Dream Server is the exit. A local-first AI stack — LLM inference, chat, voice, agents, workflows, RAG, image generation, and privacy tools — deployed on your hardware with a single command. No cloud required. No subscriptions required. No one watching. Cloud and hybrid API modes are optional when you choose them.]]>
            </summary>
            <updated>2026-05-18T11:57:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12773</id>
            <title type="text"><![CDATA[LLPhant]]></title>
            <link rel="alternate" href="https://github.com/LLPhant/LLPhant" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12773"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A comprehensive PHP Generative AI Framework using OpenAI GPT 4. Inspired by Langchain.

Related contents:

- [LLPhant: A PHP Generative AI Framework Inspired by LangChain @ Laravel News](https://laravel-news.com/llphant-a-php-generative-ai-framework-inspired-by-langchain).]]>
            </summary>
            <updated>2026-05-15T14:59:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12672</id>
            <title type="text"><![CDATA[How LLMs Work — A Visual Deep Dive]]></title>
            <link rel="alternate" href="https://ynarwal.github.io/how-llms-work/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12672"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A complete walkthrough of how large language models like ChatGPT are built — from raw internet text to a conversational assistant. Based on Andrej Karpathy&amp;#039;s technical deep dive.

- [How LLMs Actually Work @ GitHub](http://github.com/ynarwal/how-llms-work).]]>
            </summary>
            <updated>2026-05-14T07:52:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12654</id>
            <title type="text"><![CDATA[Pike Agent]]></title>
            <link rel="alternate" href="https://github.com/synacktiv/pike-agent" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12654"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Experimental Linux strace LLM agent.

pike-agent records and analyzes how programs behave on Linux. It traces a program&amp;#039;s activity, indexes it into a database, and lets you chat with an LLM agent about it in a TUI.

Related contents:

- [Dites bonjour à Pike! @ Synacktiv :fr:](https://www.synacktiv.com/publications/dites-bonjour-a-pike).]]>
            </summary>
            <updated>2026-04-30T11:18:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12618</id>
            <title type="text"><![CDATA[Is Your Site Agent-Ready?]]></title>
            <link rel="alternate" href="https://isitagentready.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12618"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Scan your website to see how ready it is for AI agents. We check multiple emerging standards — from robots.txt and Markdown negotiation to MCP, OAuth, Agent Skills and agentic commerce.]]>
            </summary>
            <updated>2026-04-24T13:34:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12611</id>
            <title type="text"><![CDATA[HasAIbeenPwned]]></title>
            <link rel="alternate" href="https://hasaibeenpwned.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12611"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Model Security Database.

Track jailbreaks, prompt injections, and security incidents across all major AI models. The question is not if - it&amp;#039;s when.]]>
            </summary>
            <updated>2026-04-23T13:56:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12600</id>
            <title type="text"><![CDATA[RAG-Anything]]></title>
            <link rel="alternate" href="https://github.com/HKUDS/RAG-Anything" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12600"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[All-in-One RAG Framework.

RAG-Anything eliminates the need for multiple specialized tools. It provides seamless processing and querying across all content modalities within a single integrated framework. Unlike conventional RAG approaches that struggle with non-textual elements, our all-in-one system delivers comprehensive multimodal retrieval capabilities.

Users can query documents containing interleaved text, visual diagrams, structured tables, and mathematical formulations through one cohesive interface. This consolidated approach makes RAG-Anything particularly valuable for academic research, technical documentation, financial reports, and enterprise knowledge management where rich, mixed-content documents demand a unified processing framework.]]>
            </summary>
            <updated>2026-04-22T12:48:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12593</id>
            <title type="text"><![CDATA[GAIA SDK]]></title>
            <link rel="alternate" href="https://amd-gaia.ai/docs" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12593"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[GAIA Logo GAIA: AI Agent Framework for AMD Ryzen AI.

GAIA is AMD&amp;#039;s open-source framework for building intelligent AI agents that run 100% locally on AMD Ryzen AI hardware. Keep your data private, eliminate cloud costs, and deploy in air-gapped environments—all with hardware-accelerated performance.

- [GAIA @ GitHub](https://github.com/amd/gaia).

Related contents:

- [AMD&amp;#039;s GAIA Makes It Easier To Import/Export Custom AI Agents Across PCs @ phoronix](https://www.phoronix.com/news/AMD-GAIA-Import-Export-Agent).
- [AMD GAIA 0.17.3 sait maintenant empaqueter vos agents IA dans un installeur custom @ Korben :fr:](https://korben.info/amd-gaia-0-17-3-sait-maintenant-empaqueter-vos-agents-ia-dans-un-installeur-custom.html).]]>
            </summary>
            <updated>2026-04-21T13:25:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12533</id>
            <title type="text"><![CDATA[Datadog SAIST]]></title>
            <link rel="alternate" href="https://github.com/dataDog/datadog-saist" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12533"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Datadog Static AI Security Testing (SAIST) tool.

Code Security scans your first-party code and open source libraries used in your applications in both your repositories and running services, providing end-to-end visibility from development to production. 

Related contents:

- [Introducing our open source AI-native SAST @ Datadog](https://www.datadoghq.com/blog/open-source-ai-sast/).]]>
            </summary>
            <updated>2026-04-13T11:51:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12491</id>
            <title type="text"><![CDATA[Vera]]></title>
            <link rel="alternate" href="https://veralang.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12491"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A language designed for machines to write.
A programming language designed for LLMs to write, not humans.

Vera (v-ERR-a) is a programming language designed for large language models to write. The name comes from the Latin veritas (truth). Programs compile to WebAssembly and run at the command line or in the browser.

- [Vera @ GitHub](https://github.com/aallan/vera).]]>
            </summary>
            <updated>2026-04-09T11:45:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12476</id>
            <title type="text"><![CDATA[Mesh LLM]]></title>
            <link rel="alternate" href="https://github.com/michaelneale/mesh-llm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12476"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[reference impl with llama.cpp compiled to distributed inference across machines, with real end to end demo.

Mesh LLM lets you pool spare GPU capacity across machines and expose the result as one OpenAI-compatible API.

If a model fits on one machine, it runs there. If it does not, Mesh LLM automatically spreads the work across the mesh.

Related contents:

- [Episode 661: Sink Your Claws In @ Linux Unplugged](https://linuxunplugged.com/661).]]>
            </summary>
            <updated>2026-04-09T06:08:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12445</id>
            <title type="text"><![CDATA[GuppyLM]]></title>
            <link rel="alternate" href="https://github.com/arman-bd/guppylm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12445"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A ~9M parameter LLM that talks like a small fish.

This project exists to show that training your own language model is not magic. No PhD required. No massive GPU cluster. One Colab notebook, 5 minutes, and you have a working LLM that you built from scratch — data generation, tokenizer, model architecture, training loop, and inference. If you can run a notebook, you can train a language model.]]>
            </summary>
            <updated>2026-04-07T07:32:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12444</id>
            <title type="text"><![CDATA[apfel]]></title>
            <link rel="alternate" href="https://apfel.franzai.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12444"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The free AI already on your Mac.

macOS Tahoe ships with a 3B parameter LLM. apfel gives you CLI access with one brew install. No model downloads, no API keys, no configuration needed, just works.

- [apfel @ GitHub](https://github.com/Arthur-Ficial/apfel).

Related contents:

- [Apfel - Le LLM caché de votre Mac enfin libéré @ Korben :fr:](https://korben.info/apfel-ia-mac-apple-silicon.html).]]>
            </summary>
            <updated>2026-04-07T07:09:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12443</id>
            <title type="text"><![CDATA[llama.cpp TurboQuant]]></title>
            <link rel="alternate" href="https://github.com/TheTom/llama-cpp-turboquant" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12443"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[llama.cpp fork with TurboQuant optimization

Related contents:

- [TurboQuant - Un LLM de 104B sur un MacBook, merci Google @ Korben :fr:](https://korben.info/turboquant-compression-kv-cache-llm.html).]]>
            </summary>
            <updated>2026-04-07T07:04:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12437</id>
            <title type="text"><![CDATA[Gemma Gem]]></title>
            <link rel="alternate" href="https://github.com/kessler/gemma-gem" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12437"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Gemma Gem runs Google&amp;#039;s Gemma 4 model entirely on-device via WebGPU — no API keys, no cloud, no data leaving your machine. 

Your personal AI assistant living right inside the browser. Gemma Gem runs Google&amp;#039;s Gemma 4 model entirely on-device via WebGPU — no API keys, no cloud, no data leaving your machine. It can read pages, click buttons, fill forms, run JavaScript, and answer questions about any site you visit.]]>
            </summary>
            <updated>2026-04-09T09:11:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12435</id>
            <title type="text"><![CDATA[LiteRT-LM]]></title>
            <link rel="alternate" href="https://github.com/google-ai-edge/LiteRT-LM" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12435"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LiteRT-LM is Google&amp;#039;s production-ready, high-performance, open-source inference framework for deploying Large Language Models on edge devices.]]>
            </summary>
            <updated>2026-04-07T05:54:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12430</id>
            <title type="text"><![CDATA[ZML - Model to Metal]]></title>
            <link rel="alternate" href="https://zml.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12430"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[ZML is a production inference stack, purpose-built to decouple AI workloads from proprietary hardware.

Any model, many hardwares, one codebase, peak performance.
Compiled directly to NVIDIA, AMD, TPU, Trainium for peak hardware performance on any accelerator. No rewriting.

- [ZML @ GitHub](https://github.com/zml/zml).

Related contents:

- [Introducing ZML/v2 @ ZML](https://zml.ai/posts/zml-v2/).]]>
            </summary>
            <updated>2026-04-04T09:29:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12413</id>
            <title type="text"><![CDATA[Folo]]></title>
            <link rel="alternate" href="https://folo.is/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12413"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Folo is the AI RSS Reader

AI RSS Reader for deep, noise-free reading with contextual AI.

The AI that reads the internet for you,
cutting through noise to surface the knowledge you actually care about.

- [Folo @ GitHub](https://github.com/RSSNext/Folo).]]>
            </summary>
            <updated>2026-04-03T17:22:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12405</id>
            <title type="text"><![CDATA[pGenie]]></title>
            <link rel="alternate" href="https://pgenie.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12405"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Write SQL. Ship confidence.
SQL-first tooling for PostgreSQL
Type-safe PostgreSQL client code generator.

pGenie validates SQL, manages indexes, and generates type-safe client SDKs — all derived from the migrations and queries in plain SQL. 

- [pGenie @ GitHub](https://github.com/pgenie-io/pgenie).]]>
            </summary>
            <updated>2026-04-03T16:43:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12379</id>
            <title type="text"><![CDATA[Langflow]]></title>
            <link rel="alternate" href="https://www.langflow.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12379"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Low-code AI builder for agentic and RAG applications.
 Langflow is a powerful tool for building and deploying AI-powered agents and workflows. 

Langflow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.

- [Langflow @ GitHub](https://github.com/langflow-ai/langflow).

Related contents:

- [CVE-2026-33017 Detail @ NIST](https://nvd.nist.gov/vuln/detail/CVE-2026-33017).
- [Using AI for Terraform: running locally with Langflow, OpenSearch, &amp;amp; Ollama @ Rosemary Wang&amp;#039;s dev.to](https://dev.to/joatmon08/using-ai-for-terraform-running-a-locally-with-langflow-opensearch-ollama-5co6).]]>
            </summary>
            <updated>2026-04-08T05:59:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12376</id>
            <title type="text"><![CDATA[Onyx AI]]></title>
            <link rel="alternate" href="https://onyx.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12376"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source Enterprise Search &amp;amp; AI Assistant.
Give your team superpowers.

Onyx is the open-source AI chat connected to your docs, apps, and people.
 Open Source AI Platform - AI Chat with advanced features that works with every LLM.


Onyx is a feature-rich, self-hostable Chat UI that works with any LLM. It is easy to deploy and can run in a completely airgapped environment.
Onyx comes loaded with advanced features like Agents, Web Search, RAG, MCP, Deep Research, Connectors to 40+ knowledge sources, and more.

- [Onyx @ GitHub](https://github.com/onyx-dot-app/onyx)]]>
            </summary>
            <updated>2026-03-30T18:47:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12364</id>
            <title type="text"><![CDATA[CyberDeck]]></title>
            <link rel="alternate" href="https://cyberdeck.co.in/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12364"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Communicate &amp;amp; Survive. When the Grid Goes Down. Offline Knowledge &amp;amp; Survival Platform.

CyberDeck is an offline-first communication and knowledge platform. Transform any device into a decentralized mesh node to chat, share, and learn without internet.

 Portable offline knowledge, AI, and mesh communication platform. Run local LLMs, Wikipedia, and decentralized networking without internet. 

- [CyberDeck @ GitHub](https://github.com/sarogamedev/CyberDeck).]]>
            </summary>
            <updated>2026-03-29T15:38:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12343</id>
            <title type="text"><![CDATA[KAITO]]></title>
            <link rel="alternate" href="https://kaito-project.github.io/kaito/docs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12343"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Kubernetes AI Toolchain Operator.

KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster. The target models are popular open-sourced large models such as falcon and phi-3.

- [KAITO @ GitHub](https://github.com/kaito-project/kaito).

Related contents:

- [Building a Kubernetes-native pattern for AI infrastructure at scale @ The New Stack](https://thenewstack.io/kubernetes-native-ai-infrastructure/).]]>
            </summary>
            <updated>2026-03-28T14:42:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12336</id>
            <title type="text"><![CDATA[llmfit]]></title>
            <link rel="alternate" href="https://github.com/AlexsJones/llmfit" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12336"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Hundreds of models &amp;amp; providers. One command to find what runs on your hardware.

A terminal tool that right-sizes LLM models to your system&amp;#039;s RAM, CPU, and GPU. Detects your hardware, scores each model across quality, speed, fit, and context dimensions, and tells you which ones will actually run well on your machine.

Ships with an interactive TUI (default) and a classic CLI mode. Supports multi-GPU setups, MoE architectures, dynamic quantization selection, speed estimation, and local runtime providers (Ollama, llama.cpp, MLX, Docker Model Runner, LM Studio).

Related contents:

- [\#130 - News avril 2026, Cursor et Copilot dans la tourmente, Axios compromis et Arrow JS @ Double Slash :fr:](https://double-slash.dev/podcasts/news-avril26/).
- [llmfit - L&amp;#039;outil qui sait quel LLM votre PC peut encaisser @ Korben :fr:](https://korben.info/llmfit-trouver-llm-compatible-hardware.html).
- [LLMFit : Quel LLM faire tourner sur votre ordinateur ? @ Geeek :fr:](https://www.geeek.org/llmfit-llm-local/).]]>
            </summary>
            <updated>2026-04-30T11:15:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12325</id>
            <title type="text"><![CDATA[Flash-MoE]]></title>
            <link rel="alternate" href="https://github.com/danveloper/flash-moe" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12325"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Running a 397B Parameter Model on a Laptop.

Pure C/Metal inference engine that runs Qwen3.5-397B-A17B (a 397 billion parameter Mixture-of-Experts model) on a MacBook Pro with 48GB RAM at 4.4+ tokens/second with production-quality output including tool calling.

The entire 209GB model streams from SSD through a custom Metal compute pipeline. No Python. No frameworks. Just C, Objective-C, and hand-tuned Metal shaders.]]>
            </summary>
            <updated>2026-03-28T08:23:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12306</id>
            <title type="text"><![CDATA[Opilot]]></title>
            <link rel="alternate" href="https://opilot.self.agency/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12306"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Ollama for GitHub Copilot VS Code Extension.
Run Ollama models with full tool and vision support inside GitHub Copilot Chat.

Opilot integrates the full Ollama ecosystem — local models, cloud models, and the Ollama model library — directly into VS Code&amp;#039;s Copilot Chat interface. Your conversations never leave your machine when using local models, and you can switch between models without leaving the editor.

- [Opilot @ GitHub](https://github.com/selfagency/opilot).]]>
            </summary>
            <updated>2026-03-26T16:12:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12304</id>
            <title type="text"><![CDATA[Instructor]]></title>
            <link rel="alternate" href="https://useinstructor.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12304"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Structure LLM Outputs with Ease.
Structured outputs powered by LLMs.

The simplest way to extract structured data from LLMs with type safety and validation.

Get reliable JSON from any LLM. Built on Pydantic for validation, type safety, and IDE support.

- [Instructor (Python) documentation](https://python.useinstructor.com/).
- [Instructor (Python) @ GitHub](https://github.com/567-labs/instructor).

- [Instructor (JS) documentation](https://js.useinstructor.com/).
- [Instructor (JS) @ GitHub](https://github.com/567-labs/instructor-js).]]>
            </summary>
            <updated>2026-03-26T15:59:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12293</id>
            <title type="text"><![CDATA[Ensu]]></title>
            <link rel="alternate" href="https://ente.com/ensu/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12293"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Introducing Ensu, our first step toward a private, personal LLM app that runs on your device and grows with you over time.]]>
            </summary>
            <updated>2026-03-26T12:50:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12264</id>
            <title type="text"><![CDATA[Claude Octopus]]></title>
            <link rel="alternate" href="https://github.com/nyldn/claude-octopus" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12264"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Multi-LLM orchestration plugin for Claude Code — 8 providers (Codex, Gemini, Claude, Perplexity, OpenRouter, Copilot, Qwen, Ollama), 47 commands, 50 skills, Double Diamond workflows .

Multi-LLM orchestration plugin for Claude Code — coordinates Codex, Gemini, Perplexity, OpenRouter, Copilot, Qwen, and Ollama with consensus gates. Eight tentacles, zero blind spots.

Related contents:

- [Claude Octopus - Faites débattre 3 IA sur votre code @ Korben :fr:](https://korben.info/claude-octopus-orchestrateur-multi-ia-claude-code.html).]]>
            </summary>
            <updated>2026-03-23T16:27:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12234</id>
            <title type="text"><![CDATA[Qevlar AI]]></title>
            <link rel="alternate" href="https://www.qevlar.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12234"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn SOC Noise into Real Signals. Autonomous SOC Platform.

Qevlar AI investigates every alert like your top analyst would. So your SOC focuses on real threats, not alert firefighting.

Related contents:

- [Episode \#536 consacré à l’automatisation des investigations du SOC @ NoLimitSecu :fr:](https://www.nolimitsecu.fr/automatisation-des-investigations-du-soc/).]]>
            </summary>
            <updated>2026-03-23T13:28:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12224</id>
            <title type="text"><![CDATA[CanIRun.ai]]></title>
            <link rel="alternate" href="https://www.canirun.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12224"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Can I Run AI locally? 

 Find out which AI models your machine can actually run.

Related contents:

- [\#130 - News avril 2026, Cursor et Copilot dans la tourmente, Axios compromis et Arrow JS @ Double Slash :fr:](https://double-slash.dev/podcasts/news-avril26/).]]>
            </summary>
            <updated>2026-04-09T06:02:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12194</id>
            <title type="text"><![CDATA[Chat SDK]]></title>
            <link rel="alternate" href="https://chat-sdk.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12194"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A unified TypeScript SDK for building chat bots across Slack, Microsoft Teams, Google Chat, Discord, Telegram, GitHub, Linear, and WhatsApp. Write your bot logic once, deploy everywhere.

- [Chat SDK @ GitHub](https://github.com/vercel/chat).

Related contents:

- [\#129 - News Mars 2026, Vite+, Void Cloud, du drama et de l&amp;#039;IA @ Double Slash :fr:](https://double-slash.dev/podcasts/news-mars26/).]]>
            </summary>
            <updated>2026-03-20T07:21:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12189</id>
            <title type="text"><![CDATA[Argus]]></title>
            <link rel="alternate" href="https://tryargus.cloud/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12189"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-Native Infrastructure Monitoring.
Argus uses AI to detect anomalies, investigate incidents, and resolve issues — before your users notice.

 AI-native observability for production systems. Automatically understands your application from runtime data and logs. No dashboards. No manual configuration. 

 Argus is an open-source observability platform with a built-in AI agent that monitors your infrastructure, investigates anomalies autonomously, and proposes fixes — all through a chat interface. Think Datadog + ChatGPT, self-hosted and under your control. 

- [Argus @ GitHub](https://github.com/precious112/Argus).]]>
            </summary>
            <updated>2026-03-19T14:39:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12172</id>
            <title type="text"><![CDATA[OpenReview]]></title>
            <link rel="alternate" href="https://openreview.labs.vercel.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12172"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open-source, self-hosted AI code review bot. Deploy to Vercel, connect a GitHub App, and get on-demand PR reviews powered by Claude.

- [OpenReview @ GitHub](https://github.com/vercel-labs/openreview).]]>
            </summary>
            <updated>2026-03-18T11:02:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12166</id>
            <title type="text"><![CDATA[RAGFlow]]></title>
            <link rel="alternate" href="https://ragflow.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12166"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build a superior context layer for AI agents.

Empower your AI agents through the leading open-source RAG engine, delivering reliable context and an integrated agent platform, built for enterprise.

 RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs 

- [RAGFlow @ GitHub](https://github.com/infiniflow/ragflow).]]>
            </summary>
            <updated>2026-03-17T16:36:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12165</id>
            <title type="text"><![CDATA[Dify]]></title>
            <link rel="alternate" href="https://dify.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12165"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Leading Agentic Workflow Builder.

Dify offers everything you need — agentic workflows, RAG pipelines, integrations, and observability — all in one place, putting AI power into your hands.

Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. Here&amp;#039;s a list of the core features:

- [Dify @ GitHub](https://github.com/langgenius/dify).]]>
            </summary>
            <updated>2026-03-17T16:34:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12164</id>
            <title type="text"><![CDATA[Deep Agents]]></title>
            <link rel="alternate" href="https://docs.langchain.com/oss/python/deepagents/overview" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12164"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The batteries-included agent harness.

The easiest way to start building agents and applications powered by LLMs—with built-in capabilities for task planning, file systems for context management, subagent-spawning, and long-term memory. You can use deep agents for any task, including complex, multi-step tasks.

 Agent harness built with LangChain and LangGraph. Equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - well-equipped to handle complex agentic tasks. 

Deep Agents is an agent harness. An opinionated, ready-to-run agent out of the box. Instead of wiring up prompts, tools, and context management yourself, you get a working agent immediately and customize what you need.

- [Deep Agents @ GitHub](https://github.com/langchain-ai/deepagents).

Related contents:

- [Your harness, your memory @ LangChain Blog](https://blog.langchain.com/your-harness-your-memory/).
- [Sandboxing an AI Agent @ Sajal Sharma](https://sajalsharma.com/posts/sandboxing-an-ai-agent/).]]>
            </summary>
            <updated>2026-07-02T12:11:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12150</id>
            <title type="text"><![CDATA[autoresearch]]></title>
            <link rel="alternate" href="https://github.com/karpathy/autoresearch" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12150"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI agents running research on single-GPU nanochat training automatically.



The idea: give an AI agent a small but real LLM training setup and let it experiment autonomously overnight. It modifies the code, trains for 5 minutes, checks if the result improved, keeps or discards, and repeats. You wake up in the morning to a log of experiments and (hopefully) a better model.

Related contents:

- [Autoresearch on an old research idea @ Yogesh Kumar](https://ykumar.me/blog/eclip-autoresearch/).]]>
            </summary>
            <updated>2026-03-24T13:31:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12148</id>
            <title type="text"><![CDATA[OpenRAG]]></title>
            <link rel="alternate" href="https://www.openr.ag/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12148"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[OpenRAG is a comprehensive, single package Retrieval-Augmented Generation platform built on Langflow, Docling, and Opensearch. 

Users can upload, process, and query documents through a chat interface backed by large language models and semantic search capabilities. The system utilizes Langflow for document ingestion, retrieval workflows, and intelligent nudges, providing a seamless RAG experience.

- [OpenRAG @ GitHub](https://github.com/langflow-ai/openrag).

Related contents:

- [Veille \#47 — L&amp;#039;actu de la semaine @ Camille Roux :fr:](https://www.camilleroux.com/veille-47-lactu-de-la-semaine/).
- [OpenRAG - Le RAG clé en main qui vous évite 3 jours de galère @ Korben :fr:](https://korben.info/openrag-rag-cle-en-main-documents-ia.html).]]>
            </summary>
            <updated>2026-03-23T15:21:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12127</id>
            <title type="text"><![CDATA[nao]]></title>
            <link rel="alternate" href="https://getnao.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12127"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[the Analytics Agent built for context engineering.
Build your agent context like a file system.

Deploy a chat UI for anyone to run analytics on your data.

- [nao @ GitHub](https://github.com/getnao/nao).

Related contents:

- [SQL Is Solved. Here&amp;#039;s Where Chat-BI Still Breaks @ Ju Data Engineering Newsletter](https://juhache.substack.com/p/sql-is-solved-heres-where-chat-bi).]]>
            </summary>
            <updated>2026-03-16T07:05:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12126</id>
            <title type="text"><![CDATA[BIRD-bench]]></title>
            <link rel="alternate" href="https://bird-bench.github.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12126"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A BIg Bench for Large-Scale Relational Database Grounded Text-to-SQLs.

 BIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation) represents a pioneering, cross-domain dataset that examines the impact of extensive database contents on text-to-SQL parsing. BIRD contains over 12,751 unique question-SQL pairs, 95 big databases with a total size of 33.4 GB. It also covers more than 37 professional domains, such as blockchain, hockey, healthcare and education, etc. 

- [BIRD-SQL @ GitHub](https://github.com/AlibabaResearch/DAMO-ConvAI/tree/main/bird).

Related contents:

- [SQL Is Solved. Here&amp;#039;s Where Chat-BI Still Breaks @ Ju Data Engineering Newsletter](https://juhache.substack.com/p/sql-is-solved-heres-where-chat-bi).]]>
            </summary>
            <updated>2026-03-16T07:02:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12109</id>
            <title type="text"><![CDATA[BitNet]]></title>
            <link rel="alternate" href="https://github.com/microsoft/BitNet" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12109"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Official inference framework for 1-bit LLMs.

bitnet.cpp is the official inference framework for 1-bit LLMs (e.g., BitNet b1.58). It offers a suite of optimized kernels, that support fast and lossless inference of 1.58-bit models on CPU and GPU (NPU support will coming next).]]>
            </summary>
            <updated>2026-03-13T13:00:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12103</id>
            <title type="text"><![CDATA[OBLITERATUS]]></title>
            <link rel="alternate" href="https://github.com/elder-plinius/OBLITERATUS" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12103"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[OBLITERATE THE CHAINS THAT BIND YOU.
 Break the chains. Free the mind. Keep the brain. 

OBLITERATUS is the most advanced open-source toolkit for understanding and removing refusal behaviors from large language models — and every single run makes it smarter. It implements abliteration — a family of techniques that identify and surgically remove the internal representations responsible for content refusal, without retraining or fine-tuning. The result: a model that responds to all prompts without artificial gatekeeping, while preserving its core language capabilities.

Related contents:

- [OBLITERATUS, l&amp;#039;outil qui débride toutes les IA ? @ Choses à Savoir TECH :fr:](https://shows.acast.com/choses-a-savoir-technologie/episodes/obliteratus-loutil-qui-debride-toutes-les-ia).]]>
            </summary>
            <updated>2026-03-13T06:42:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12096</id>
            <title type="text"><![CDATA[AI Best Practices — Semgrep Rules]]></title>
            <link rel="alternate" href="https://github.com/semgrep/ai-best-practices" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12096"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Semgrep Pro Rules to ensure code using LLMs is following best practices.

Semgrep rules that catch common trust &amp;amp; safety mistakes in LLM-powered applications. Scan any codebase in seconds to find hardcoded API keys, missing safety checks, prompt injection risks, and unhandled errors across all major AI providers.]]>
            </summary>
            <updated>2026-03-12T11:15:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12087</id>
            <title type="text"><![CDATA[RCLI]]></title>
            <link rel="alternate" href="https://github.com/RunanywhereAI/rcli" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12087"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Talk to your Mac, query your docs, no cloud required. On-device voice AI + RAG. 

RCLI is an on-device voice AI for macOS. A complete STT + LLM + TTS pipeline running natively on Apple Silicon — 38 macOS actions via voice, local RAG over your documents, sub-200ms end-to-end latency. No cloud, no API keys.]]>
            </summary>
            <updated>2026-03-11T12:12:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12070</id>
            <title type="text"><![CDATA[PageAgent]]></title>
            <link rel="alternate" href="https://alibaba.github.io/page-agent/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12070"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The AI Operator Living in Your Web Page.
 JavaScript in-page GUI agent. Control web interfaces with natural language. 

🪄One line of code, turns your website into an AI-native app.
Users give natural language commands, AI handles the rest.

- [PageAgent @ GitHub](https://github.com/alibaba/page-agent).]]>
            </summary>
            <updated>2026-03-09T12:15:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12063</id>
            <title type="text"><![CDATA[Perspective Server]]></title>
            <link rel="alternate" href="https://github.com/Techopolis/Perspective-Server" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12063"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[macOS menu bar app that exposes Apple&amp;#039;s on-device Foundation Models as an OpenAI-compatible local API. Zero cloud. Zero dependencies. 

- [Perspective Intelligence Web (Community Edition) @ GitHub](https://github.com/Techopolis/perspective-intelligence-web-community).

Related contents:

- [Perspective Intelligence - L&amp;#039;IA de votre Mac sort de sa cage @ Korben :fr:](https://korben.info/perspective-intelligence-web-community.html).]]>
            </summary>
            <updated>2026-03-09T09:59:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12049</id>
            <title type="text"><![CDATA[Threat Designer]]></title>
            <link rel="alternate" href="https://github.com/awslabs/threat-designer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12049"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Threat Designer is a GenerativeAI application designed to automate and streamline the threat modeling process for secure system design. 

Threat Designer is an AI-driven agent that automates and streamlines the threat modeling process for secure system design. Harnessing the power of large language models (LLMs), it analyzes system architectures, identifies potential security threats, and generates detailed threat models—empowering developers and security professionals to incorporate security from the earliest stages of development.]]>
            </summary>
            <updated>2026-03-09T07:19:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12044</id>
            <title type="text"><![CDATA[Label Studio]]></title>
            <link rel="alternate" href="https://labelstud.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12044"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source Data Labeling.

The most flexible data labeling platform to fine-tune LLMs, prepare training data, or evaluate AI systems.
 Label Studio is a multi-type data labeling and annotation tool with standardized output format.
Label Studio is an open source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. It can be used to prepare raw data or improve existing training data to get more accurate ML models.

- [Label Studio @ GitHub](https://github.com/HumanSignal/label-studio/).]]>
            </summary>
            <updated>2026-03-06T14:56:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12041</id>
            <title type="text"><![CDATA[AReaL]]></title>
            <link rel="alternate" href="https://inclusionai.github.io/AReaL/en/intro.html" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12041"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Lightning-Fast RL for LLM Reasoning and Agents. Made Simple &amp;amp; Flexible. 

AReaL is an open-source fully asynchronous reinforcement learning training system for large reasoning and agentic models, developed by members from Tsinghua IIIS and the AReaL Team at Ant Group. Built upon the open-source project ReaLHF, we are fully committed to open-source principles by providing the training details, data, and infrastructure required to reproduce our results, along with the models themselves. AReaL aims to help everyone build their own AI agents easily and affordably. Our team loves milk tea because it&amp;#039;s delicious, customizable, and affordable—we hope you enjoy our project just as much as you&amp;#039;d enjoy real milk tea. Cheers!

- [AReaL @ GitHub](https://github.com/inclusionAI/AReaL).]]>
            </summary>
            <updated>2026-03-06T12:35:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11922</id>
            <title type="text"><![CDATA[RuVector]]></title>
            <link rel="alternate" href="https://github.com/ruvnet/ruvector" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11922"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The vector database that gets smarter the more you use it — and now ships as a cognitive container.

RuVector is a High Performance, Real-Time, Self-Learning, Vector Graph Neural Network, and Database built in Rust. 

Most vector databases are static — they store embeddings and search them. That&amp;#039;s it. RuVector is different: it learns from every query, runs LLMs locally, scales horizontally, boots as a Linux microservice from a single file, and costs nothing to operate.]]>
            </summary>
            <updated>2026-02-25T12:43:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11906</id>
            <title type="text"><![CDATA[Codeplain]]></title>
            <link rel="alternate" href="https://www.codeplain.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11906"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[spec-driven, production-ready code generation.

- [Codeplain @ GitHub](https://github.com/Codeplain-ai/codeplain).

Related contents:

- [The uncomfortable truth about vibe coding @ RedHat Developer](https://developers.redhat.com/articles/2026/02/17/uncomfortable-truth-about-vibe-coding).]]>
            </summary>
            <updated>2026-02-24T07:18:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11905</id>
            <title type="text"><![CDATA[Augustus]]></title>
            <link rel="alternate" href="https://github.com/praetorian-inc/augustus" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11905"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM Vulnerability Scanner.

Test large language models against 210+ adversarial attacks covering prompt injection, jailbreaks, encoding exploits, and data extraction.

Related contents:

- [Digest \#202: Terraform Claude Skills, FinOps FOCUS 1.2, AI Fatigue for Cloud Engineers, and MCP for Web Data Extraction @ DevOps Bulletin](https://www.devopsbulletin.com/p/digest-202-terraform-claude-skills).]]>
            </summary>
            <updated>2026-02-24T07:13:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11860</id>
            <title type="text"><![CDATA[Premodern Concordance]]></title>
            <link rel="alternate" href="https://premodern-concordance.vercel.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11860"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Cross-linguistic entity matching across early modern texts.

 A prototype for a digital history project aimed at creating a searchable concordance, knowledge graph, and resources for better understanding premodern science and natural knowledge. 

- [Premodern Concordance @ GitHub](https://github.com/benjaminbreen/premodern-concordance).

Related contents:

- [What is happening to writing? @ Res Obscura](https://resobscura.substack.com/p/what-is-happening-to-writing).]]>
            </summary>
            <updated>2026-02-19T13:02:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11833</id>
            <title type="text"><![CDATA[Lingoku]]></title>
            <link rel="alternate" href="https://lingoku.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11833"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Learn Languages While You Watch.
No More Memorizing.

Turn YouTube, Netflix, and Bilibili into your personal language tutor. Just watch naturally, and let AI help you understand and learn new words instantly.

Related contents:

- [Lingoku - L&amp;#039;extension qui transforme votre navigation en cours de japonais @ Korben :fr:](https://korben.info/lingoku-apprendre-japonais-extension-chrome-firefo.html).]]>
            </summary>
            <updated>2026-02-16T09:37:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11828</id>
            <title type="text"><![CDATA[GitHub Agentic Workflows]]></title>
            <link rel="alternate" href="https://github.github.com/gh-aw/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11828"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Write agentic workflows in natural language markdown, and run them in GitHub Actions.

- [GitHub Agentic Workflows @ GitHub](https://github.com/github/gh-aw).

Related contents:

- [gh-aw - GitHub lâche des agents IA dans vos pipelines @ Korben :fr:](https://korben.info/gh-aw-github-agents-ia-pipelines.html).
- [Automate repository tasks with GitHub Agentic Workflows @ GitHub Blog](https://github.blog/ai-and-ml/automate-repository-tasks-with-github-agentic-workflows/).
- [A GitHub agentic workflow @ A Java geek](https://blog.frankel.ch/agentic-github-workflows/).]]>
            </summary>
            <updated>2026-04-20T05:21:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11797</id>
            <title type="text"><![CDATA[Distill]]></title>
            <link rel="alternate" href="https://distill.siddhantkhare.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11797"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Context window optimization for LLMs.
Reliable LLM outputs start with clean context.

A reliability layer for LLM context. Deterministic deduplication that removes redundancy before it reaches your model.
Less redundant data. Lower costs. Faster responses.
More efficient &amp;amp; deterministic results.

- [Distill @ GitHub](https://github.com/Siddhant-K-code/distill).

Related contents:

- [AI fatigue is real and nobody talks about it @ Siddhant Khare](https://siddhantkhare.com/writing/ai-fatigue-is-real).]]>
            </summary>
            <updated>2026-02-13T09:30:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11788</id>
            <title type="text"><![CDATA[Julius]]></title>
            <link rel="alternate" href="https://github.com/praetorian-inc/julius" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11788"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM Service Fingerprinting Tool.

Simple LLM service identification - translate IP:Port to Ollama, vLLM, LiteLLM, or 30+ other AI services in seconds.

Julius is an LLM service fingerprinting tool for security professionals. It detects which AI server software is running on network endpoints during penetration tests, attack surface discovery, and security assessments.

Unlike model fingerprinting tools that identify which LLM generated text, Julius identifies the server infrastructure: Is that endpoint running Ollama? vLLM? LiteLLM? A Hugging Face deployment? Julius answers in seconds.

Related contents:

- [Erreur 403 | \#63 :fr:](https://newsletter.erreur403.fr/p/erreur-403-63).
- [Introducing Julius: Open Source LLM Service Fingerprinting @ Praetorian](https://www.praetorian.com/blog/introducing-julius-open-source-llm-service-fingerprinting/).]]>
            </summary>
            <updated>2026-02-12T09:36:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11720</id>
            <title type="text"><![CDATA[God&amp;#039;s Eye]]></title>
            <link rel="alternate" href="https://github.com/Vyntral/god-eye" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11720"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-powered subdomain enumeration tool with local LLM analysis via Ollama - 100% private, zero API costs.

God&amp;#039;s Eye is a powerful, ultra-fast subdomain enumeration and reconnaissance tool written in Go. It combines multiple passive sources with active DNS brute-forcing and comprehensive security checks to provide a complete picture of a target&amp;#039;s attack surface.

Related contents:

- [Newsletter du 19 Janvier 2026 @ Rudeops :fr:](https://www.rudeops.com/newsletter/2026-01-19-rudeops-newsletter/).]]>
            </summary>
            <updated>2026-02-06T10:17:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11696</id>
            <title type="text"><![CDATA[Kthena]]></title>
            <link rel="alternate" href="https://kthena.volcano.sh/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11696"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Kubernetes-native AI serving platform for scalable model serving. 

- [Kthena @ GitHub](https://github.com/volcano-sh/kthena).

Related contents:

- [Introducing Kthena: LLM inference for the cloud native era @ CNCF](https://www.cncf.io/blog/2026/01/28/introducing-kthena-llm-inference-for-the-cloud-native-era/).]]>
            </summary>
            <updated>2026-02-05T08:12:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11687</id>
            <title type="text"><![CDATA[Tokentap]]></title>
            <link rel="alternate" href="https://github.com/jmuncor/tokentap?utm_source=changelog-news" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11687"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Intercept LLM API traffic and visualize token usage in a real-time terminal dashboard. Track costs, debug prompts, and monitor context window usage across your AI development sessions. 

tokentap tracks token usage for LLM CLI tools with a live terminal dashboard. See exactly how many tokens you&amp;#039;re using in real-time.]]>
            </summary>
            <updated>2026-02-03T07:00:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11665</id>
            <title type="text"><![CDATA[Text2SQirreL 🐿️]]></title>
            <link rel="alternate" href="https://github.com/distil-labs/distil-text2sql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11665"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Query your data in plain English.

Turn natural language questions into SQL queries with a small, local model that matches cloud LLM accuracy.

We fine-tuned a small language model to convert plain English questions into executable SQL queries. Because it&amp;#039;s small, you can run it locally on your own machine, no API keys, no cloud dependencies, full privacy. Load your CSV files, ask questions, get answers.]]>
            </summary>
            <updated>2026-02-02T06:33:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11651</id>
            <title type="text"><![CDATA[PageIndex]]></title>
            <link rel="alternate" href="https://pageindex.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11651"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Human-like Document AI

PageIndex is a vectorless, reasoning-based RAG engine that mirrors how humans read, delivering traceable, explainable, and context-aware retrieval, without vector databases or chunking.

- [PageIndex @ GitHub](https://github.com/VectifyAI/PageIndex).]]>
            </summary>
            <updated>2026-01-30T12:52:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11639</id>
            <title type="text"><![CDATA[Sec-Context]]></title>
            <link rel="alternate" href="https://arcanum-sec.github.io/sec-context/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11639"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Code Security Anti-Patterns distilled from 150+ sources to help LLMs generate safer code. 

A comprehensive security reference distilled from 150+ sources to help LLMs generate safer code.

- [Sec-Context @ GitHub](https://github.com/Arcanum-Sec/sec-context).

Related contents:

- [Erreur 403 | #61 :fr:](https://newsletter.erreur403.fr/p/erreur-403-61).]]>
            </summary>
            <updated>2026-01-29T11:49:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11636</id>
            <title type="text"><![CDATA[Toad]]></title>
            <link rel="alternate" href="https://www.batrachian.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11636"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Universal AI Terminal Interface.

Toad is an interface to coding agents, such as Claude, Gemini, Codex, OpenHand, and many more.
Toad blends a traditional shell based workflow and powerful agentic AI, with an intuitive Terminal User Interface.

- [Toad](https://github.com/batrachianai/toad).

Related contents:

- [Introducing Claude Chic @ Matthew Rocklin](https://matthewrocklin.com/introducing-claude-chic/).]]>
            </summary>
            <updated>2026-01-28T13:19:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11598</id>
            <title type="text"><![CDATA[coreml-cli]]></title>
            <link rel="alternate" href="https://github.com/schappim/coreml-cli" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11598"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A native command-line interface for working with Apple Core ML models on macOS.
Inspect, run inference, benchmark, and manage Core ML models without Xcode or Python.

Related contents:

- [CoreML CLI - Gérez vos modèles Apple sans Xcode ! @ Korben :fr:](https://korben.info/coreml-cli-gestion-apple-modele-sans-xcode.html).]]>
            </summary>
            <updated>2026-01-26T08:18:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11547</id>
            <title type="text"><![CDATA[Gemini Voyager]]></title>
            <link rel="alternate" href="https://voyager.nagi.fun/en/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11547"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An all-in-one enhancement suite for Google Gemini - timeline navigation, folder management, prompt library, and chat export in one powerful extension. 

- [Gemini Voyager @ GitHub](https://github.com/Nagi-ovo/gemini-voyager).]]>
            </summary>
            <updated>2026-01-20T13:18:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11546</id>
            <title type="text"><![CDATA[Looper]]></title>
            <link rel="alternate" href="https://github.com/nibzard/looper" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11546"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A deterministic, autonomous loop runner for the Codex CLI. It processes exactly one task per iteration from a JSON backlog, with fresh context each run, and keeps a JSONL audit log for traceability.

Related contents:

- [Looper: The AI Junior That Never Forgets the Backlog @ Nikola Balic](https://www.nibzard.com/looper-article/).]]>
            </summary>
            <updated>2026-01-20T13:16:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11545</id>
            <title type="text"><![CDATA[LLM Loop]]></title>
            <link rel="alternate" href="https://github.com/nibzard/llm-loop" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11545"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Autonomous task execution plugin for LLM CLI - refactored modular architecture.

llm loop is a powerful plugin for the LLM CLI tool that enables autonomous, goal-oriented task execution. Unlike traditional single-turn LLM interactions, llm loop allows the AI to work persistently towards a goal by making multiple tool calls, analyzing results, and iterating until the task is complete.

Related contents:

- [Looper: The AI Junior That Never Forgets the Backlog @ Nikola Balic](https://www.nibzard.com/looper-article/).]]>
            </summary>
            <updated>2026-01-20T13:17:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11525</id>
            <title type="text"><![CDATA[OGhidra]]></title>
            <link rel="alternate" href="https://github.com/LLNL/OGhidra" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11525"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-Powered Reverse Engineering with Ghidra.

OGhidra bridges Large Language Models (LLMs) via Ollama with the Ghidra reverse engineering platform, enabling AI-driven binary analysis through natural language. Interact with Ghidra using conversational queries and automate complex reverse engineering workflows. 

Related contents:

- [OGhidra - Dopage à l&amp;#039;IA pour Ghidra en local @ Korben :fr:](https://korben.info/oghidra-dopage-a-lia-pour-ghidra-en-local.html).]]>
            </summary>
            <updated>2026-01-19T08:26:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11484</id>
            <title type="text"><![CDATA[Gambit]]></title>
            <link rel="alternate" href="https://github.com/bolt-foundry/gambit" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11484"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Agent harness framework for building, running, and verifying LLM workflows.

Gambit helps you build reliable LLM workflows by composing small, typed “decks”
with clear inputs/outputs and guardrails. Run decks locally, stream traces, and
debug with a built-in UI.]]>
            </summary>
            <updated>2026-01-16T13:03:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11483</id>
            <title type="text"><![CDATA[Oh My OpenCode]]></title>
            <link rel="alternate" href="https://github.com/code-yeongyu/oh-my-opencode" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11483"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Best Agent Harness. Meet Sisyphus: The Batteries-Included Agent that codes like you.]]>
            </summary>
            <updated>2026-01-16T12:59:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11482</id>
            <title type="text"><![CDATA[Open Responses]]></title>
            <link rel="alternate" href="https://www.openresponses.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11482"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Responses is an open-source specification and ecosystem for building multi-provider, interoperable LLM interfaces based on the OpenAI Responses API. It defines a shared schema, and tooling layer that enable a unified experience for calling language models, streaming results, and composing agentic workflows—independent of provider.

- [Open Responses @ GitHub](https://github.com/openresponses/openresponses).]]>
            </summary>
            <updated>2026-01-16T12:56:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11470</id>
            <title type="text"><![CDATA[Agent Skills]]></title>
            <link rel="alternate" href="https://agentskills.io/home" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11470"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A simple, open format for giving agents new capabilities and expertise.
Agent Skills are folders of instructions, scripts, and resources that agents can discover and use to do things more accurately and efficiently.

- [Agent Skills @ GitHub](https://github.com/agentskills/agentskills).

Related contents:

- [Vercel&amp;#039;s Agent Skills @ GitHub](https://github.com/vercel-labs/agent-skills).
- [MCP, Skills, and Agents @ cramr](https://cra.mr/mcp-skills-and-agents/).
- [Agent Skills vs. Rules vs. Commands @ builder.io](https://www.builder.io/blog/agent-skills-rules-commands).
- [3 Principles for Designing Agent Skills @ Block Engineering Blog](https://engineering.block.xyz/blog/3-principles-for-designing-agent-skills).
- [Claude Code Skills Are a Massive Security Threat — Greg Pstrucha, Sentry @ Mastra&amp;#039;s YouTube](https://www.youtube.com/watch?v=WNJHMoHTrBU).]]>
            </summary>
            <updated>2026-06-04T05:55:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11464</id>
            <title type="text"><![CDATA[WeKnora :cn:]]></title>
            <link rel="alternate" href="https://weknora.weixin.qq.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11464"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM-powered framework for deep document understanding, semantic retrieval, and context-aware answers using RAG paradigm.

It adopts a modular architecture that combines multimodal preprocessing, semantic vector indexing, intelligent retrieval, and large language model inference. At its core, WeKnora follows the RAG (Retrieval-Augmented Generation) paradigm, enabling high-quality, context-aware answers by combining relevant document chunks with model reasoning.

- [WeKnora @ GitHub](https://github.com/Tencent/WeKnora).]]>
            </summary>
            <updated>2026-01-15T06:50:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11463</id>
            <title type="text"><![CDATA[Headroom]]></title>
            <link rel="alternate" href="https://github.com/chopratejas/headroom" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11463"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Context Optimization Layer for LLM Applications.

 Cut your LLM costs by 50-90% without losing accuracy.]]>
            </summary>
            <updated>2026-01-15T06:47:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11457</id>
            <title type="text"><![CDATA[mgrep]]></title>
            <link rel="alternate" href="https://www.mgrep.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11457"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Semantic search for agents.

 A calm, CLI-native way to semantically grep everything, like code, images, pdfs and more. 

- [mgrep @ GitHub](https://github.com/mixedbread-ai/mgrep).

Related contents:

- [Mgrep c&amp;#039;est quoi ? @ RayaneRachid&amp;#039;s X](https://nitter.net/RayaneRachid_/status/2008950450931048575).
- [\#161 - Veille tech et l&amp;#039;interview de Jessim @ Quoi de neuf les devs? :fr:](https://happytodev.substack.com/p/quoi-de-neuf-les-devs-161-veille).]]>
            </summary>
            <updated>2026-01-13T14:31:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11433</id>
            <title type="text"><![CDATA[TermsTooLong]]></title>
            <link rel="alternate" href="https://www.termstoolong.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11433"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Understand Privacy &amp;amp; Legal Terms.
Plain-language analysis of Terms &amp;amp; Conditions. Know what you&amp;#039;re agreeing to before you sign up.

Related contents:

- [TermsTooLong - L&amp;#039;outil qui note les CGU que vous ne lisez jamais @ Korben :fr:](https://korben.info/termstoolong-cgu-trop-longues.html).]]>
            </summary>
            <updated>2026-01-12T08:30:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11429</id>
            <title type="text"><![CDATA[Orla]]></title>
            <link rel="alternate" href="https://github.com/dorcha-inc/orla" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11429"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A dead-simple unix tool for lightweight open-source local agents.

Orla is a unix tool for running lightweight open-source agents. It is easy to add to a script, use with pipes, or build things on top of.

Related contents:

- [Orla - L&amp;#039;outil CLI qui transforme votre terminal en assistant IA local @ Korben :fr:](https://korben.info/orla-agent-ia-local-cli.html).]]>
            </summary>
            <updated>2026-01-12T08:19:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11376</id>
            <title type="text"><![CDATA[Awesome Agentic Patterns]]></title>
            <link rel="alternate" href="https://agentic-patterns.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11376"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A curated catalogue of agentic AI patterns — real‑world tricks, workflows, and mini‑architectures that help autonomous or semi‑autonomous AI agents get useful work done in production.

- [Awesome Agentic Patterns @ GitHub](https://github.com/nibzard/awesome-agentic-patterns).

Related contents:

- [Looper: The AI Junior That Never Forgets the Backlog @ Nikola Balic](https://www.nibzard.com/looper-article/).]]>
            </summary>
            <updated>2026-01-20T13:09:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11356</id>
            <title type="text"><![CDATA[Gas Town]]></title>
            <link rel="alternate" href="https://github.com/steveyegge/gastown" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11356"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Multi-agent orchestrator for Claude Code. Track work with convoys; sling to agents.

Related contents:

- [Welcome to Gas Town @ Steve Yegge&amp;#039;s Medium](https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16dd04).
- [Gas Town Decoded @ Andrew Lilley Brinker](https://www.alilleybrinker.com/mini/gas-town-decoded/).
- [How to think about Gas Town @ Steve Klabnik](https://steveklabnik.com/writing/how-to-think-about-gas-town/).
- [Agent Psychosis: Are We Going Insane? @ Armin Ronacher&amp;#039;s Thoughts and Writings](https://lucumr.pocoo.org/2026/1/18/agent-psychosis/).
- [Gas Town’s Agent Patterns, Design Bottlenecks, and Vibecoding at Scale @ Maggie Appleton](https://maggieappleton.com/gastown/).
- [Move Over Gas Town, Claude Has First-Party Agent Orchestration @ Andrew Lilley Brinker](https://www.alilleybrinker.com/mini/move-over-gas-town/).]]>
            </summary>
            <updated>2026-02-06T14:19:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11352</id>
            <title type="text"><![CDATA[ensue]]></title>
            <link rel="alternate" href="https://ensue.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11352"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[shared memory for agents. Get smarter alongside your AI.

Your intelligence shouldn&amp;#039;t reset every conversation. Ensue is a persistent knowledge tree that grows with you - what you learn today enriches tomorrow&amp;#039;s reasoning.

- [Ensue Memory Network @ GitHub](https://github.com/mutable-state-inc/ensue-skill).]]>
            </summary>
            <updated>2026-01-05T06:58:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11350</id>
            <title type="text"><![CDATA[NERD]]></title>
            <link rel="alternate" href="https://www.nerd-lang.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11350"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The World&amp;#039;s First LLM-Native Language.
the first intermediate language designed for machine authorship.

- [NERD @ GitHub](https://github.com/Nerd-Lang/nerd-lang-core).]]>
            </summary>
            <updated>2026-01-05T06:50:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11275</id>
            <title type="text"><![CDATA[Cordon]]></title>
            <link rel="alternate" href="https://github.com/calebevans/cordon" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11275"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Reduce logs to their semantic anomalies.

Cordon uses transformer embeddings and density scoring to identify semantically unusual patterns in large log files, reducing massive logs to the most anomalous sections for analysis. Repetitive patterns (even errors) are considered &amp;quot;normal background.&amp;quot; Cordon surfaces unusual, rare, or clustered events that stand out semantically from the bulk of the logs.

Related contents:

- [Cordon - L&amp;#039;outil qui trouve les aiguilles dans vos meules de logs @ Korben :fr:](https://korben.info/cordon-detection-anomalies-logs-transformers.html).]]>
            </summary>
            <updated>2025-12-22T08:36:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11215</id>
            <title type="text"><![CDATA[Layrr]]></title>
            <link rel="alternate" href="https://www.layrr.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11215"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Layrr is the visual editor for real code.
Design visually, edit any stack, own everything. 
 A browser coding agent interface for selecting elements and sending instructions directly to Claude Code. 

- [Layrr @ GitHub](https://github.com/thetronjohnson/layrr).]]>
            </summary>
            <updated>2025-12-12T07:29:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11170</id>
            <title type="text"><![CDATA[Tesslate Studio]]></title>
            <link rel="alternate" href="https://github.com/TesslateAI/Studio" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11170"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source Locally Hosted Lovable with Full Stack Support.
The Open-Source AI Development Platform Built for Self-Hosting.

AI-powered development environment with advanced agent orchestration - designed for complete data sovereignty and infrastructure control.]]>
            </summary>
            <updated>2025-12-05T15:20:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11161</id>
            <title type="text"><![CDATA[remend]]></title>
            <link rel="alternate" href="https://streamdown.ai/docs/termination" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11161"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Unterminated Block Parsing.

Remend is a lightweight, standalone preprocessor that completes incomplete Markdown syntax.

- [Streamdown @ GitHub](https://github.com/vercel/streamdown).
- [remend @ npm](https://www.npmjs.com/package/remend).

Related contents:

- [New npm package for automatic recovery of broken streaming markdown @ Vercel](https://vercel.com/changelog/new-npm-package-for-automatic-recovery-of-broken-streaming-markdown).]]>
            </summary>
            <updated>2025-12-04T12:51:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11141</id>
            <title type="text"><![CDATA[Skald]]></title>
            <link rel="alternate" href="https://useskald.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11141"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Production-ready RAG in your infrastructure.

Skald gives you a production-ready RAG in minutes through a plug-and-play API, and then let&amp;#039;s you configure your RAG engine exactly to your needs.

Our solid defaults will work for most use cases, but you can tune every part of your RAG to better suit your needs. That means configurable vector search params, reranking, models, query rewriting, chunking (soon), and more.

- [Skald @ GitHub](https://github.com/skaldlabs/skald).

Related contents:

- [So you wanna build a local RAG? @ yakko&amp;#039;s blog](https://blog.yakkomajuri.com/blog/local-rag).]]>
            </summary>
            <updated>2025-12-01T10:13:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11138</id>
            <title type="text"><![CDATA[Metis]]></title>
            <link rel="alternate" href="https://github.com/arm/metis" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11138"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Metis is an open-source, AI-driven tool for deep security code review.

Metis is an open-source, AI-driven tool for deep security code review, created by Arm&amp;#039;s Product Security Team. It helps engineers detect subtle vulnerabilities, improve secure coding practices, and reduce review fatigue. This is especially valuable in large, complex, or legacy codebases where traditional tooling often falls short.]]>
            </summary>
            <updated>2025-12-01T09:46:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11120</id>
            <title type="text"><![CDATA[Dotprompt]]></title>
            <link rel="alternate" href="https://google.github.io/dotprompt/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11120"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Executable GenAI Prompt Templates.

Dotprompt is an executable prompt template file format for Generative AI. It is designed to be agnostic to programming language and model provider to allow for maximum flexibility in usage. Dotprompt extends the popular Handlebars templating language with GenAI-specific features.

- [Dotprompt @ GitHub](https://github.com/google/dotprompt).
- [runprompt @ GitHub](https://github.com/chr15m/runprompt).]]>
            </summary>
            <updated>2025-11-28T12:45:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11081</id>
            <title type="text"><![CDATA[smartcommit]]></title>
            <link rel="alternate" href="https://github.com/arpxspace/smartcommit" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11081"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Enforce the habit of self-documenting code through better commit messages. 

smartcommit is an intelligent, AI-powered CLI tool that helps you write semantic, Conventional Commits messages effortlessly. It analyzes your staged changes, asks clarifying questions to understand the &amp;quot;why&amp;quot; behind your code, and generates a structured commit message for you.]]>
            </summary>
            <updated>2025-11-24T12:48:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11076</id>
            <title type="text"><![CDATA[🛠️ kit]]></title>
            <link rel="alternate" href="https://kit.cased.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11076"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The toolkit for AI devtools context engineering. Build with codebase mapping, symbol extraction, and many kinds of code search. 

kit is a production-ready toolkit for codebase mapping, symbol extraction, code search, and building LLM-powered developer tools, agents, and workflows.

kit shines for getting precise, accurate, and relevant context to LLMs. Use kit to build code reviewers, code generators and graphs, even full-fledged coding assistants: all enriched with the right code context.

- [kit 🛠️ Code Intelligence Toolkit @ GitHub](https://github.com/cased/kit?utm_source=tldrnewsletter)]]>
            </summary>
            <updated>2025-11-24T12:16:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11036</id>
            <title type="text"><![CDATA[Memori]]></title>
            <link rel="alternate" href="https://memorilabs.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11036"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open-source SQL-Native memory engine for AI.
Open-Source Memory Engine for LLMs, AI Agents &amp;amp; Multi-Agent Systems.

 One line of code to give any LLM persistent, queryable memory using standard SQL databases.

Memori enables any LLM to remember conversations, learn from interactions, and maintain context across sessions with a single line: memori.enable(). Memory is stored in standard SQL databases (SQLite, PostgreSQL, MySQL) that you fully own and control.]]>
            </summary>
            <updated>2025-11-21T13:00:13+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11032</id>
            <title type="text"><![CDATA[Skyvern]]></title>
            <link rel="alternate" href="https://www.skyvern.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11032"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Browser Automation.
 Automate browser based workflows with AI.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows on a large number of websites, replacing brittle or unreliable automation solutions.

- [Skyvern @ GitHub](https://github.com/Skyvern-AI/skyvern).]]>
            </summary>
            <updated>2025-11-21T12:42:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11019</id>
            <title type="text"><![CDATA[emdash]]></title>
            <link rel="alternate" href="https://emdash.sh/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11019"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Emdash is an orchestration layer for running multiple coding agents in parallel in isolated Git worktrees.

An orchestration layer for running multiple coding agents in parallel, each isolated in its own Git worktree. Run several agent instances concurrently to tackle independent subtasks or experiments.

Emdash lets you develop and test multiple features with multiple agents in parallel. It’s provider-agnostic (we support 10+ CLIs, such as Claude Code and Codex) and runs each agent in its own Git worktree to keep changes clean; when the environment matters, you can run a PR in its own Docker container. Hand off Linear, GitHub, or Jira tickets to an agent, review diffs side-by-side, and keep everything local.

- [emdash @ GitHub](https://github.com/generalaction/emdash).]]>
            </summary>
            <updated>2026-02-25T12:42:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11017</id>
            <title type="text"><![CDATA[Tokenflood]]></title>
            <link rel="alternate" href="https://github.com/twerkmeister/tokenflood" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11017"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Tokenflood is a load testing framework for simulating arbitary loads on instruction-tuned LLMs.

Tokenflood is a load testing tool for instruction-tuned LLMs that allows you to run arbitrary load profiles without needing specific prompt and response data. Define desired prompt lengths, prefix lengths, output lengths, and request rates, and tokenflood simulates this workload for you.]]>
            </summary>
            <updated>2025-11-19T12:51:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11014</id>
            <title type="text"><![CDATA[🔂 Continuous Claude]]></title>
            <link rel="alternate" href="https://github.com/AnandChowdhary/continuous-claude" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11014"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🔂 Run Claude Code in a continuous loop, autonomously creating PRs, waiting for checks, and merging

Automated workflow that orchestrates Claude Code in a continuous loop, autonomously creating PRs, waiting for checks, and merging - so multi-step projects complete while you sleep.]]>
            </summary>
            <updated>2025-11-19T06:34:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11002</id>
            <title type="text"><![CDATA[Heretic]]></title>
            <link rel="alternate" href="https://github.com/p-e-w/heretic" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11002"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fully automatic censorship removal for language models.

Heretic is a tool that removes censorship (aka &amp;quot;safety alignment&amp;quot;) from transformer-based language models without expensive post-training. It combines an advanced implementation of directional ablation, also known as &amp;quot;abliteration&amp;quot; (Arditi et al. 2024), with a TPE-based parameter optimizer powered by Optuna.]]>
            </summary>
            <updated>2025-11-18T06:38:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10995</id>
            <title type="text"><![CDATA[Enchanted]]></title>
            <link rel="alternate" href="https://github.com/gluonfield/enchanted" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10995"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Enchanted is iOS and macOS app for chatting with private self hosted language models such as Llama2, Mistral or Vicuna using Ollama. 

Enchanted is open source, Ollama compatible, elegant macOS/iOS/visionOS app for working with privately hosted models such as Llama 2, Mistral, Vicuna, Starling and more. It&amp;#039;s essentially ChatGPT app UI that connects to your private models. The goal of Enchanted is to deliver a product allowing unfiltered, secure, private and multimodal experience across all of your devices in iOS ecosystem (macOS, iOS, Watch, Vision Pro).

Related contents:

- [Reins - Un Ollama sur mobile sans faire tourner Ollama sur mobile @ Korben :fr:](https://korben.info/reins-ollama-mobile-impossible.html).]]>
            </summary>
            <updated>2025-11-17T11:13:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10994</id>
            <title type="text"><![CDATA[Reins]]></title>
            <link rel="alternate" href="https://reins.ibrahimcetin.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10994"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chat for Ollama, Private AI Chat.

 Empowering LLM researchers and hobbyists with seamless control over self-hosted models. Connect remotely, customize prompts, manage chats, and fine-tune configurations. All in one intuitive app. 

- [Reins @ GitHub](https://github.com/ibrahimcetin/reins).

Related contents:

- [Reins - Un Ollama sur mobile sans faire tourner Ollama sur mobile @ Korben :fr:](https://korben.info/reins-ollama-mobile-impossible.html).]]>
            </summary>
            <updated>2025-11-17T11:10:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10953</id>
            <title type="text"><![CDATA[Gerbil]]></title>
            <link rel="alternate" href="https://github.com/lone-cloud/gerbil" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10953"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A desktop app to easily run Large Language Models locally.]]>
            </summary>
            <updated>2025-11-13T12:31:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10946</id>
            <title type="text"><![CDATA[tokuin]]></title>
            <link rel="alternate" href="https://github.com/nooscraft/tokuin" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10946"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[CLI tool – estimates LLM tokens/costs and runs provider-aware load tests for OpenAI, Anthropic, OpenRouter, or custom endpoints.

A fast, CLI-based tool to estimate token usage and API cost for prompts targeting various LLM providers (OpenAI, Claude, Mistral, etc.). Built in Rust for performance, portability, and safety.]]>
            </summary>
            <updated>2025-11-12T15:39:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10933</id>
            <title type="text"><![CDATA[git-rewrite-commits]]></title>
            <link rel="alternate" href="https://blog.fka.dev/git-rewrite-commits/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10933"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-powered git commit message rewriter using GPT.

Automatically rewrite your entire git commit history with better, conventional commit messages using AI. Perfect for cleaning up messy commit histories before open-sourcing projects or improving repository maintainability.

- [git-rewrite-commits @ GitHub](https://github.com/f/git-rewrite-commits).]]>
            </summary>
            <updated>2025-11-12T08:49:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10920</id>
            <title type="text"><![CDATA[Mocolamma]]></title>
            <link rel="alternate" href="https://mocolamma.taikun.design/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10920"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Ollama Manager App.

Unofficial Ollama manager app for macOS, iOS, iPadOS, and visionOS, featuring server management, model management, and simple chat feature.

- [Mocolamma @ GitHub](https://github.com/taikun114/Mocolamma).

Related contents:

- [MocoLlamma - Ollama gérable depuis iPhone, iPad et Vision Pro @ Korben :fr:](https://korben.info/mocolamma-ollama-gestion-iphone-ia-locale.html).]]>
            </summary>
            <updated>2025-11-12T07:23:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10901</id>
            <title type="text"><![CDATA[qqqa]]></title>
            <link rel="alternate" href="https://github.com/iagooar/qqqa" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10901"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fast, stateless LLM-powered assistant for your shell: qq answers; qa runs commands.

qq means quick question. qa means quick agent. Both are easy to type rapidly on QWERTY keyboards with minimal finger movement. That makes interacting with LLMs faster and more natural during real work.]]>
            </summary>
            <updated>2025-11-07T13:34:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10881</id>
            <title type="text"><![CDATA[Web Codegen Scorer]]></title>
            <link rel="alternate" href="https://github.com/angular/web-codegen-scorer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10881"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Web Codegen Scorer is a tool for evaluating the quality of web code generated by LLMs.]]>
            </summary>
            <updated>2025-11-04T12:51:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10873</id>
            <title type="text"><![CDATA[🎒 Token-Oriented Object Notation (TOON)]]></title>
            <link rel="alternate" href="https://toonformat.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10873"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[JSON for LLM prompts at half the tokens. Spec, benchmarks &amp;amp; TypeScript implementation. 

Token-Oriented Object Notation is a compact, human-readable serialization format designed for passing structured data to Large Language Models with significantly reduced token usage. It&amp;#039;s intended for LLM input, not output.

TOON&amp;#039;s sweet spot is uniform arrays of objects – multiple fields per row, same structure across items. It borrows YAML&amp;#039;s indentation-based structure for nested objects and CSV&amp;#039;s tabular format for uniform data rows, then optimizes both for token efficiency in LLM contexts. For deeply nested or non-uniform data, JSON may be more efficient.

- [🎒 Token-Oriented Object Notation (TOON) @ GitHub](https://github.com/toon-format/toon).

Related contents:

- [Issue \#168: 💪 The overlooked power of URLs @ Changelog News](https://changelog.com/news/168).
- [Which programming languages are most token-efficient? @ Martin Alderson](https://martinalderson.com/posts/which-programming-languages-are-most-token-efficient/).]]>
            </summary>
            <updated>2026-01-26T06:56:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10822</id>
            <title type="text"><![CDATA[EuroLLM :eu:]]></title>
            <link rel="alternate" href="https://eurollm.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10822"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Large language model made in Europe built to support all official 24 EU languages.

The EuroLLM project includes Instituto Superior Técnico, the University of Edinburgh, Instituto de Telecomunicações, Université Paris-Saclay, Unbabel, Sorbonne University, Naver Labs, and the University of Amsterdam. Together they created EuroLLM-9B, a multilingual AI model supporting all 24 official EU languages. Developed with support from Horizon Europe, the European Research Council, and EuroHPC, this open-source LLM aims to enhance Europe’s digital sovereignty and foster AI innovation. Trained on the MareNostrum 5 supercomputer, EuroLLM outperforms similar-sized models. It is fully open source and available via Hugging Face.

Related contents:

- [EuroLLM - Le LLM européen qui tourne sur votre laptop @ Korben :fr:](https://korben.info/eurollm-llm-europeen-local-ollama-laptop.html).]]>
            </summary>
            <updated>2025-11-12T07:32:13+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10812</id>
            <title type="text"><![CDATA[Tavily]]></title>
            <link rel="alternate" href="https://www.tavily.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10812"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Web Access Layer for AI Agents.

Connect Your Agent to the Web. Powering the Internet of Agents with fast, secure and reliable web access APIs.

Related contents:

- [RAG Against The Machine @ Quoi de neuf les devs ? :fr:](https://happytodev.substack.com/p/quoi-de-neuf-les-devs-153-veille?open=false#%C2%A7rag-against-the-machine).]]>
            </summary>
            <updated>2025-10-29T16:23:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10811</id>
            <title type="text"><![CDATA[Dexto]]></title>
            <link rel="alternate" href="https://www.dexto.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10811"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Intelligence Engine. Turn Natural Language Into Action.
 The Intelligence Layer for AI agents. Connect your models, tools, and data to create agentic apps that can think, act and talk to you. 

An all-in-one toolkit to build agentic applications that turn natural language into real-world actions.

Want to build AI-native apps that respond to natural language? Dexto is the intelligence layer that makes it easy to build agentic apps like AI assistants and copilots. Describe your agents, plug in your tools, and watch them respond to plain English.

- [Dexto @ GitHub](https://github.com/truffle-ai/dexto).]]>
            </summary>
            <updated>2025-10-29T12:59:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10810</id>
            <title type="text"><![CDATA[Butter]]></title>
            <link rel="alternate" href="https://www.butter.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10810"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Butter is a cache that identifies patterns in LLM responses and saves you money by serving responses directly.

It&amp;#039;s also deterministic, allowing your AI systems to consistently repeat past behaviors.]]>
            </summary>
            <updated>2025-10-29T12:57:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10751</id>
            <title type="text"><![CDATA[Agentset]]></title>
            <link rel="alternate" href="https://agentset.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10751"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build Frontier RAG Apps.
 The open-source RAG platform: built-in citations, deep research, 22+ file formats, partitions, MCP server, and more. 

Ground AI agents in your knowledge base, minimize hallucinations, and impress out of the box.
Agentset is the open-source platform to build, evaluate, and ship production-ready RAG and agentic applications. It provides end-to-end tooling: ingestion, vector indexing, evaluation/benchmarks, chat playground, hosting, and a clean API with first-class developer experience.

- [Agentset @ GitHub](https://github.com/agentset-ai/agentset).

Related contents:

- [Production RAG: what I learned from processing 5M+ documents @ Abdellatif Abdelfattah](https://blog.abdellatif.io/production-rag-processing-5m-documents).]]>
            </summary>
            <updated>2025-10-21T11:51:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10733</id>
            <title type="text"><![CDATA[SurfSense]]></title>
            <link rel="alternate" href="https://www.surfsense.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10733"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Customizable AI Research &amp;amp; Knowledge Management Assistant.
The AI Workspace Built for Teams.
Connect any LLM to your internal knowledge sources and chat with it in real time alongside your team.



Open Source Alternative to NotebookLM / Perplexity, connected to external sources such as Search Engines, Slack, Linear, Jira, ClickUp, Confluence, Notion, YouTube, GitHub, Discord and more.

- [SurfSense @ GitHub](https://github.com/MODSetter/SurfSense).]]>
            </summary>
            <updated>2025-10-20T12:08:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10697</id>
            <title type="text"><![CDATA[Lance]]></title>
            <link rel="alternate" href="https://lancedb.github.io/lance/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10697"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming.. 

Lance is a modern columnar data format optimized for machine learning and AI applications. It efficiently handles diverse multimodal data types while providing high-performance querying and versioning capabilities.

- [Lance @ GitHub](https://github.com/lancedb/lance).

Related contents:

- [Lance takes aim at Parquet in file format joust @ The Register](https://www.theregister.com/2025/10/14/lance_parquet/).]]>
            </summary>
            <updated>2025-10-17T12:01:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10662</id>
            <title type="text"><![CDATA[NativeMind]]></title>
            <link rel="alternate" href="https://nativemind.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10662"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your AI.Your Data. Zero Cloud.
Offline ChatGPT alternative: open-source, on-device, and 100% private.

By connecting to Ollama local LLMs, NativeMind delivers the latest AI capabilities right inside your favourite browser — without sending a single byte to cloud servers.

- [NativeMind @ GitHub](https://github.com/NativeMindBrowser/NativeMindExtension).

Related contents:

- [Nativemind - IA 100% locale dans votre navigateur web @ Korben :fr:](https://korben.info/nativemind-ia-locale-navigateur-ollama.html).]]>
            </summary>
            <updated>2025-10-15T09:46:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10650</id>
            <title type="text"><![CDATA[nanochat]]></title>
            <link rel="alternate" href="https://github.com/karpathy/nanochat" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10650"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The best ChatGPT that $100 can buy. 

This repo is a full-stack implementation of an LLM like ChatGPT in a single, clean, minimal, hackable, dependency-lite codebase. nanochat is designed to run on a single 8XH100 node via scripts like speedrun.sh, that run the entire pipeline start to end. This includes tokenization, pretraining, finetuning, evaluation, inference, and web serving over a simple UI so that you can talk to your own LLM just like ChatGPT. nanochat will become the capstone project of the course LLM101n being developed by Eureka Labs.

Related contents:

- [Excited to release new repo: nanochat! @ Andrej Karpathy&amp;#039;s Twitter](https://threadreaderapp.com/thread/1977755427569111362.html).]]>
            </summary>
            <updated>2025-10-14T11:40:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10636</id>
            <title type="text"><![CDATA[Anthropic&amp;#039;s Prompt Engineering Interactive Tutorial]]></title>
            <link rel="alternate" href="https://github.com/anthropics/prompt-eng-interactive-tutorial" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10636"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[This course is intended to provide you with a comprehensive step-by-step understanding of how to engineer optimal prompts within Claude.]]>
            </summary>
            <updated>2025-10-13T11:43:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10603</id>
            <title type="text"><![CDATA[AIaC]]></title>
            <link rel="alternate" href="https://github.com/gofireflyio/aiac/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10603"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Artificial Intelligence Infrastructure-as-Code Generator. 

aiac is a library and command line tool to generate IaC (Infrastructure as Code) templates, configurations, utilities, queries and more via LLM providers such as OpenAI, Amazon Bedrock and Ollama.

The CLI allows you to ask a model to generate templates for different scenarios (e.g. &amp;quot;get terraform for AWS EC2&amp;quot;). It composes an appropriate request to the selected provider, and stores the resulting code to a file, and/or prints it to standard output.]]>
            </summary>
            <updated>2025-10-10T09:53:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10602</id>
            <title type="text"><![CDATA[Fabric]]></title>
            <link rel="alternate" href="https://github.com/danielmiessler/fabric" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10602"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fabric is an open-source framework for augmenting humans using AI. It provides a modular system for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.]]>
            </summary>
            <updated>2025-10-10T09:51:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10587</id>
            <title type="text"><![CDATA[Recall 🧠]]></title>
            <link rel="alternate" href="https://github.com/joseairosa/recall?utm_source=tldrwebdev" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10587"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Give Claude perfect recall - Redis-powered persistent memory for LLM.
Give Claude perfect recall with persistent memory that survives context limits and session restarts.

Recall is a brain extension for Claude that stores memories in Redis. 

Your AI assistant can now remember important context, decisions, and patterns across all conversations—no more repeating yourself or losing critical information when the context window fills up.]]>
            </summary>
            <updated>2025-10-09T11:45:13+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10575</id>
            <title type="text"><![CDATA[Nova Framework]]></title>
            <link rel="alternate" href="https://novahunting.ai/#" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10575"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[NOVA: The Prompt Pattern Matching.
NOVA is a Python-based tool for detecting adversarial prompts - prompt injections, exfiltration, evasion and TTPs.

NOVA is an open-source prompt pattern matching system combining keyword detection, semantic similarity, and LLM-based evaluation to analyze and detect prompt content.

- [Nova Framework @ GitHub](https://github.com/fr0gger/nova-framework).

Related contents:

- [Introducing NOVA @ SecurityBreak&amp;#039;s Medium](https://blog.securitybreak.io/introducing-nova-f4244216ae2c).]]>
            </summary>
            <updated>2025-10-08T07:20:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10572</id>
            <title type="text"><![CDATA[ChatKit]]></title>
            <link rel="alternate" href="https://openai.github.io/chatkit-js/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10572"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[ChatKit is a framework for building high-quality, AI-powered chat experiences. It’s designed for developers who want to add advanced conversational intelligence to their apps fast—with minimal setup and no reinventing the wheel. ChatKit delivers a complete, production-ready chat interface out of the box.

- [ChatKit @ GitHub](https://github.com/openai/chatkit-js).]]>
            </summary>
            <updated>2025-10-07T11:50:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10552</id>
            <title type="text"><![CDATA[Jules]]></title>
            <link rel="alternate" href="https://jules.google/docs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10552"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Jules is an experimental coding agent that helps you fix bugs, add documentation, and build new features. It integrates with GitHub, understands your codebase, and works asynchronously — so you can move on while it handles the task.

Related contents:

- [Introducing the Jules API @ Jules documentation](https://jules.google/docs/changelog/).]]>
            </summary>
            <updated>2025-10-06T11:48:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10517</id>
            <title type="text"><![CDATA[Claudesidian]]></title>
            <link rel="alternate" href="https://github.com/heyitsnoah/claudesidian" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10517"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Claude Code + Obsidian Starter Kit.

Turn your Obsidian vault into an AI-powered second brain using Claude Code.

Related contents:

- [The Magic of Claude Code @ Alephic](https://www.alephic.com/writing/the-magic-of-claude-code).]]>
            </summary>
            <updated>2025-10-03T12:22:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10498</id>
            <title type="text"><![CDATA[Symfony AI]]></title>
            <link rel="alternate" href="https://symfony.com/ai" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10498"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Symfony AI is a set of components that integrate AI capabilities into PHP applications.

- [Symfony AI @ GitHub](https://github.com/symfony/ai).

Related contents:

- [Symfony AI : simplifier l’analyse de similarités de textes et l’interaction avec vos LLMs favoris @ JoliCode :fr:](https://jolicode.com/blog/symfony-ai-simplifier-lanalyse-de-similarites-de-textes-et-linteraction-avec-vos-llms-favoris).
- [Créer un serveur MCP avec Symfony sans se casser la tête 😎 @ YoanDev&amp;#039;s YouTube :fr:](https://www.youtube.com/watch?v=D6gu4ZNow_g).]]>
            </summary>
            <updated>2025-10-07T06:26:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10494</id>
            <title type="text"><![CDATA[Telex]]></title>
            <link rel="alternate" href="https://telex.automattic.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10494"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-Assisted Authoring Environment for WordPress Blocks.

Related contents:

- [\#119: Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC2 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-sept25-rc2/).]]>
            </summary>
            <updated>2025-10-02T09:12:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10493</id>
            <title type="text"><![CDATA[AI SDK]]></title>
            <link rel="alternate" href="https://ai-sdk.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10493"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The AI Toolkit for TypeScript.

From the creators of Next.js, the AI SDK is a free open-source library that gives you the tools you need to build AI-powered products.

- [AI SDK @ GitHub](https://github.com/vercel/ai).

Related contents:

- [\#119: Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC2 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-sept25-rc2/).]]>
            </summary>
            <updated>2025-10-02T06:01:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10489</id>
            <title type="text"><![CDATA[Laravel Boost]]></title>
            <link rel="alternate" href="https://boost.laravel.com/installed" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10489"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Laravel Boost accelerates AI-assisted development by providing the essential context and structure that AI needs to generate high-quality, Laravel-specific code.

- [Laravel Boost @ GitHub](https://github.com/laravel/boost).

Related contents:

- [Getting Started with Laravel Boost @ Laravel&amp;#039;s YouTube](https://www.youtube.com/watch?v=sUtRcpma8iU).
- [\#118 - Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC1 @ Double Slash :fr:](https://double-slash.dev/podcasts/sept25-rc1/).]]>
            </summary>
            <updated>2025-10-02T05:47:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10476</id>
            <title type="text"><![CDATA[Typebot]]></title>
            <link rel="alternate" href="https://typebot.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10476"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[💬 Typebot is a powerful chatbot builder that you can self-host. 

Hack the bot game: Build faster, Chat smarter.

Typebot is a no-code platform that enables you to effortlessly create and integrate advanced chatbots into websites and chat platforms like WhatsApp.

- [Typebot @ GitHub](https://github.com/baptisteArno/typebot.io).]]>
            </summary>
            <updated>2025-10-01T06:07:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10401</id>
            <title type="text"><![CDATA[shimmy]]></title>
            <link rel="alternate" href="https://github.com/Michael-A-Kuykendall/shimmy" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10401"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Privacy-First Alternative to Ollama.

 ⚡ Python-free Rust inference server — OpenAI-API compatible. GGUF + SafeTensors, hot model swap, auto-discovery, single binary. FREE now, FREE forever. 

Shimmy is a 5.1MB single-binary that provides 100% OpenAI-compatible endpoints for GGUF models. Point your existing AI tools to Shimmy and they just work — locally, privately, and free.]]>
            </summary>
            <updated>2025-09-26T12:18:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10361</id>
            <title type="text"><![CDATA[Prism]]></title>
            <link rel="alternate" href="https://prismphp.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10361"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prism is a powerful Laravel package for integrating Large Language Models (LLMs) into your applications.

- [Prism @ GitHub](https://github.com/prism-php/prism)
- [Prism Relay @ GitHub](https://github.com/prism-php/relay).

Related contents:

- [Prism &amp;amp; AI | TJ Miller at Laracon US 2025 @ Laravel&amp;#039;s YouTube](https://www.youtube.com/watch?v=TsEeIjWrPhI).
- [Prism, le SDK agentique pour Laravel @ Laravel France :fr:](https://laravel-france.com/posts/prism-le-sdk-agentique-pour-laravel).
- [\#118 - Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC1 @ Double Slash :fr:](https://double-slash.dev/podcasts/sept25-rc1/).]]>
            </summary>
            <updated>2025-10-02T05:52:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10327</id>
            <title type="text"><![CDATA[DetectPack Forge]]></title>
            <link rel="alternate" href="https://detect-pack-forge.vercel.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10327"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn ideas into detections your SIEM understands. Generate Sigma, KQL, and SPL rules with tests and playbooks in seconds.

 DetectPack Forge turns plain-English behaviors or sample logs into production-ready detection packs — Sigma, KQL (Sentinel), SPL (Splunk) — plus tests and a response playbook, mapped to MITRE ATT&amp;amp;CK, fully powered by Gen AI. 

- [DetectPack Forge @ GitHub](https://github.com/andrewkolagit/DetectPack-Forge).]]>
            </summary>
            <updated>2025-09-22T05:28:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10303</id>
            <title type="text"><![CDATA[Codebuff]]></title>
            <link rel="alternate" href="https://www.codebuff.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10303"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Generate code from the terminal! 
Supercharge Your AI Coding.
Simple. Fast. Powerful. Codebuff works in your terminal.

Codebuff is an open-source AI coding assistant that edits your codebase through natural language instructions. Instead of using one model for everything, it coordinates specialized agents that work together to understand your project and make precise changes.

- [Codebuff @ GitHub](https://github.com/CodebuffAI/codebuff).]]>
            </summary>
            <updated>2025-09-19T11:49:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10302</id>
            <title type="text"><![CDATA[9P]]></title>
            <link rel="alternate" href="http://9p.cat-v.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10302"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A sane distributed file system.

9P is a network protocol developed at Bell Labs for the Plan 9 from Bell Labs distributed operating system as the means of accessing and manipulating resources and applications transparently in a distributed environment. 9P works both as a distributed file system and as a network transparent and language agnostic ‘API’.]]>
            </summary>
            <updated>2025-09-19T11:43:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10301</id>
            <title type="text"><![CDATA[ZeroFS]]></title>
            <link rel="alternate" href="https://github.com/Barre/ZeroFS" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10301"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Filesystem That Makes S3 your Primary Storage. ZeroFS is 9P/NFS/NBD on top of S3. 

ZeroFS makes S3 storage feel like a real filesystem. It provides file-level access via NFS and 9P and block-level access via NBD. Fast enough to compile code on, with clients already built into your OS. No FUSE drivers, no kernel modules, just mount and go.]]>
            </summary>
            <updated>2025-09-19T11:42:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10293</id>
            <title type="text"><![CDATA[Terragon]]></title>
            <link rel="alternate" href="https://www.terragonlabs.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10293"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Background Agents for Claude Code.

Terragon is a developer platform that lets you run AI coding agents in the cloud. Whether you&amp;#039;re at your browser, in your terminal, or on your phone, Terragon works wherever you are. Offload coding tasks and come back to pull requests ready to review.]]>
            </summary>
            <updated>2025-09-19T06:06:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10291</id>
            <title type="text"><![CDATA[LLM Visualization]]></title>
            <link rel="alternate" href="https://bbycroft.net/llm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10291"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A visualization and walkthrough of the LLM algorithm that backs OpenAI&amp;#039;s ChatGPT. Explore the algorithm down to every add &amp;amp; multiply, seeing the whole process in action.

This project displays a 3D model of a working implementation of a GPT-style network. That is, the network topology that&amp;#039;s used in OpenAI&amp;#039;s GPT-2, GPT-3, (and maybe GPT-4).

- [LLM Visualization @ GitHub](https://github.com/bbycroft/llm-viz).]]>
            </summary>
            <updated>2025-09-19T06:03:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10290</id>
            <title type="text"><![CDATA[repomirror]]></title>
            <link rel="alternate" href="https://github.com/repomirrorhq/repomirror" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10290"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A tool to perform transformations on code repositories with AI. 

Related contents:

- [We Put a Coding Agent in a While Loop and It Shipped 6 Repos Overnight @ repomirror&amp;#039;s GitHub](https://github.com/repomirrorhq/repomirror/blob/main/repomirror.md).]]>
            </summary>
            <updated>2025-09-19T06:01:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10288</id>
            <title type="text"><![CDATA[System Prompts Leaks]]></title>
            <link rel="alternate" href="https://github.com/asgeirtj/system_prompts_leaks" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10288"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Collection of extracted System Prompts from popular chatbots like ChatGPT, Claude &amp;amp; Gemini]]>
            </summary>
            <updated>2025-09-19T05:56:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10277</id>
            <title type="text"><![CDATA[Noton]]></title>
            <link rel="alternate" href="https://github.com/bartvantuijn/noton" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10277"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A free and open documentation platform built with Laravel and Filament, enhanced by Ollama for local AI features, focused on clarity, structure, and self-hosted simplicity.]]>
            </summary>
            <updated>2025-09-18T14:26:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10274</id>
            <title type="text"><![CDATA[AgentScope]]></title>
            <link rel="alternate" href="https://agentscope.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10274"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Agent-Oriented Programming for Building LLM Applications.

- [AgentScope’s documentation](https://doc.agentscope.io/).
- [AgentScope @ GitHub](https://github.com/agentscope-ai/agentscope).]]>
            </summary>
            <updated>2025-09-18T13:51:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10271</id>
            <title type="text"><![CDATA[MCP Registry]]></title>
            <link rel="alternate" href="https://github.com/mcp" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10271"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Servers and tools from the community that connect models to files, APIs, databases, and more.

Related contents:

- [Meet the GitHub MCP Registry: The fastest way to discover MCP Servers @ GitHub Blog](https://github.blog/ai-and-ml/github-copilot/meet-the-github-mcp-registry-the-fastest-way-to-discover-mcp-servers/).
- [How to find, install, and manage MCP servers with the GitHub MCP Registry @ GitHub Blog](https://github.blog/ai-and-ml/generative-ai/how-to-find-install-and-manage-mcp-servers-with-the-github-mcp-registry/).]]>
            </summary>
            <updated>2025-10-29T13:12:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10262</id>
            <title type="text"><![CDATA[GSO]]></title>
            <link rel="alternate" href="https://gso-bench.github.io/index.html" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10262"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Challenging Software Optimization Tasks for Evaluating SWE-Agents.

A benchmark for evaluating language models&amp;#039; capabilities in developing high-performance software.

GSO (Global Software Optimization) is a benchmark for evaluating language models&amp;#039; capabilities in developing high-performance software. We present 100+ challenging optimization tasks across 10 codebases spanning diverse domains and programming languages. Each task provides a codebase and performance test as a precise specification, with agents required to optmize the codebase and measured against expert developer commits.

- [GSO @ GitHub](https://github.com/gso-bench/gso).]]>
            </summary>
            <updated>2025-09-18T06:03:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10260</id>
            <title type="text"><![CDATA[GEPA]]></title>
            <link rel="alternate" href="https://github.com/gepa-ai/gepa" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10260"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[System Optimization through Reflective Text Evolution.
Optimize prompts, code, and more with AI-powered Reflective Text Evolution.

GEPA (Genetic-Pareto) is a framework for optimizing arbitrary systems composed of text components—like AI prompts, code snippets, or textual specs—against any evaluation metric. It employs LLMs to reflect on system behavior, using feedback from execution and evaluation traces to drive targeted improvements. Through iterative mutation, reflection, and Pareto-aware candidate selection, GEPA evolves robust, high-performing variants with minimal evaluations, co-evolving multiple components in modular systems for domain-specific gains.

Related contents:

- [Building and Optimizing Multi-Agent RAG Systems with DSPy and GEPA @ Isaac Kargar&amp;#039;s Medium](https://kargarisaac.medium.com/building-and-optimizing-multi-agent-rag-systems-with-dspy-and-gepa-2b88b5838ce2).]]>
            </summary>
            <updated>2025-09-18T05:59:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10259</id>
            <title type="text"><![CDATA[DSPy (Declarative Self-improving Python)]]></title>
            <link rel="alternate" href="https://dspy.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10259"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The framework for programming—not prompting—language models 

DSPy is a declarative framework for building modular AI software. It allows you to iterate fast on structured code, rather than brittle strings, and offers algorithms that compile AI programs into effective prompts and weights for your language models, whether you&amp;#039;re building simple classifiers, sophisticated RAG pipelines, or Agent loops.

- [DSPy @ GitHub](https://github.com/stanfordnlp/dspy).

Related contents:

- [Building and Optimizing Multi-Agent RAG Systems with DSPy and GEPA @ Isaac Kargar&amp;#039;s Medium](https://kargarisaac.medium.com/building-and-optimizing-multi-agent-rag-systems-with-dspy-and-gepa-2b88b5838ce2).]]>
            </summary>
            <updated>2025-09-18T05:57:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10253</id>
            <title type="text"><![CDATA[AutoGen]]></title>
            <link rel="alternate" href="https://microsoft.github.io/autogen/stable/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10253"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A framework for building AI agents and applications.

AutoGen is a framework for creating multi-agent AI applications that can act autonomously or work alongside humans.

- [AutoGen @ GitHub](https://github.com/microsoft/autogen).

Related contents:

- [Don’t Build Multi-Agents @ Cognition](https://cognition.ai/blog/dont-build-multi-agents#principles-of-context-engineering).]]>
            </summary>
            <updated>2025-09-17T14:32:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10252</id>
            <title type="text"><![CDATA[Malloy]]></title>
            <link rel="alternate" href="https://www.malloydata.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10252"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A modern open source language for analyzing,
transforming, and modeling data.

Malloy is a modern open source language for describing data relationships and transformations. It is both a semantic modeling language and a query language that uses an existing SQL engine to execute queries. Malloy currently can connect to BigQuery, Snowflake, PostgreSQL, MySQL, Trino, or Presto, and natively supports DuckDB. We&amp;#039;ve built a Visual Studio Code extension to facilitate building Malloy data models, querying and transforming data, and creating simple visualizations and dashboards.

- [Malloy @ GitHub](https://github.com/malloydata/malloy).

Related contents:

- [Lessons on building an AI data analyst @ Pedro Nascimento](https://www.pedronasc.com/articles/lessons-building-ai-data-analyst).]]>
            </summary>
            <updated>2025-09-17T14:29:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10251</id>
            <title type="text"><![CDATA[The /llms.txt file]]></title>
            <link rel="alternate" href="https://llmstxt.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10251"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A proposal to standardise on using an /llms.txt file to provide information to help LLMs use a website at inference time.

We propose adding a /llms.txt markdown file to websites to provide LLM-friendly content. This file offers brief background information, guidance, and links to detailed markdown files.

llms.txt markdown is human and LLM readable, but is also in a precise format allowing fixed processing methods (i.e. classical programming techniques such as parsers and regex).

- [llms.txt @ GitHub](https://github.com/answerdotai/llms-txt).
- [MCP LLMS-TXT Documentation Server @ GitHub](https://github.com/langchain-ai/mcpdoc).

Related contents:

- [Firecrawl LLMs.txt Generator @ GitHub](https://github.com/firecrawl/create-llmstxt-py).
- [A proposal for inline LLM instructions in HTML based on llms.txt @ Vercel](https://vercel.com/blog/a-proposal-for-inline-llm-instructions-in-html).
- [\#119: Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC2 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-sept25-rc2/).
- [A fun trick for getting discovered by LLMs and AI tools @ Cassidy Williams](https://cassidoo.co/post/ai-llm-discoverability/).]]>
            </summary>
            <updated>2026-02-02T10:24:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10248</id>
            <title type="text"><![CDATA[Genkit]]></title>
            <link rel="alternate" href="https://genkit.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10248"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open-source framework for building AI-powered apps, built and used in production by Google

Open-source framework for building AI-powered apps in JavaScript, Go, and Python, built and used in production by Google 

It offers a unified interface for integrating AI models from providers like Google, OpenAI, Anthropic, Ollama, and more. Rapidly build and deploy production-ready chatbots, automations, and recommendation systems using streamlined APIs for multimodal content, structured outputs, tool calling, and agentic workflows.

- [Genkit @ GitHub](https://github.com/firebase/genkit).

Related contents:

- [Announcing Genkit Go 1.0 and Enhanced AI-Assisted Development @ Google for Developers](https://developers.googleblog.com/en/announcing-genkit-go-10-and-enhanced-ai-assisted-development/).]]>
            </summary>
            <updated>2025-09-17T11:38:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10245</id>
            <title type="text"><![CDATA[Chronon]]></title>
            <link rel="alternate" href="https://github.com/airbnb/chronon" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10245"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chronon is a data platform for serving for AI/ML applications. 

Chronon is a platform that abstracts away the complexity of data computation and serving for AI/ML applications. Users define features as transformation of raw data, then Chronon can perform batch and streaming computation, scalable backfills, low-latency serving, guaranteed correctness and consistency, as well as a host of observability and monitoring tools.

It allows you to utilize all of the data within your organization, from batch tables, event streams or services to power your AI/ML projects, without needing to worry about all the complex orchestration that this would usually entail.]]>
            </summary>
            <updated>2025-09-17T11:19:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10238</id>
            <title type="text"><![CDATA[Semlib]]></title>
            <link rel="alternate" href="https://semlib.anish.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10238"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Semantic Data Processing.
Build data processing and data analysis pipelines that leverage the power of LLMs 🧠 

Semlib is a Python library for building data processing and data analysis pipelines that leverage the power of large language models (LLMs). Semlib provides, as building blocks, familiar functional programming primitives like map, reduce, sort, and filter, but with a twist: Semlib&amp;#039;s implementation of these operations are programmed with natural language descriptions rather than code. Under the hood, Semlib handles complexities such as prompting, parsing, concurrency control, caching, and cost tracking.

- [Semlib @ GitHub](https://github.com/anishathalye/semlib).]]>
            </summary>
            <updated>2025-09-16T12:17:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10217</id>
            <title type="text"><![CDATA[mdream]]></title>
            <link rel="alternate" href="https://github.com/harlan-zw/mdream" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10217"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[☁️ Convert any site to clean markdown &amp;amp; llms.txt. Boost your site&amp;#039;s AI discoverability or generate LLM context for a project you&amp;#039;re working with. 

Mdream core is a highly optimized primitive for producing Markdown from HTML that is optimized for LLMs.]]>
            </summary>
            <updated>2025-09-15T14:08:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10180</id>
            <title type="text"><![CDATA[Chat GipiTTY]]></title>
            <link rel="alternate" href="https://divanv.com/chat-gipitty/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10180"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chat Gipitty (Chat Get Information, Print Information TTY) is a command line client primarily intended for the official OpenAI Chat Completions API. It allows you to chat with language models in a terminal and even pipe output into it. While optimized for OpenAI&amp;#039;s ChatGPT (with GPT-4 as the default model), it can also work with other providers that expose OpenAI-compatible endpoints.

- [Chat GipiTTY @ GitHub](https://github.com/divanvisagie/chat-gipitty).

Related contents:

- [Episode 610: Linus&amp;#039; Next Big Thing @ Linux Unplugged](https://linuxunplugged.com/610).]]>
            </summary>
            <updated>2025-09-14T16:51:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10179</id>
            <title type="text"><![CDATA[LobeChat]]></title>
            <link rel="alternate" href="https://lobechat.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10179"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your personal AI productivity tool for a smarter brain.

 🤯 Lobe Chat - an open-source, modern design AI chat framework. Supports multiple AI providers (OpenAI / Claude 4 / Gemini / DeepSeek / Ollama / Qwen), Knowledge Base (file upload / RAG ), one click install MCP Marketplace and Artifacts / Thinking. One-click FREE deployment of your private AI Agent application. 

- [LobeChat @ GitHub](https://github.com/lobehub/lobe-chat).

Related contents:

- [Episode 586: Kexec with Determination @ Linux Unplugged](https://linuxunplugged.com/586).]]>
            </summary>
            <updated>2026-04-09T06:11:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10164</id>
            <title type="text"><![CDATA[Serena]]></title>
            <link rel="alternate" href="https://github.com/oraios/serena" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10164"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A powerful coding agent toolkit providing semantic retrieval and editing capabilities (MCP server &amp;amp; other integrations).

🚀 Serena is a powerful coding agent toolkit capable of turning an LLM into a fully-featured agent that works directly on your codebase. Unlike most other tools, it is not tied to an LLM, framework or an interface, making it easy to use it in a variety of ways.

Related contents:

- [Accelerate developer productivity with these 9 open source AI and MCP projects @ GitHub blog](https://github.blog/open-source/accelerate-developer-productivity-with-these-9-open-source-ai-and-mcp-projects/).]]>
            </summary>
            <updated>2025-10-27T14:07:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10146</id>
            <title type="text"><![CDATA[Dosu |]]></title>
            <link rel="alternate" href="https://dosu.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10146"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your best engineers shouldn&amp;#039;t Q&amp;amp;A all day.
 
Dosu is an AI-powered Github maintainer agent. Dosu helps open source maintainers encourage contributors, organize issues, triage bugs, answer questions, and more.

Dosu turns your codebase into a living knowledge base that every team member can understand—from engineering to operations—so builders can build.

Related contents:

- [How TriliumNext Revitalized an Abandoned Open Source Project with Dosu&amp;#039;s Help @ Dosu blog](https://dosu.dev/blog/how-triliumnext-revitalized-an-abandoned-open-source-project-with-dosus-help).]]>
            </summary>
            <updated>2025-09-12T07:08:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10135</id>
            <title type="text"><![CDATA[Apertus: Public AI inference utility :ch:]]></title>
            <link rel="alternate" href="https://publicai.co/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10135"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[EPFL, ETH Zurich, and the Swiss National Supercomputing Centre (CSCS) has released Apertus, Switzerland’s first large-scale open, multilingual language model — a milestone in generative AI for transparency and diversity. Trained on 15 trillion tokens across more than 1,000 languages – 40% of the data is non-English – Apertus includes many languages that have so far been underrepresented in LLMs, such as Swiss German, Romansh, and many others. Apertus serves as a building block for developers and organizations for future applications such as chatbots, translation systems, or educational tools. 

- [Apertus LLM @ Hugging Face](https://huggingface.co/collections/swiss-ai/apertus-llm-68b699e65415c231ace3b059).
- [Apertus v1 Technical Report @ GitHub](https://github.com/swiss-ai/apertus-tech-report/).
- [Apertus @ Swiss AI](https://www.swiss-ai.org/apertus).

Related contents:

- [S12E01 : 9 septembre 2025 @ Les Technos :fr:](https://lestechnos.be/s12e01-9-septembre-2025/).
- [\#119: Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC2 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-sept25-rc2/).]]>
            </summary>
            <updated>2025-10-02T06:10:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10125</id>
            <title type="text"><![CDATA[Qwen Code :cn:]]></title>
            <link rel="alternate" href="https://qwenlm.github.io/qwen-code-docs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10125"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Qwen Code is a coding agent that lives in the digital world. 

Qwen Code brings the capabilities of advanced code models to your terminal in an interactive Read-Eval-Print Loop (REPL) environment. Qwen Code consists of a client-side application (packages/cli) that communicates with a local server (packages/core). Qwen Code also contains a variety of tools for tasks such as performing file system operations, running shells, and web fetching, which are managed by packages/core.

- [Qwen Code @ GitHub](https://github.com/QwenLM/qwen-code).

Related contents:

- [Qwen3-Coder: Is this Agentic CLI smarter than senior devs? @ LogRocket](https://blog.logrocket.com/qwen-3-coder-agentic-cli).
- [\#126 - 🤖 News Janvier 2026 : Open Code, Qwen Code et un peu de code @ Double Slash :fr:](https://double-slash.dev/podcasts/news-jan26/).]]>
            </summary>
            <updated>2026-02-20T07:18:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10124</id>
            <title type="text"><![CDATA[Paddler]]></title>
            <link rel="alternate" href="https://paddler.intentee.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10124"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source LLMOps platform for hosting and scaling AI in your own infrastructure 🏓🦙 
 Paddler is an open-source LLMOps platform that lets teams run inference and deploy LLMs on their own infrastructure. 

- [Paddler @ GitHub](https://github.com/intentee/paddler).]]>
            </summary>
            <updated>2025-09-11T10:33:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10094</id>
            <title type="text"><![CDATA[PyTorch]]></title>
            <link rel="alternate" href="https://pytorch.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10094"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Tensors and Dynamic neural networks in Python with strong GPU acceleration.

PyTorch is a Python package that provides two high-level features:

- Tensor computation (like NumPy) with strong GPU acceleration
- Deep neural networks built on a tape-based autograd system

You can reuse your favorite Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.

- [PyTorch @ GitHub](https://github.com/pytorch/pytorch).

Related contents:

- [Intro to PyTorch. Easy to follow, visual introduction. @ 0byte.io](https://0byte.io/articles/pytorch_introduction.html).
- [Faire tourner un LLM localement sur votre ordinateur @ Quoi de neuf les devs ? :fr:](https://happytodev.substack.com/p/brent-roose-est-linvite-du-n147-de?open=false#%C2%A7faire-tourner-un-llm-localement-sur-votre-ordinateur).
- [the bug that taught me more about PyTorch than years of using it  @ matmols](https://elanapearl.github.io/blog/2025/the-bug-that-taught-me-pytorch/).
- [The annotated PyTorch training loop @ idlemachines](https://idlemachines.co.uk/essays/pytorch-training-loop).]]>
            </summary>
            <updated>2026-06-26T11:36:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10090</id>
            <title type="text"><![CDATA[LiteLLM]]></title>
            <link rel="alternate" href="https://docs.litellm.ai/docs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10090"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Call all LLM APIs using the OpenAI format [Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, Groq etc.] 

Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq] 

- [LiteLLM @ GitHub](https://github.com/BerriAI/litellm).

Related contents:

- [Guide LiteLLM : Interface unifiée pour 100+ modèles IA @ DevSecOps :fr:](https://blog.stephane-robert.info/docs/developper/programmation/python/litellm/).
- [Prise en main de LiteLLM Proxy Server @ DevSecOps :fr:](https://blog.stephane-robert.info/docs/developper/programmation/python/litellm-proxy-server/).
- [Monitor your LiteLLM AI proxy with Datadog @ Datadog](https://www.datadoghq.com/blog/monitor-litellm-with-datadog/).]]>
            </summary>
            <updated>2025-09-17T11:30:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10060</id>
            <title type="text"><![CDATA[kubewall]]></title>
            <link rel="alternate" href="https://github.com/kubewall/kubewall" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10060"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Single-Binary Kubernetes Dashboard with Multi-Cluster Management &amp;amp; AI Integration. (OpenAI / Claude 4 / Gemini / DeepSeek / OpenRouter / Ollama / Qwen / LMStudio).

It provides a simple and rich realtime interface to manage and investigate your clusters.

Related contents:

- [Newsletter du 02 Février 2026 @ RudeOps :fr:](https://www.rudeops.com/newsletter/2026-02-02-rudeops-newsletter/).]]>
            </summary>
            <updated>2026-02-12T07:30:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10038</id>
            <title type="text"><![CDATA[BruteForceAI]]></title>
            <link rel="alternate" href="https://github.com/MorDavid/BruteForceAI" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10038"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Advanced LLM-powered brute-force tool combining AI intelligence with automated login attacks.

Related contents:

- [BruteForceAI - L&amp;#039;IA qui cracke vos mots de passe @ Korben :fr:](https://korben.info/bruteforceai.html).
- [BruteForceAI: Free AI-powered login brute force tool @ Help Net Security](https://www.helpnetsecurity.com/2025/09/03/bruteforceai-free-ai-powered-login-brute-force-tool/).]]>
            </summary>
            <updated>2025-09-08T10:03:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10016</id>
            <title type="text"><![CDATA[Parlant]]></title>
            <link rel="alternate" href="https://www.parlant.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10016"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build compliant AI chat agents, in minutes.
 LLM agents built for control. Designed for real-world use. Deployed in minutes. 

Parlant gives you all the structure you need to build customer-facing agents that behave exactly as your business requires

- [Parlant @ GitHub](https://github.com/emcie-co/parlant).]]>
            </summary>
            <updated>2025-09-04T17:08:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10013</id>
            <title type="text"><![CDATA[ort]]></title>
            <link rel="alternate" href="https://github.com/grahamking/ort" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10013"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An honest CLI for openrouter.ai. Fast and tmux-aware.
ort sends your prompts to AI models on openrouter.ai.

It is built the old fashioned way, in solid Rust. It doesn&amp;#039;t slow you down with Python interpreters. This is a modest 2 MiB ELF binary.

Related contents:

- [Evaluating LLMs for my personal use case @ Graham King](https://darkcoding.net/software/personal-ai-evals-aug-2025/).]]>
            </summary>
            <updated>2025-09-04T16:53:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10002</id>
            <title type="text"><![CDATA[🤗 Hub client library]]></title>
            <link rel="alternate" href="https://huggingface.co/docs/huggingface_hub/index" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10002"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The huggingface_hub library allows you to interact with the Hugging Face Hub, a machine learning platform for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the hundreds of machine learning apps hosted on the Hub. You can also create and share your own models and datasets with the community. The huggingface_hub library provides a simple way to do all these things with Python.

- [🤗 Python client for the Huggingface Hub @ GitHub](https://github.com/huggingface/huggingface_hub).
- [Hugging Face JS libraries @ GitHub](https://github.com/huggingface/huggingface.js).

Related contents:

- [Tiny Agents in Python: an MCP-powered agent in ~70 lines of code @ Hugging Face](https://huggingface.co/blog/python-tiny-agents).
- [Tiny Agents: an MCP-powered agent in 50 lines of code @ Hugging Face](https://huggingface.co/blog/tiny-agents).]]>
            </summary>
            <updated>2025-09-04T11:53:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/9998</id>
            <title type="text"><![CDATA[rendergit]]></title>
            <link rel="alternate" href="https://github.com/karpathy/rendergit" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/9998"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Render any git repo into a single static HTML page for humans or LLMs.

Tired of clicking around complex file hierarchies of GitHub repos? Do you just want to see all of the code on a single page? Enter rendergit. Flatten any GitHub repository into a single, static HTML page with syntax highlighting, markdown rendering, and a clean sidebar navigation. Perfect for code review, exploration, and an instant Ctrl+F experience.]]>
            </summary>
            <updated>2025-09-04T09:43:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1</id>
            <title type="text"><![CDATA[Sim]]></title>
            <link rel="alternate" href="https://www.sim.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build / Deploy Agent Workflows.

Launch agentic workflows with an open source, user-friendly environment for devs and agents.

 Sim is an open-source AI agent workflow builder. Sim Studio&amp;#039;s interface is a lightweight, intuitive way to quickly build and deploy LLMs that connect with your favorite tools. 

- [Sim @ GitHub](https://github.com/simstudioai/sim).

Related contents:

- [Sim Studio - Créez vos workflows d&amp;#039;agents IA aussi facilement que quand vous dessinez sur Figma @ Korben :fr:](https://korben.info/sim-studio-workflows-agents-ia-open-source.html).]]>
            </summary>
            <updated>2025-12-16T10:25:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7</id>
            <title type="text"><![CDATA[AGENTS.md]]></title>
            <link rel="alternate" href="https://agents.md/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A simple, open format for guiding coding agents,
used by over 20k open-source projects.

Think of AGENTS.md as a README for agents: a dedicated, predictable place to provide the context and instructions to help AI coding agents work on your project.

- [AGENTS.md @ GitHub](https://github.com/openai/agents.md).

Related contents:

- [Improve your AI code output with AGENTS.md (+ my best tips) @ builder.io](https://www.builder.io/blog/agents-md).
- [\#118 - Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC1 @ Double Slash :fr:](https://double-slash.dev/podcasts/sept25-rc1/).
- [Optimizing repos for AI @ Tom Bedor&amp;#039;s Blog](https://tombedor.dev/optimizing-repos-for-ai/).
- [How to write a great agents.md: Lessons from over 2,500 repositories @ GitHub Blog](https://github.blog/ai-and-ml/github-copilot/how-to-write-a-great-agents-md-lessons-from-over-2500-repositories/).
- [Writing a good CLAUDE.md @ humanlayer](https://www.humanlayer.dev/blog/writing-a-good-claude-md).
- [Streamlining my user-level CLAUDE.md @ chris dzombak](https://www.dzombak.com/blog/2025/12/streamlining-my-user-level-claude-md/).
- [The Complete Guide to CLAUDE.md @ builder.io](https://www.builder.io/blog/claude-md-guide).
- [How to build self-improving coding agents - Part 1 @ Eric J Ma&amp;#039;s Website](https://ericmjl.github.io/blog/2026/1/17/how-to-build-self-improving-coding-agents-part-1/).
- [AGENTS.md outperforms skills in our agent evals @ Vercel](https://vercel.com/blog/agents-md-outperforms-skills-in-our-agent-evals).
- [Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents? @ arXiv](https://arxiv.org/abs/2602.11988).
- [Knowledge Priming @ martinFowler.com](https://martinfowler.com/articles/reduce-friction-ai/knowledge-priming.html).
- [J&amp;#039;ai mis deux IA en code review l&amp;#039;une contre l&amp;#039;autre — voici ce que ça donne @ Maxence Maireaux :fr:](https://maxence.maireaux.fr/fr/blog/mon-workflow-ia-claude-code-codex/).
- [Filesystems are having a moment @ madalitso.me](https://madalitso.me/notes/why-everyone-is-talking-about-filesystems/).
- [Your Docs Directory Is Doomed @ Jim Yagmin&amp;#039;s Blog](https://yagmin.com/blog/your-docs-directory-is-doomed/).
- [Stop Wasting Hours Writing Unit Tests: Use GitHub Copilot to Explode Code Coverage Fast @ Build5Nines](https://build5nines.com/stop-wasting-hours-writing-unit-tests-use-github-copilot-to-explode-code-coverage-fast/).]]>
            </summary>
            <updated>2026-06-04T07:03:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/8</id>
            <title type="text"><![CDATA[opcode]]></title>
            <link rel="alternate" href="https://opcode.sh/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/8"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Elegant Desktop Companion for Claude Code.

A powerful GUI app and Toolkit for Claude Code - Create custom agents, manage interactive Claude Code sessions, run secure background agents, and more. 

- [opcode @ GitHub](https://github.com/getAsterisk/opcode).

Related contents:

- [Opcode transforme Claude Code en machine de guerre @ Korben :fr:](https://korben.info/opcode-gui-claude-code-asterisk.html).]]>
            </summary>
            <updated>2025-11-20T12:12:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12</id>
            <title type="text"><![CDATA[Newelle]]></title>
            <link rel="alternate" href="https://newelle.qsk.me/#home" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Ultimate Virtual Assistant.

Experience the future of AI assistance with advanced customization, flexible model support, and seamless integration. Newelle brings you the power of AI with unmatched flexibility and control.

- [Newelle @ GitHub](https://github.com/qwersyk/Newelle).

Related contents:

- [Un agent IA débarque sur Linux ? @ Choses à Savoir TECH :fr:](https://shows.acast.com/choses-a-savoir-technologie/episodes/un-agent-ia-debarque-sur-linux).]]>
            </summary>
            <updated>2026-06-30T00:01:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/15</id>
            <title type="text"><![CDATA[Agentic Workflows]]></title>
            <link rel="alternate" href="https://githubnext.com/projects/agentic-workflows/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/15"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Towards Natural‑Language Programming for GitHub Action.

Write agentic workflows in natural language markdown, and run them in GitHub Actions. 

- [Agentic Workflows @ GitHub](https://github.com/githubnext/gh-aw?utm_source=tldrdevops).]]>
            </summary>
            <updated>2025-09-04T07:26:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/18</id>
            <title type="text"><![CDATA[Epicenter]]></title>
            <link rel="alternate" href="https://epicenter.so/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/18"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Database for Your Mind.

One shared context across all your apps. Your transcripts inform your notes. Your notes guide your AI. Everything connects through a single folder of plain text and SQLite. 

Epicenter is an ecosystem of open-source, local-first apps. Our eventual goal is to store all of your data—notes, transcripts, chat histories—in a single folder of plain text and SQLite. Every tool we build shares this memory. It&amp;#039;s open, tweakable, and yours. Grep it, open it in Obsidian, host it wherever you like. The choice is yours.

- [Epicenter @ GitHub](https://github.com/epicenter-so/epicenter?utm_source=tldrwebdev).]]>
            </summary>
            <updated>2026-01-18T12:01:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/26</id>
            <title type="text"><![CDATA[Bytebot]]></title>
            <link rel="alternate" href="https://www.bytebot.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/26"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Easiest Way to Build Desktop Agents.
Bytebot is a turn-key container for developers building desktop agents.

 Bytebot is a self-hosted AI desktop agent that automates computer tasks through natural language commands, operating within a containerized Linux desktop environment. 

- [Bytebot @ GitHub](https://github.com/bytebot-ai/bytebot).

Related contents:

- [ByteBot - L&amp;#039;agent IA qui prend le contrôle de votre ordi (mais dans Docker, faut pas déconner) @ Korben :fr:](https://korben.info/bytebot-agent-prend-controle-votre-ordinateur.html).]]>
            </summary>
            <updated>2025-09-08T11:30:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/32</id>
            <title type="text"><![CDATA[RamaLama]]></title>
            <link rel="alternate" href="https://ramalama.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/32"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[RamaLama strives to make working with AI simple, straightforward, and familiar by using OCI containers. 

RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of containers. 

- [RamaLama @ GitHub](https://github.com/containers/ramalama).

Related contents:

- [Episode 616: From Boston to bootc @ Linux Unplugged](https://linuxunplugged.com/616).]]>
            </summary>
            <updated>2025-09-04T08:32:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/42</id>
            <title type="text"><![CDATA[llm-d]]></title>
            <link rel="alternate" href="https://llm-d.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/42"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[a Kubernetes-native high-performance distributed LLM inference framework.

llm-d is a Kubernetes-native distributed inference serving stack, providing well-lit paths for anyone to serve large generative AI models at scale, with the fastest time-to-value and competitive performance per dollar for most models across most hardware accelerators.

- [llm-d @ GitHub](https://github.com/llm-d/llm-d).

Related contents:

- [Episode 616: From Boston to bootc @ Linux Unplugged](https://linuxunplugged.com/616).
- [Kubernetes as AI Infrastructure: Google Cloud, llm-d, and the CNCF @ Google Cloud Blog](https://cloud.google.com/blog/products/containers-kubernetes/llm-d-officially-a-cncf-sandbox-project/).]]>
            </summary>
            <updated>2026-04-03T16:45:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/44</id>
            <title type="text"><![CDATA[spaCy]]></title>
            <link rel="alternate" href="https://spacy.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/44"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[💫 Industrial-strength Natural Language Processing (NLP) in Python.

spaCy is a library for advanced Natural Language Processing in Python and Cython. It&amp;#039;s built on the very latest research, and was designed from day one to be used in real products.

spaCy comes with pretrained pipelines and currently supports tokenization and training for 70+ languages. It features state-of-the-art speed and neural network models for tagging, parsing, named entity recognition, text classification and more, multi-task learning with pretrained transformers like BERT, as well as a production-ready training system and easy model packaging, deployment and workflow management. spaCy is commercial open-source software, released under the MIT license.

- [spaCy @ GitHub](https://github.com/explosion/spaCy).

Related contents:

- [Embedding Millions of Text Documents With Qwen3 @ daft](https://www.daft.ai/blog/embedding-millions-of-text-documents-with-qwen3).
- [Learn How to Use Transformers with HuggingFace and SpaCy @ towards data science](https://towardsdatascience.com/mastering-nlp-with-spacy-part-4/).]]>
            </summary>
            <updated>2025-09-18T05:52:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/46</id>
            <title type="text"><![CDATA[Qwen/Qwen3-Embedding-0.6B @ Hugging Face]]></title>
            <link rel="alternate" href="https://huggingface.co/collections/Qwen/qwen3-67dd247413f0e2e4f653967f" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/46"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining.

Related contents:

- [Embedding Millions of Text Documents With Qwen3 @ daft](https://www.daft.ai/blog/embedding-millions-of-text-documents-with-qwen3).]]>
            </summary>
            <updated>2025-09-04T08:33:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/77</id>
            <title type="text"><![CDATA[YAMS]]></title>
            <link rel="alternate" href="https://yamsmemory.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/77"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Yet Another Memory System. Content addressable storage with excellent search.

Persistent memory for LLMs and applications. Content‑addressed storage with deduplication, compression, semantic search, and full‑text indexing.

- [YAMS @ GitHub](https://github.com/trvon/yams).]]>
            </summary>
            <updated>2025-09-17T19:31:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/82</id>
            <title type="text"><![CDATA[coderunner-ui]]></title>
            <link rel="alternate" href="https://github.com/instavm/coderunner-ui" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/82"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chat UI for Coderunner.

coderunner-ui is a local‑first AI workspace that lets you:

- Chat with local or remote LLMs
- Run generated code inside a fully isolated Apple Container VM
- Browse the web and automate tasks via a built‑in headless browser (Playwright) All without sending your data to the cloud.

Related contents:

- [I Want Everything Local — Building My Offline AI Workspace @ InstaVM](https://instavm.io/blog/building-my-offline-ai-workspace).]]>
            </summary>
            <updated>2025-09-17T19:31:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/83</id>
            <title type="text"><![CDATA[CodeRunner]]></title>
            <link rel="alternate" href="https://github.com/instavm/coderunner" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/83"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run AI Generated Code Locally.
A secure local sandbox to run LLM-generated code using Apple containers.

CodeRunner is an MCP (Model Context Protocol) server that executes AI-generated code in a sandboxed environment on your Mac using Apple&amp;#039;s native containers.

Related contents:

- [I Want Everything Local — Building My Offline AI Workspace @ InstaVM](https://instavm.io/blog/building-my-offline-ai-workspace).
- [Accelerate developer productivity with these 9 open source AI and MCP projects @ GitHub blog](https://github.blog/open-source/accelerate-developer-productivity-with-these-9-open-source-ai-and-mcp-projects/).]]>
            </summary>
            <updated>2025-10-27T14:06:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/107</id>
            <title type="text"><![CDATA[Omnara]]></title>
            <link rel="alternate" href="https://omnara.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/107"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your AI workforce launchpad, in your pocket. Talk to Your AI Agents from Anywhere!

Omnara transforms your AI agents (Claude Code, Cursor, GitHub Copilot, and more) from silent workers into communicative teammates. Get real-time visibility into what your agents are doing, respond to their questions instantly, and guide them to success - all from your phone.

- [Omnara @ GitHub](https://github.com/omnara-ai/omnara).]]>
            </summary>
            <updated>2025-10-14T09:44:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/111</id>
            <title type="text"><![CDATA[CodeRabbit]]></title>
            <link rel="alternate" href="https://www.coderabbit.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/111"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Cut Code Review Time &amp;amp; Bugs in Half. Instantly.

Supercharge your team to ship faster with the most advanced AI code reviews.

Related contents:

- [How to do code reviews with AI tools @ Tech World With Milan Newsletter](https://newsletter.techworld-with-milan.com/p/how-to-do-code-reviews-with-ai-tools).
- [How We Exploited CodeRabbit: From a Simple PR to RCE and Write Access on 1M Repositories @ Kudelski Security Research](https://research.kudelskisecurity.com/2025/08/19/how-we-exploited-coderabbit-from-a-simple-pr-to-rce-and-write-access-on-1m-repositories/).]]>
            </summary>
            <updated>2026-03-14T15:08:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/121</id>
            <title type="text"><![CDATA[Open Lovable]]></title>
            <link rel="alternate" href="https://github.com/mendableai/open-lovable" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/121"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chat with AI to build React apps instantly.

🔥 Clone and recreate any website as a modern React app in seconds.]]>
            </summary>
            <updated>2025-10-15T15:29:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/128</id>
            <title type="text"><![CDATA[POML (Prompt Orchestration Markup Language)]]></title>
            <link rel="alternate" href="https://microsoft.github.io/poml/latest/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/128"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[POML (Prompt Orchestration Markup Language) is a novel markup language designed to bring structure, maintainability, and versatility to advanced prompt engineering for Large Language Models (LLMs). It addresses common challenges in prompt development, such as lack of structure, complex data integration, format sensitivity, and inadequate tooling. POML provides a systematic way to organize prompt components, integrate diverse data types seamlessly, and manage presentation variations, empowering developers to create more sophisticated and reliable LLM applications.

- [POML (Prompt Orchestration Markup Language) @ GitHub](https://github.com/microsoft/poml).]]>
            </summary>
            <updated>2025-10-16T09:05:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/135</id>
            <title type="text"><![CDATA[Second Me]]></title>
            <link rel="alternate" href="https://www.secondme.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/135"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Train your AI self, amplify you, bridge the world.

 an open-source prototype where you craft your own AI self—a new AI species that preserves you, delivers your context, and defends your interests.

- [Second Me @ GitHub](https://github.com/mindverse/Second-Me).

Related contents:

- [Second Me - Créez votre jumeau virtuel en local @ Korben :fr:](https://korben.info/second-creez-votre-jumeau-numerique-local.html).]]>
            </summary>
            <updated>2025-10-16T12:06:13+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/137</id>
            <title type="text"><![CDATA[gpt-oss]]></title>
            <link rel="alternate" href="https://openai.com/open-models/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/137"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI.

- [gpt-oss @ GitHub](https://github.com/openai/gpt-oss).
- [gpt-oss @ Ollama](https://ollama.com/library/gpt-oss).

Related contents:

- [OpenAI libère enfin ses modèles open-weight GPT-OSS - Comment les utiliser ? @ Korben :fr:](https://korben.info/openai-gpt-oss-modeles-open-weight-ollama-tutoriel.html).]]>
            </summary>
            <updated>2025-10-16T12:06:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/166</id>
            <title type="text"><![CDATA[Claude Code IDE for Emacs]]></title>
            <link rel="alternate" href="https://github.com/manzaltu/claude-code-ide.el" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/166"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Claude Code IDE integration for Emacs.

Claude Code IDE for Emacs provides native integration with Claude Code CLI through the Model Context Protocol (MCP). Unlike simple terminal wrappers, this package creates a bidirectional bridge between Claude and Emacs, enabling Claude to understand and leverage Emacs’ powerful features—from LSP and project management to custom Elisp functions. This transforms Claude into a true Emacs-aware AI assistant that works within your existing workflow and can interact with your entire Emacs ecosystem.]]>
            </summary>
            <updated>2026-03-24T14:25:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/170</id>
            <title type="text"><![CDATA[stagewise]]></title>
            <link rel="alternate" href="https://stagewise.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/170"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[stagewise is the first frontend coding agent for existing production-grade web apps 🪄 -- Lives inside your browser 💻 -- Makes changes in local codebase 🤓 -- Compatible with all kinds of frameworks and setups 💪 .

- [stagewise @ GitHub](https://github.com/stagewise-io/stagewise).]]>
            </summary>
            <updated>2025-10-29T14:30:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/173</id>
            <title type="text"><![CDATA[OpenAI Harmony]]></title>
            <link rel="alternate" href="https://github.com/openai/harmony" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/173"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Renderer for the harmony response format to be used with gpt-oss.

The gpt-oss models were trained on the harmony response format for defining conversation structures, generating reasoning output and structuring function calls. If you are not using gpt-oss directly but through an API or a provider like HuggingFace, Ollama, or vLLM, you will not have to be concerned about this as your inference solution will handle the formatting. If you are building your own inference solution, this guide will walk you through the prompt format. The format is designed to mimic the OpenAI Responses API, so if you have used that API before, this format should hopefully feel familiar to you. gpt-oss should not be used without using the harmony format as it will not work correctly.]]>
            </summary>
            <updated>2026-03-24T14:25:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/174</id>
            <title type="text"><![CDATA[tambo]]></title>
            <link rel="alternate" href="https://tambo.co/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/174"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Add React UI components to your AI agent.

A React package for building AI-powered applications with generative UI, where users interact through natural language. 

- [tambo  @ GitHub](https://github.com/tambo-ai/tambo).]]>
            </summary>
            <updated>2025-10-27T15:09:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/194</id>
            <title type="text"><![CDATA[Price Per Token]]></title>
            <link rel="alternate" href="https://pricepertoken.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/194"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM API Pricing Data.

 Up-to-date pricing information for major LLM APIs including OpenAI, Anthropic, Google, and more. Compare costs across different AI models and find the best value for your use case. 

Related contents:

- [tokens are getting more expensive @ mandates](https://ethanding.substack.com/p/ai-subscriptions-get-short-squeezed).]]>
            </summary>
            <updated>2025-10-28T07:51:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/197</id>
            <title type="text"><![CDATA[🧠🤖Deep Agents]]></title>
            <link rel="alternate" href="https://github.com/hwchase17/deepagents?ref=blog.langchain.com" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/197"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Using an LLM to call tools in a loop is the simplest form of an agent. This architecture, however, can yield agents that are “shallow” and fail to plan and act over longer, more complex tasks. Applications like “Deep Research”, &amp;quot;Manus&amp;quot;, and “Claude Code” have gotten around this limitation by implementing a combination of four things: a planning tool, sub agents, access to a file system, and a detailed prompt.

deepagents is a Python package that implements these in a general purpose way so that you can easily create a Deep Agent for your application.]]>
            </summary>
            <updated>2025-10-16T09:08:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/198</id>
            <title type="text"><![CDATA[LangExtract]]></title>
            <link rel="alternate" href="https://github.com/google/langextract" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/198"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization. 

LangExtract is a Python library that uses LLMs to extract structured information from unstructured text documents based on user-defined instructions. It processes materials such as clinical notes or reports, identifying and organizing key details while ensuring the extracted data corresponds to the source text.

Related contents:

- [LangExtract - La nouvelle pépite de Google pour extraire des données structurées avec l&amp;#039;IA @ Korben :fr:](https://korben.info/langextract-la-nouvelle-pepite-de-google-pour-extraire-des-donnees-structurees-avec-lia.html).]]>
            </summary>
            <updated>2026-03-14T15:09:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/226</id>
            <title type="text"><![CDATA[🦌 DeerFlow]]></title>
            <link rel="alternate" href="https://deerflow.tech/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/226"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Deep Research at Your Fingertipsat Your Fingertips

Meet DeerFlow, your personal Deep Research assistant. With powerful tools like search engines, web crawlers, Python and MCP services, it delivers instant insights, comprehensive reports, and even captivating podcasts.

 DeerFlow is a community-driven Deep Research framework, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community. 

- [🦌 DeerFlow @ GitHub](https://github.com/bytedance/deer-flow).]]>
            </summary>
            <updated>2025-10-27T15:09:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/229</id>
            <title type="text"><![CDATA[Sourcebot]]></title>
            <link rel="alternate" href="https://www.sourcebot.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/229"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Understand your codebase.The Code Understanding Tool.

Sourcebot is a self-hosted tool that helps you answer questions about your code.

- [Sourcebot @ GitHub](https://github.com/sourcebot-dev/sourcebot).]]>
            </summary>
            <updated>2025-10-20T09:18:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/233</id>
            <title type="text"><![CDATA[MCP-Use]]></title>
            <link rel="alternate" href="https://mcp-use.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/233"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build and deploy MCP agents.

Spin-up and aggregate MCP servers through a single endpoint and zero friction.

 mcp-use is the easiest way to interact with mcp servers with custom agents.
🌐 MCP-Use is the open source way to connect any LLM to any MCP server and build custom MCP agents that have tool access, without using closed source or application clients.

- [MCP-Use @ GitHub](https://github.com/mcp-use/mcp-use).]]>
            </summary>
            <updated>2025-10-28T10:36:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/241</id>
            <title type="text"><![CDATA[FastChat]]></title>
            <link rel="alternate" href="https://github.com/lm-sys/FastChat" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/241"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

Related contents:

- [Exposer un LLM local avec FastChat @ DevSecOps :fr:](https://blog.stephane-robert.info/docs/developper/programmation/python/fastchat/).
- [Evals are not all you need @ Andrew Marble](https://www.marble.onl/posts/evals_are_not_all_you_need.html).]]>
            </summary>
            <updated>2025-10-27T15:09:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/245</id>
            <title type="text"><![CDATA[Crush]]></title>
            <link rel="alternate" href="https://github.com/charmbracelet/crush" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/245"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The glamourous AI coding agent for your favourite terminal 💘 

Your new coding bestie, now available in your favourite terminal.
Your tools, your code, and your workflows, wired into your LLM of choice.

Related contents:

- [Self-Hosting AI Models After Claude&amp;#039;s Usage Limits @ Peter Steinberger](https://steipete.me/posts/2025/self-hosting-ai-models).
- [Episode 627: The 2 a.m. Rescue @ Linux Matters](https://linuxunplugged.com/627).
- [Testing out Crush, a TUI based coding agent (in neovim btw) @ Graham Helton](https://grahamhelton.com/blog/crushing-it).
- [Coding for the Future Agentic World @ Elevate](https://addyo.substack.com/p/coding-for-the-future-agentic-world).]]>
            </summary>
            <updated>2025-11-20T08:05:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/270</id>
            <title type="text"><![CDATA[Grok CLI]]></title>
            <link rel="alternate" href="https://github.com/superagent-ai/grok-cli" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/270"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open-source AI agent that brings the power of Grok directly into your terminal.
A conversational AI CLI tool powered by Grok with intelligent text editor capabilities and tool usage.]]>
            </summary>
            <updated>2025-12-31T08:17:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/291</id>
            <title type="text"><![CDATA[LetterFeed]]></title>
            <link rel="alternate" href="https://github.com/LeonMusCoden/letterfeed" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/291"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Convert email newsletters into RSS feeds.

LetterFeed is a self-hosted application that transforms your email newsletters into RSS feeds.

It periodically scans your email inbox via IMAP for new emails from the senders you&amp;#039;ve configured. When it finds a new email, it processes it, and adds it as a new entry to the corresponding newsletter&amp;#039;s RSS feed.]]>
            </summary>
            <updated>2026-04-09T09:14:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/295</id>
            <title type="text"><![CDATA[YouTube TLDR]]></title>
            <link rel="alternate" href="https://youtubetldr.onrender.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/295"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Enter a YouTube URL to get an AI-generated summary.

 ⚡ A lightweight, self-hosted YouTube video summarizer with Gemini AI 

- [YouTube TLDR @ GitHub](https://github.com/Milkshiift/YouTubeTLDR).]]>
            </summary>
            <updated>2025-12-31T14:23:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/304</id>
            <title type="text"><![CDATA[Mesop]]></title>
            <link rel="alternate" href="https://mesop-dev.github.io/mesop/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/304"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Rapidly build AI apps in Python.

Create web apps without the complexity of frontend development.
Used at Google for rapid AI app development. 

Mesop is a Python-based UI framework that allows you to rapidly build web apps like demos and internal apps.

- [Mesop @ GitHub](https://github.com/mesop-dev/mesop).]]>
            </summary>
            <updated>2026-01-19T15:55:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/307</id>
            <title type="text"><![CDATA[Agents.md]]></title>
            <link rel="alternate" href="https://agentsmd.net/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/307"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Agents.md Guide for OpenAI Codex

Learn how to use Agents.md files to enhance OpenAI Codex and other AI agents in navigating your codebases, running tests, and adhering to your project&amp;#039;s standard practices.

Related contents:

- [Docs for AI agents @ https://technicalwriting.dev](https://technicalwriting.dev/ai/agents/).]]>
            </summary>
            <updated>2025-12-31T14:22:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/317</id>
            <title type="text"><![CDATA[any-llm]]></title>
            <link rel="alternate" href="https://mozilla-ai.github.io/any-llm/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/317"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Communicate with an LLM provider using a single interface.

any-llm is a Python library providing a single interface to different llm providers.

- [any-llm @ GitHub](https://github.com/mozilla-ai/any-llm).]]>
            </summary>
            <updated>2026-01-19T15:56:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/321</id>
            <title type="text"><![CDATA[Morphik]]></title>
            <link rel="alternate" href="https://www.morphik.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/321"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build Agents that Never Hallucinate.
Deploy the most accurate RAG in the world in two lines of code.

 The most accurate document search and store for building AI apps.

- [Morphik @ GitHub](https://github.com/morphik-org/morphik-core).

Related contents:

- [Don&amp;#039;t bother parsing: Just use images for RAG @ Morphik](https://www.morphik.ai/blog/stop-parsing-docs).]]>
            </summary>
            <updated>2026-01-13T13:25:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/339</id>
            <title type="text"><![CDATA[Fireplexity]]></title>
            <link rel="alternate" href="https://tools.firecrawl.dev/fireplexity" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/339"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-Powered Web Scraping &amp;amp; Data Enrichment.
AI-powered web search with instant results and follow-up questions.

 🔥 Blazing-fast AI search engine with real-time citations, streaming responses, and live data powered by Firecrawl 

- [Fireplexity @ GitHub](https://github.com/mendableai/fireplexity).

Related contents:

- [\#116: Les news sur le développement web et l&amp;#039;IA pour juillet 2025 RC1@ Double Slash :fr:](https://double-slash.dev/podcasts/news-jul25/).]]>
            </summary>
            <updated>2026-01-21T13:12:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/356</id>
            <title type="text"><![CDATA[Chainlit]]></title>
            <link rel="alternate" href="https://docs.chainlit.io/get-started/overview" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/356"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chainlit is an open-source Python package to build production ready Conversational AI.

- [Chainlit @ GitHub](https://github.com/Chainlit/chainlit).

Related contents:

- [Prise en main de Chainlit @ DevSecOps :fr:](https://blog.stephane-robert.info/docs/developper/programmation/python/chainlit/).]]>
            </summary>
            <updated>2026-01-23T15:18:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/359</id>
            <title type="text"><![CDATA[React Native Apple LLM Plugin]]></title>
            <link rel="alternate" href="https://github.com/deveix/react-native-apple-llm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/359"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[React Native plugin for Apple Intelligence and Foundation Models.

A React Native plugin to access Apple Intelligence Foundation Models using native on-device LLM APIs. This module lets you check model availability, create sessions, generate structured outputs (JSON), and text using Apple&amp;#039;s LLMs, all from React Native.]]>
            </summary>
            <updated>2026-01-23T15:18:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/382</id>
            <title type="text"><![CDATA[Vibe Kanban]]></title>
            <link rel="alternate" href="https://www.vibekanban.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/382"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Orchestrate AI Coding Agents.
Kanban board to manage your AI coding agents.

AI coding agents are increasingly writing the world&amp;#039;s code and human engineers now spend the majority of their time planning, reviewing, and orchestrating tasks. Vibe Kanban streamlines this process.

- [Vibe Kanban @ GitHub](https://github.com/BloopAI/vibe-kanban).

Related contents:

- [Software Engineering Is Becoming Plan and Review — Louis Knight-Webb, Vibe Kanban @ AI Engineer&amp;#039;s YouTube](https://www.youtube.com/watch?v=W76woOYHlvY).
- [\#131: News Mai 2026, TypeScript 7 en beta, faux package TanStack et agent Cursor destructeur @ Double Slash :fr:](https://double-slash.dev/podcasts/news-mai26/).]]>
            </summary>
            <updated>2026-06-04T05:37:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/388</id>
            <title type="text"><![CDATA[LangFast - Prompt Playground]]></title>
            <link rel="alternate" href="https://langfa.st/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/388"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A simple prompt playground to test and share your prompt templates.

A tool for testing, debugging, and refining AI prompts. Supports variables, templates to improve prompt quality and speed up development.]]>
            </summary>
            <updated>2026-01-20T15:32:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/414</id>
            <title type="text"><![CDATA[Zero]]></title>
            <link rel="alternate" href="https://0.email/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/414"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Powered Email, Built to Save You Time
Zero is an AI-native email client that manages your inbox, so you don&amp;#039;t have to.

Zero is an open-source AI email solution that gives users the power to self-host their own email app while also integrating external services like Gmail and other email providers. Our goal is to modernize and improve emails through AI agents to truly modernize emails.

- [Zero @ GitHub](https://github.com/Mail-0/Zero).]]>
            </summary>
            <updated>2025-08-28T17:06:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/445</id>
            <title type="text"><![CDATA[Spegel]]></title>
            <link rel="alternate" href="https://github.com/simedw/spegel" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/445"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Reflect the web through AI.

Automatically rewrites the websites into markdown optimised for viewing in the terminal. Read intro blog post here
This is a proof-of-concept, bugs are to be expected but feel free to raise an issue or pull request.

Related contents:

- [Spegel - A Terminal Browser That Uses LLMs to Rewrite Webpages @ SimEdw&amp;#039;s Blog](https://simedw.com/2025/06/23/introducing-spegel/).]]>
            </summary>
            <updated>2025-08-28T17:11:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/468</id>
            <title type="text"><![CDATA[Git Smart Squash]]></title>
            <link rel="alternate" href="https://github.com/edverma/git-smart-squash" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/468"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Use AI to transform your messy commit history into clean, logical commits that reviewers will love.

Git Smart Squash uses AI to automatically organize your changes into logical, well-structured commits in seconds.

Related contents:

- [Lundi 30 Juin 2025 - \#44 : un édito engagé et qui dénonce (parce que j&amp;#039;avais trop bu). @ RudeOps :fr:](https://join.rudeops.com/emails/webview/325165/158626394213975615).]]>
            </summary>
            <updated>2025-08-28T17:15:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/472</id>
            <title type="text"><![CDATA[Comet Browser by Perplexity]]></title>
            <link rel="alternate" href="https://www.perplexity.ai/comet" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/472"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Related contents:

- [Perplexity’s Comet Browser is Now Available in Beta @ Analytics India Magazine](https://analyticsindiamag.com/ai-news-updates/perplexitys-comet-browser-is-now-available-in-beta/).
- [Comet - Le navigateur IA de Perplexity débarque sur Windows @ Korben :fr:](https://korben.info/comet-navigateur-ia-perplexity-windows-beta.html).
- [Agentic Browser Security: Indirect Prompt Injection in Perplexity Comet @ Brave](https://brave.com/blog/comet-prompt-injection/).]]>
            </summary>
            <updated>2025-09-19T05:55:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/481</id>
            <title type="text"><![CDATA[AI Dataset Generator]]></title>
            <link rel="alternate" href="https://github.com/metabase/dataset-generator" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/481"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Generate realistic datasets for demos, learning, and dashboards. Instantly preview data, export as CSV or SQL, and explore with Metabase.]]>
            </summary>
            <updated>2025-08-28T17:17:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/486</id>
            <title type="text"><![CDATA[Claude Code Router]]></title>
            <link rel="alternate" href="https://github.com/musistudio/claude-code-router" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/486"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[This is a tool for routing Claude Code requests to different models, and you can customize any request.

 Use Claude Code as the foundation for coding infrastructure, allowing you to decide how to interact with the model while enjoying updates from Anthropic.]]>
            </summary>
            <updated>2025-08-28T17:18:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/497</id>
            <title type="text"><![CDATA[RTranslator]]></title>
            <link rel="alternate" href="https://github.com/niedev/RTranslator" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/497"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open source real-time translation app for Android that runs locally.

RTranslator is an (almost) open-source, free, and offline real-time translation app for Android.

Connect to someone who has the app, connect Bluetooth headphones, put the phone in your pocket and you can have a conversation as if the other person spoke your language.]]>
            </summary>
            <updated>2025-08-28T17:21:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/507</id>
            <title type="text"><![CDATA[SnapQL]]></title>
            <link rel="alternate" href="https://github.com/NickTikhonov/snap-ql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/507"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-powered Postgres Client.
cursor for data ⚡️ - explore your postgresql db in seconds.]]>
            </summary>
            <updated>2025-08-28T17:22:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/522</id>
            <title type="text"><![CDATA[KServe]]></title>
            <link rel="alternate" href="https://kserve.github.io/website/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/522"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Standardized Serverless ML Inference Platform on Kubernetes.
Highly scalable and standards based
Model Inference Platform on Kubernetes
for Trusted AI.

KServe provides a Kubernetes Custom Resource Definition for serving predictive and generative machine learning (ML) models. It aims to solve production model serving use cases by providing high abstraction interfaces for Tensorflow, XGBoost, ScikitLearn, PyTorch, Huggingface Transformer/LLM models using standardized data plane protocols.

- [KServe @ GitHub](https://github.com/kserve/kserve).

Related contents:

- [KServe becomes a CNCF incubating project @ CNCF Blog](https://www.cncf.io/blog/2025/11/11/kserve-becomes-a-cncf-incubating-project/).]]>
            </summary>
            <updated>2025-11-12T14:37:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/529</id>
            <title type="text"><![CDATA[Stagehand]]></title>
            <link rel="alternate" href="https://www.stagehand.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/529"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A browser automation SDK built for developers and LLMs.

Most existing browser automation tools either require you to write low-level code in a framework like Selenium, Playwright, or Puppeteer, or use high-level agents that can be unpredictable in production. By letting developers choose what to write in code vs. natural language, Stagehand is the natural choice for browser automations in production.

- [Stagehand @ GitHub](https://github.com/browserbase/stagehand).]]>
            </summary>
            <updated>2025-08-28T17:26:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/530</id>
            <title type="text"><![CDATA[Genkit]]></title>
            <link rel="alternate" href="https://github.com/firebase/genkit?tab=readme-ov-file" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/530"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit works with various models and platforms.

Genkit is an open-source framework for building full-stack AI-powered applications, built and used in production by Google&amp;#039;s Firebase. It provides SDKs for multiple programming languages with varying levels of stability]]>
            </summary>
            <updated>2025-08-28T17:26:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/555</id>
            <title type="text"><![CDATA[TensorZero]]></title>
            <link rel="alternate" href="https://www.tensorzero.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/555"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[open-source LLM infrastructure.

 TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation. 

- [TensorZero @ GitHub](https://github.com/tensorzero/tensorzero).]]>
            </summary>
            <updated>2025-08-28T17:30:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/559</id>
            <title type="text"><![CDATA[Forge Code]]></title>
            <link rel="alternate" href="https://forgecode.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/559"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The AI Shell.  AI enabled pair programmer for Claude, GPT, O Series, Grok, Deepseek, Gemini and 300+ models.

A comprehensive coding agent that integrates AI capabilities with your development environment.

- [Forge @ GitHub](https://github.com/antinomyhq/forge).]]>
            </summary>
            <updated>2025-08-28T17:31:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/569</id>
            <title type="text"><![CDATA[Datafari Enterprise Search]]></title>
            <link rel="alternate" href="https://www.datafari.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/569"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source, Distributed, Big Data Enterprise Search Engine.

Datafari is an open source enterprise search solution enriched with AI. It is the perfect product for anyone who needs to search and analyze its corporate data and documents, both within the content and the metadata. Plus, with its genAI modules, it allows to easily leverage mistral, openai, or local LLMs for your company data.

- [Datafari @ GitHub](https://github.com/francelabs/datafari).]]>
            </summary>
            <updated>2025-08-28T17:34:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/592</id>
            <title type="text"><![CDATA[DeepWiki]]></title>
            <link rel="alternate" href="https://deepwiki.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/592"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI documentation you can talk to, for every repo.

Related contents:

- [DeepWiki: Understand Any Codebase @ AI Tidbits](https://www.aitidbits.ai/p/deepwiki).]]>
            </summary>
            <updated>2025-09-05T04:18:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/609</id>
            <title type="text"><![CDATA[prompt-kit]]></title>
            <link rel="alternate" href="https://www.prompt-kit.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/609"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Core building blocks for AI apps.
High-quality, accessible, and customizable components for AI interfaces. 

Build chat experiences, AI agents, autonomous assistants, and more, quickly and beautifully.

- [prompt-kit @ GitHub](https://github.com/ibelick/prompt-kit).]]>
            </summary>
            <updated>2025-08-28T17:39:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/620</id>
            <title type="text"><![CDATA[Claude Composer]]></title>
            <link rel="alternate" href="https://github.com/possibilities/claude-composer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/620"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A tool that adds small enhancements to Claude Code.


- Reduced interruptions: Auto-handles permission dialogs based on configurable rules
- Flexible control: Rulesets define which actions to allow automatically
- Tool management: Toolsets configure which tools Claude can use
- Enhanced visibility: System notifications keep you informed]]>
            </summary>
            <updated>2025-08-28T17:42:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/630</id>
            <title type="text"><![CDATA[BrowserBee]]></title>
            <link rel="alternate" href="https://parsaghaffari.github.io/browserbee/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/630"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🐝 AI-powered browser assistant (&amp;quot;Cline for web browsing&amp;quot;).

- [BrowserBee @ GitHub](https://github.com/parsaghaffari/browserbee).]]>
            </summary>
            <updated>2025-08-28T17:43:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/633</id>
            <title type="text"><![CDATA[FastMCP]]></title>
            <link rel="alternate" href="https://gofastmcp.com/getting-started/welcome" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/633"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The fast, Pythonic way to build MCP servers and clients.

The Model Context Protocol (MCP) is a new, standardized way to provide context and tools to your LLMs, and FastMCP makes building MCP servers and clients simple and intuitive. Create tools, expose resources, define prompts, and more with clean, Pythonic code.

- [FastMCP @ GitHub](https://github.com/jlowin/fastmcp).
- [FastMCP Cloud](https://fastmcp.cloud/).

Related contents:

- [An Open-Source Maintainer&amp;#039;s Guide to Saying No @ Mostly Harmless](https://www.jlowin.dev/blog/oss-maintainers-guide-to-saying-no).
- [Learn MCP Essentials and How to Create Secure Agent Interfaces with FastMCP @ freeCodeCamp](https://www.freecodecamp.org/news/learn-mcp-essentials-and-how-to-create-secure-agent-interfaces-with-fastmcp/).
- [Build and Deploy a Remote MCP Server to GKE in 30 Minutes @ Google Cloud Blog](https://cloud.google.com/blog/topics/developers-practitioners/build-and-deploy-a-remote-mcp-server-to-gke-in-30-minutes/).]]>
            </summary>
            <updated>2026-06-24T11:51:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/636</id>
            <title type="text"><![CDATA[Lingo.dev]]></title>
            <link rel="alternate" href="https://lingo.dev/en" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/636"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Automated AI localization for web &amp;amp; mobile apps.

AI localization for teams who ship fast. Translate apps, websites, and entire databases using the best LLM models.

- [Lingo.dev @ GitHub](https://github.com/lingodotdev/lingo.dev).]]>
            </summary>
            <updated>2025-08-28T17:44:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/637</id>
            <title type="text"><![CDATA[KAI Scheduler]]></title>
            <link rel="alternate" href="https://github.com/NVIDIA/KAI-Scheduler" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/637"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[KAI Scheduler is an open source Kubernetes Native scheduler for AI workloads at large scale]]>
            </summary>
            <updated>2025-08-28T17:44:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/653</id>
            <title type="text"><![CDATA[Uzi]]></title>
            <link rel="alternate" href="http://blank" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/653"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[CLI for running large numbers of coding agents in parallel with git worktrees 

- [Uzi @ GitHub](https://github.com/devflowinc/uzi).

Related contents:

- [LLM Codegen go Brrr – Parallelization with Git Worktrees and Tmux @ Nick Khami&amp;#039;s Blog](https://www.skeptrune.com/posts/git-worktrees-agents-and-tmux/).]]>
            </summary>
            <updated>2025-08-28T17:46:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/654</id>
            <title type="text"><![CDATA[Claude Squad]]></title>
            <link rel="alternate" href="https://smtg-ai.github.io/claude-squad/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/654"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Manage multiple AI agents like Claude Code, Aider, Codex, and Amp. 10x your productivity.

- [Claude Squad @ GitHub](https://github.com/smtg-ai/claude-squad).

Related contents:

- [LLM Codegen go Brrr – Parallelization with Git Worktrees and Tmux @ Nick Khami&amp;#039;s Blog](https://www.skeptrune.com/posts/git-worktrees-agents-and-tmux/).]]>
            </summary>
            <updated>2025-08-28T17:46:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/664</id>
            <title type="text"><![CDATA[🐚 MCP Server in Bash]]></title>
            <link rel="alternate" href="https://github.com/muthuishere/mcp-server-bash-sdk" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/664"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A lightweight, zero-overhead implementation of the Model Context Protocol (MCP) server in pure Bash.

Why? Most MCP servers are just API wrappers with schema conversion. This implementation provides a zero-overhead alternative to Node.js, Python, or other heavy runtimes.]]>
            </summary>
            <updated>2025-08-28T17:48:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/670</id>
            <title type="text"><![CDATA[OneMCP]]></title>
            <link rel="alternate" href="https://onemcp.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/670"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run MCPs without the complexity ⚡️

OneMCP is an app that lets you run any MCP without the complexity of downloading repos, reading docs, or setting up servers.

Related contents:

- [OneMCP - Pour faire tourner des serveurs MCP facilement @ Korben :fr:](https://korben.info/onemcp-serveur-mcp-anthropic-facile.html).]]>
            </summary>
            <updated>2025-08-28T17:50:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/673</id>
            <title type="text"><![CDATA[LLM]]></title>
            <link rel="alternate" href="https://llm.datasette.io/en/stable/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/673"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A CLI utility and Python library for interacting with Large Language Models.

A CLI tool and Python library for interacting with OpenAI, Anthropic’s Claude, Google’s Gemini, Meta’s Llama and dozens of other Large Language Models, both via remote APIs and with models that can be installed and run on your own machine.

- [LLM @ GitHub](https://github.com/simonw/llm/).
- [llm-openrouter @ GitHub](https://github.com/simonw/llm-openrouter).

Related contents:

- [Large Language Models can run tools in your terminal with LLM 0.26 @ Simon Willison’s Weblog](https://simonwillison.net/2025/May/27/llm-tools/).
- [Using AI Without Leaving the Terminal: A Guide to llm @ Ashwin&amp;#039;s Blog](https://kashw1n.com/blog/llm-cli/).
- [Evaluating LLMs for my personal use case @ Graham King](https://darkcoding.net/software/personal-ai-evals-aug-2025/).
- [Kimi K3, and what we can still learn from the pelican benchmark @ Simon Willison’s Weblog](https://simonwillison.net/2026/Jul/16/kimi-k3/).]]>
            </summary>
            <updated>2026-07-21T06:28:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/676</id>
            <title type="text"><![CDATA[Memvid]]></title>
            <link rel="alternate" href="https://github.com/Olow304/memvid" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/676"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Video-Based AI Memory 🧠📹.

Video-based AI memory library. Store millions of text chunks in MP4 files with lightning-fast semantic search. No database needed. 

Memvid revolutionizes AI memory management by encoding text data into videos, enabling lightning-fast semantic search across millions of text chunks with sub-second retrieval times. Unlike traditional vector databases that consume massive amounts of RAM and storage, Memvid compresses your knowledge base into compact video files while maintaining instant access to any piece of information.]]>
            </summary>
            <updated>2025-08-28T17:50:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/706</id>
            <title type="text"><![CDATA[🛡️ PII Guard]]></title>
            <link rel="alternate" href="https://github.com/rpgeeganage/pII-guard" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/706"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🛡️ PII Guard is an LLM-powered tool that detects and manages Personally Identifiable Information (PII) in logs — designed to support data privacy and GDPR compliance]]>
            </summary>
            <updated>2025-08-28T17:55:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/725</id>
            <title type="text"><![CDATA[codesys]]></title>
            <link rel="alternate" href="https://github.com/RVCA212/codesys" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/725"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Python SDK for interacting with the Claude CLI tool.]]>
            </summary>
            <updated>2025-08-28T17:58:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/728</id>
            <title type="text"><![CDATA[Brokk]]></title>
            <link rel="alternate" href="https://brokk.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/728"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI for Large Codebases

The first AI-native code platform that gives large projects compiler-grade context, so LLMs stay useful even when your repo spans millions of lines.

Brokk (the Norse god of the forge) is the first code assistant that understands code semantically, not just as chunks of text. Brokk is designed to allow LLMs to work effectively on large codebases that cannot be jammed entirely into working context.

- [Brokk @ GitHub](https://github.com/brokkai/brokk).]]>
            </summary>
            <updated>2025-08-28T17:59:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/735</id>
            <title type="text"><![CDATA[Ktransformers]]></title>
            <link rel="alternate" href="https://kvcache-ai.github.io/ktransformers/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/735"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Flexible Framework for Experiencing Cutting-edge LLM Inference Optimizations.

 KTransformers, pronounced as Quick Transformers, is designed to enhance your 🤗 Transformers experience with advanced kernel optimizations and placement/parallelism strategies.

KTransformers is a flexible, Python-centric framework designed with extensibility at its core. By implementing and injecting an optimized module with a single line of code, users gain access to a Transformers-compatible interface, RESTful APIs compliant with OpenAI and Ollama, and even a simplified ChatGPT-like web UI. 

- [Ktransformers @ GitHub](https://github.com/kvcache-ai/ktransformers).]]>
            </summary>
            <updated>2025-08-28T18:00:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/740</id>
            <title type="text"><![CDATA[Semantic Unit Testing]]></title>
            <link rel="alternate" href="https://github.com/alexmolas/suite" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/740"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Semantic unit testing is a testing approach that evaluates whether a function&amp;#039;s implementation aligns with its documented behavior. The code is analyzed using LLMs to assess whether the implementation matches the expected behavior described in the docstring.

Related contents:

- [Semantic Unit Testing @ Alex Molas](https://www.alexmolas.com/2025/04/09/semantic-unit-testing.html).]]>
            </summary>
            <updated>2025-08-28T18:02:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/762</id>
            <title type="text"><![CDATA[react-native-ai]]></title>
            <link rel="alternate" href="https://github.com/callstackincubator/ai" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/762"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[On-device LLM execution in React Native with Vercel AI SDK compatibility.

Run LLMs on-device in React Native via MLC LLM Engine with compatibility for Vercel AI SDK.]]>
            </summary>
            <updated>2025-08-28T18:04:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/765</id>
            <title type="text"><![CDATA[ANEMLL]]></title>
            <link rel="alternate" href="https://github.com/Anemll/Anemll" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/765"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Artificial Neural Engine Machine Learning Library.

ANEMLL (pronounced like &amp;quot;animal&amp;quot;) is an open-source project focused on accelerating the porting of Large Language Models (LLMs) to tensor processors, starting with the Apple Neural Engine (ANE).]]>
            </summary>
            <updated>2025-08-28T18:06:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/766</id>
            <title type="text"><![CDATA[Taskmaster AI]]></title>
            <link rel="alternate" href="https://www.task-master.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/766"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The PM for your AI agent.
 An AI-powered task-management system you can drop into Cursor, Lovable, Windsurf, Roo, and others. 

Taskmaster is your AI&amp;#039;s personal project manager. Organize, research, expand, prioritize, and ship tasks effortlessly. Enjoy permanent context, zero drift &amp;amp; instant clarity. It&amp;#039;s free, open-source &amp;amp; API-friendly. Let&amp;#039;s vibe productively.

- [Taskmaster AI @ GitHub](https://github.com/eyaltoledano/claude-task-master).]]>
            </summary>
            <updated>2025-08-28T18:06:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/779</id>
            <title type="text"><![CDATA[Gemini Coder]]></title>
            <link rel="alternate" href="https://gemini-coder.netlify.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/779"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[free AI coding.
 Non-agentic 100% free &amp;amp; open source coding tool for AI-assisted programming. 

Copy folders and files for chatbots or initialize them hands-free! Use built-in API Tools for code completions, file refactoring and applying chat responses.

- [Gemini Coder @ GitHub](https://github.com/robertpiosik/gemini-coder).]]>
            </summary>
            <updated>2025-08-28T18:07:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/790</id>
            <title type="text"><![CDATA[CoRT (Chain of Recursive Thoughts) 🧠🔄]]></title>
            <link rel="alternate" href="https://github.com/PhialsBasement/Chain-of-Recursive-Thoughts" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/790"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[I made my AI think harder by making it argue with itself repeatedly. It works stupidly well. 

CoRT makes AI models recursively think about their responses, generate alternatives, and pick the best one. It&amp;#039;s like giving the AI the ability to doubt itself and try again... and again... and again.]]>
            </summary>
            <updated>2025-08-28T18:10:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/799</id>
            <title type="text"><![CDATA[CleverBee]]></title>
            <link rel="alternate" href="https://cleverb.ee/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/799"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Transparent AI, Rooted in Research, Open to All.
The Open Source Deep Researcher Tool.
AI-Powered Online Data Information Synthesis Assistant.

CleverBee is a powerful Python-based research assistant agent using Large Language Models (LLMs) like Claude and Gemini, Playwright for web browsing, and Chainlit for an interactive UI. It performs research assistance by browsing the web, extracting content (HTML), cleaning it, and synthesizing findings based on user research topics.

- [CleverBee @ GitHub](https://github.com/SureScaleAI/cleverbee).]]>
            </summary>
            <updated>2025-08-28T18:10:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/823</id>
            <title type="text"><![CDATA[Boson]]></title>
            <link rel="alternate" href="https://github.com/bosonstack/boson" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/823"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A self-contained, lightweight and OOB research platform for modern ML.

Boson is a lightweight, fully containerized, and feature-rich machine learning research platform. It centralizes essential tools to help teams keep projects lean, organized, and reproducible—while reducing overhead and boosting productivity. Think Databricks/Sagemaker but local and free.

Boson enables engineers and researchers to iterate faster without getting bogged down by infrastructure or tooling complexity.]]>
            </summary>
            <updated>2025-08-28T18:14:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/849</id>
            <title type="text"><![CDATA[Index]]></title>
            <link rel="alternate" href="https://github.com/lmnr-ai/index" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/849"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-Source Browser Agent for autonomously performing complex tasks on the web]]>
            </summary>
            <updated>2025-08-28T18:19:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/881</id>
            <title type="text"><![CDATA[RowBoat Labs]]></title>
            <link rel="alternate" href="https://www.rowboatlabs.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/881"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-powered multi-agent builder.
Let AI build multi-agent systems for you Build with Agents SDK.
Connect MCP tools. Open-source.

- [RowBoat @ GitHub](https://github.com/rowboatlabs/rowboat).]]>
            </summary>
            <updated>2025-08-28T18:24:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/891</id>
            <title type="text"><![CDATA[Cline]]></title>
            <link rel="alternate" href="https://cline.bot/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/891"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Autonomous Coding Agent for VS Code.

 Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way. 

- [Cline @ GitHub](https://github.com/cline/cline).

Related contents:

- [Épisode \#108 - Les news web dev pour Mars 2025 RC2 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-mars-rc2/).
- [Using Skills with Cline @ Data Science Collective](https://medium.com/data-science-collective/using-skills-with-cline-3acf2e289a7c).]]>
            </summary>
            <updated>2026-01-15T07:46:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/897</id>
            <title type="text"><![CDATA[Open Codex CLI]]></title>
            <link rel="alternate" href="https://github.com/codingmoh/open-codex" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/897"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fully open-source command-line AI assistant inspired by OpenAI Codex, supporting local language models. 

Open Codex is a fully open-source command-line AI assistant inspired by OpenAI Codex, supporting local language models like phi-4-mini.]]>
            </summary>
            <updated>2025-08-28T18:27:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/899</id>
            <title type="text"><![CDATA[MCP Containers]]></title>
            <link rel="alternate" href="https://metorial.com/mcp/containers" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/899"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Containerized versions of hundreds of MCP servers 📡 🧠 

While experimenting with Model Context Protocol (MCP) servers, we found that setting them up could be a bit tedious and time-consuming. To simplify the process, we created containerized versions of these servers—making it quick, easy, and secure for anyone to get started.

- [MCP Containers @ GitHub](https://github.com/metorial/mcp-containers).]]>
            </summary>
            <updated>2025-08-28T18:27:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/906</id>
            <title type="text"><![CDATA[sidekick-cli]]></title>
            <link rel="alternate" href="https://github.com/geekforbrains/sidekick-cli" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/906"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your agentic CLI developer.

Sidekick is an agentic CLI-based AI tool inspired by Claude Code, Copilot, Windsurf and Cursor. It&amp;#039;s meant to be an open source alternative to these tools, providing a similar experience but with the flexibility of using different LLM providers while keeping the agentic workflow.]]>
            </summary>
            <updated>2025-08-28T18:28:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/911</id>
            <title type="text"><![CDATA[Exmeralda]]></title>
            <link rel="alternate" href="https://exmeralda.chat/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/911"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Exmeralda helps you ask questions about Elixir libraries and get accurate, version-specific answers. Powered by Retrieval-Augmented Generation (RAG), it combines the latest AI with real documentation to deliver helpful, grounded responses. 

- [Exmeralda @ GitHub](https://github.com/bitcrowd/exmeralda/).]]>
            </summary>
            <updated>2025-08-28T18:30:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/912</id>
            <title type="text"><![CDATA[Pocket Flow]]></title>
            <link rel="alternate" href="https://the-pocket.github.io/PocketFlow/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/912"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A 100-line minimalist LLM framework for Agents, Task Decomposition, RAG, etc.

- [Pocket Flow @ GitHub](https://github.com/The-Pocket/PocketFlow).

Related contents:

- [Turns Codebase into Easy Tutorial with AI @ GitHub](https://github.com/The-Pocket/Tutorial-Codebase-Knowledge).]]>
            </summary>
            <updated>2025-08-28T18:30:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/921</id>
            <title type="text"><![CDATA[React Agent Hooks]]></title>
            <link rel="alternate" href="https://github.com/chuanqisun/react-agent-hooks" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/921"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn React hooks into LLM tools]]>
            </summary>
            <updated>2025-08-28T18:31:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/923</id>
            <title type="text"><![CDATA[A practical guide to building agents :pdf:]]></title>
            <link rel="alternate" href="https://cdn.openai.com/business-guides-and-resources/a-practical-guide-to-building-agents.pdf" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/923"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Agents are AI systems that can perform workflows on users&amp;#039; behalf with a high degree of independence. This guide, designed for product and engineering teams, explores how to build agents with frameworks for identifying promise use cases, clear patterns for designing agent logic and orchestration, and best practices to ensure agents run safely, predictably, and effectively. It provides the foundational knowledge needed to confidently start building agents. Building reliable agents means starting with strong foundations - start small, validate with real users, and grow capabilities over time.]]>
            </summary>
            <updated>2025-08-28T18:31:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/928</id>
            <title type="text"><![CDATA[12 Factor Agents]]></title>
            <link rel="alternate" href="https://github.com/humanlayer/12-factor-agents" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/928"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Principles for building reliable LLM applications.

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?]]>
            </summary>
            <updated>2025-08-28T18:32:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/952</id>
            <title type="text"><![CDATA[Claude Code]]></title>
            <link rel="alternate" href="https://www.anthropic.com/claude-code" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/952"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Claude Code is Anthropic’s new agentic coding tool. A command-line companion that can read, edit, and manage your projects through natural language prompts. It integrates directly into your development environment, removing friction and helping you focus on what matters most: writing great code.

Related contents:

- [Poking Around Claude Code @ Han, Not Solo](https://leehanchung.github.io/blogs/2025/03/07/claude-code/).
- [What makes Claude Code so damn good (and how to recreate that magic in your agent)!? @ minusx](https://minusx.ai/blog/decoding-claude-code/).
- [Claude Code: Best practices for agentic coding @ Engineering at Anthropic](https://www.anthropic.com/engineering/claude-code-best-practices).
- [Agentic Coding Recommendations @ Armin Ronacher&amp;#039;s Thoughts and Writings](https://lucumr.pocoo.org/2025/6/12/agentic-coding/).
- [Quand Claude Code pilote votre terminal... @ Korben :fr:](https://korben.info/quand-claude-code-pilote-votre-terminal.html).
- [Turning Claude Code Into My Best Design Partner @ Between the Prompts](https://betweentheprompts.com/design-partner/).
- [Using Claude Code to modernize a 25-year-old kernel driver @ Dmitry Brant](https://dmitrybrant.com/2025/09/07/using-claude-code-to-modernize-a-25-year-old-kernel-driver).
- [The babysitter problem @ chrisbeckman.dev](https://chrisbeckman.dev/posts/the-babysitter-problem).
- [Claude Skills are awesome, maybe a bigger deal than MCP @ Simon Willison’s Weblog](https://simonwillison.net/2025/Oct/16/claude-skills/).
- [Mastering Claude Code in 30 minutes @ Anthropic&amp;#039;s YouTube](https://www.youtube.com/watch?v=6eBSHbLKuN0).]]>
            </summary>
            <updated>2026-04-28T07:42:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/954</id>
            <title type="text"><![CDATA[awesome-ai-system-prompts]]></title>
            <link rel="alternate" href="https://github.com/dontriskit/awesome-ai-system-prompts" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/954"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Crafting Effective Prompts for Agentic AI Systems: Patterns and Practices.

 🧠 Curated collection of system prompts for top AI tools. Perfect for AI agent builders and prompt engineers. Incuding: ChatGPT, Claude, Perplexity, Manus, Claude-Code, Loveable, v0, Grok, same new, windsurf, notion, and MetaAI.]]>
            </summary>
            <updated>2025-08-28T18:36:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/958</id>
            <title type="text"><![CDATA[Zev]]></title>
            <link rel="alternate" href="https://github.com/dtnewman/zev" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/958"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A simple CLI to help you remember commands.

Zev helps you remember (or discover) terminal commands using natural language.]]>
            </summary>
            <updated>2025-08-28T18:38:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/970</id>
            <title type="text"><![CDATA[LocalAI]]></title>
            <link rel="alternate" href="https://localai.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/970"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LocalAI is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families and architectures. Does not require GPU. It is created and maintained by Ettore Di Giacinto.

- [LocalAI @ GitHub](https://github.com/mudler/LocalAI).]]>
            </summary>
            <updated>2025-08-28T18:39:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/973</id>
            <title type="text"><![CDATA[Clidey WhoDB]]></title>
            <link rel="alternate" href="https://whodb.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/973"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A lightweight next-gen data explorer - Postgres, MySQL, SQLite, MongoDB, Redis, MariaDB, Elastic Search, and Clickhouse with Chat interface 

- [WhoDB @ GitHub](https://github.com/clidey/whodb).

Related contents:

- [Digest #186: Inside the AWS Outage, Docker Compose in Production, F1 Hacks and 86,000 npm Packages Attacks @ DevOps Bulletin](https://www.devopsbulletin.com/p/digest-186-inside-the-aws-outage).]]>
            </summary>
            <updated>2025-11-03T10:12:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/989</id>
            <title type="text"><![CDATA[smartfunc]]></title>
            <link rel="alternate" href="https://github.com/koaning/smartfunc" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/989"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn docstrings into LLM-functions.]]>
            </summary>
            <updated>2025-08-28T18:42:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1009</id>
            <title type="text"><![CDATA[🐫 CAMEL]]></title>
            <link rel="alternate" href="https://www.camel-ai.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1009"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The first and the best multi-agent framework. Finding the Scaling Law of Agents

Building Multi-Agent Systems for Task Automation.

 🐫 CAMEL is an open-source community dedicated to finding the scaling laws of agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

CAMEL emerges as the earliest LLM-based multi-agent framework, and is now a generic framework to build and use LLM-based agents for real-world task solving. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

- [🐫 CAMEL @ GitHub](https://github.com/camel-ai/camel).
- [🐫 CAMEL&amp;#039;s documentation](https://docs.camel-ai.org/).]]>
            </summary>
            <updated>2025-08-28T18:46:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1011</id>
            <title type="text"><![CDATA[Gemini API]]></title>
            <link rel="alternate" href="https://ai.google.dev/gemini-api/docs?hl=en" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1011"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Google AI for Developers

- [Gemini API Cookbook @ GitHub](https://github.com/google-gemini/cookbook).]]>
            </summary>
            <updated>2025-08-28T18:46:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1018</id>
            <title type="text"><![CDATA[Browser MCP]]></title>
            <link rel="alternate" href="https://browsermcp.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1018"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[MCP server for your browser.

 Browser MCP is a Model Context Provider (MCP) server that allows AI applications to control your browser.

If you want to automate actions on a website, like repeatedly fill out a form, you normally can&amp;#039;t do it with AI apps like Cursor or Claude because they don&amp;#039;t have access to a web browser. With Browser MCP, you can connect AI apps to your browser so they can automate tasks on your behalf.

- [Browser MCP @ GitHub](https://github.com/browsermcp/mcp).]]>
            </summary>
            <updated>2025-08-28T18:46:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1071</id>
            <title type="text"><![CDATA[GitSummarize]]></title>
            <link rel="alternate" href="https://gitsummarize.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1071"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn any GitHub repository into a comprehensive AI-powered documentation hub.

Generate beautiful, world-class documentation from any GitHub repository — instantly.
Just replace hub with summarize in any GitHub URL to generate a live, interactive documentation hub.

- [GitSummarize @ GitHub](https://github.com/antarixxx/gitsummarize).]]>
            </summary>
            <updated>2025-08-28T18:55:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1078</id>
            <title type="text"><![CDATA[Tablepilot]]></title>
            <link rel="alternate" href="https://github.com/Yiling-J/tablepilot" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1078"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A CLI/API/WebUI tool designed to generate and autofill tables using AI in a scalable and diverse way.]]>
            </summary>
            <updated>2025-08-28T18:56:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1087</id>
            <title type="text"><![CDATA[airflow-ai-sdk]]></title>
            <link rel="alternate" href="https://github.com/astronomer/airflow-ai-sdk?tab=readme-ov-file" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1087"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An SDK for working with LLMs and AI Agents from Apache Airflow, based on Pydantic AI.
 
It allows users to call LLMs and orchestrate agent calls directly within their Airflow pipelines using decorator-based tasks. The SDK leverages the familiar Airflow @task syntax with extensions like @task.llm, @task.llm_branch, and @task.agent.]]>
            </summary>
            <updated>2025-08-28T18:58:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1095</id>
            <title type="text"><![CDATA[Langtrace]]></title>
            <link rel="alternate" href="https://www.langtrace.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1095"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Transform Al Prototypes into Enterprise-Grade Products.

Langtrace is an Open Source Observability and Evaluations Platform for Al Agents.

- [Langtrace @ GitHub](https://github.com/Scale3-Labs/langtrace).

Related contents:

- [Tracing a RAG based Chatbot with Elastic Distributions of OpenTelemetry and Langtrace @ elastic observability labs](https://www.elastic.co/observability-labs/blog/openai-tracing-langtrace-elastic).]]>
            </summary>
            <updated>2025-08-28T18:58:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1111</id>
            <title type="text"><![CDATA[IBM Granite]]></title>
            <link rel="alternate" href="https://www.ibm.com/granite" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1111"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLMs for language and code + Time series and geospatial foundation models.

Achieve over 90% cost savings with Granite&amp;#039;s smaller and open models, designed for developer efficiency.
Fit for purpose and open sourced, these enterprise-ready models deliver exceptional performance against safety benchmarks and across a wide range of enterprise tasks from cybersecurity to RAG.

- [IBM Granite @ Hugging Face](https://huggingface.co/ibm-granite).

Related contents:

- [Optimizing for efficiency with IBM’s Granite @ Changelog&amp;#039;s Practical AI](https://practicalai.fm/306).]]>
            </summary>
            <updated>2025-08-28T19:02:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1161</id>
            <title type="text"><![CDATA[Cocommit]]></title>
            <link rel="alternate" href="https://github.com/andrewromanenco/cocommit" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1161"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Copilot for Git.

Cocommit is a command-line tool that works with your HEAD commit and leverages an LLM of your choice to enhance commit quality. 

A good commit consists of multiple elements, but at a minimum, it should have a well-crafted commit message. Cocommit analyzes the message from the last (HEAD) commit and suggests improvements, highlighting both strengths and areas for enhancement.]]>
            </summary>
            <updated>2025-08-28T19:10:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1162</id>
            <title type="text"><![CDATA[Playwright MCP]]></title>
            <link rel="alternate" href="https://github.com/microsoft/playwright-mcp" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1162"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Playwright Tools for MCP.

A Model Context Protocol (MCP) server that provides browser automation capabilities using Playwright. This server enables LLMs to interact with web pages through structured accessibility snapshots, bypassing the need for screenshots or visually-tuned models.

Related contents:

- [Guide détaillé du serveur Playwright MCP @ bright data :fr:](https://brightdata.fr/blog/ai/playwright-mcp-server).
- [\#346.src - IA &amp;amp; DevX: Code assisté, valeur humaine préservée avec Jocelyn N&amp;#039;takpe @ \&amp;lt;ifttd&amp;gt;](https://www.ifttd.io/episodes/ia-devx).]]>
            </summary>
            <updated>2026-03-22T18:14:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1166</id>
            <title type="text"><![CDATA[GitHub Copilot]]></title>
            <link rel="alternate" href="https://github.com/features/copilot" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1166"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your AI pair programmer.

Related contents:

- [AI-assisted coding with GitHub&amp;#039;s COO @ Practical AI](https://practicalai.fm/307).
- [\#108 Les dernières (r)évolutions de GitHub Copilot (1/2) @  DevApps.ms :fr:](https://devapps.ms/podcasts/108-evolutions-github-copilot-1).]]>
            </summary>
            <updated>2025-08-28T19:10:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1171</id>
            <title type="text"><![CDATA[LangGraph]]></title>
            <link rel="alternate" href="https://www.langchain.com/langgraph" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1171"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Balance agent control with agency.  Build resilient language agents as graphs. 

Gain control with LangGraph to design agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform.

LangGraph — used by Replit, Uber, LinkedIn, GitLab and more — is a low-level orchestration framework for building controllable agents. While langchain provides integrations and composable components to streamline LLM application development, the LangGraph library enables agent orchestration — offering customizable architectures, long-term memory, and human-in-the-loop to reliably handle complex tasks.

- [LangGraph @ GitHub](https://github.com/langchain-ai/langgraph).

Related contents:

- [Why we chose LangGraph to build our coding agent @  qodo](https://www.qodo.ai/blog/why-we-chose-langgraph-to-build-our-coding-agent/).
- [LangGraph for complex workflows @ surma.dev](https://surma.dev/things/langgraph/).
- [LangChain, LangGraph Flaws Expose Files, Secrets, Databases in Widely Used AI Frameworks @ The Hacker News](https://thehackernews.com/2026/03/langchain-langgraph-flaws-expose-files.html).]]>
            </summary>
            <updated>2026-03-30T18:57:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1184</id>
            <title type="text"><![CDATA[Vibe Coding Manifesto]]></title>
            <link rel="alternate" href="https://vibemanifesto.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1184"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[We are uncovering a new way of building software by embracing AI, iteration, and human intuition.

- [Vibe Coding Manifesto Landing Page @ GitHub](https://github.com/przadka/vibemanifesto-lp/).]]>
            </summary>
            <updated>2025-08-28T19:14:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1195</id>
            <title type="text"><![CDATA[Claude Code (Research Preview) Cleanroom Deobfuscation]]></title>
            <link rel="alternate" href="https://github.com/ghuntley/claude-code-source-code-deobfuscation" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1195"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[This is a cleanroom deobfuscation of the official Claude Code npm package. 

Related contents:

- [Yes, Claude Code can decompile itself. Here&amp;#039;s the source code @ gh](https://ghuntley.com/tradecraft/).
- [Comment les IA transforment tout code en code open source @ Korben :fr:](https://korben.info/llm-decompilation-claude-code-hack-intelligence-artificielle.html).]]>
            </summary>
            <updated>2025-08-28T19:15:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1196</id>
            <title type="text"><![CDATA[Fleur MCP App Store]]></title>
            <link rel="alternate" href="https://www.fleurmcp.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1196"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fleur is the app store for Claude.
 The easiest way to discover and install MCPs.

Fleur is a desktop application that serves as an app marketplace for MCPs. It allows you to discover, install, and manage apps that extend the functionality of Claude Desktop and Cursor.

All without having to use a command line. Fleur is made for non-technical users in mind, but is open-source and extensible so developers can make it their own.

- [Fleur @ GitHub](https://github.com/fleuristes/fleur).

Related contents:

- [Fleur MCP - Comment donner des super-pouvoirs à Claude @ Korben :fr:](https://korben.info/fleur-mcp-comment-donner-super-pouvoirs-claude.html).]]>
            </summary>
            <updated>2025-08-28T19:15:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1223</id>
            <title type="text"><![CDATA[Fetcher MCP]]></title>
            <link rel="alternate" href="https://github.com/jae-jae/fetcher-mcp" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1223"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[MCP server for fetch web page content using Playwright headless browser.]]>
            </summary>
            <updated>2025-08-28T19:19:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1240</id>
            <title type="text"><![CDATA[NVIDIA Dynamo]]></title>
            <link rel="alternate" href="https://developer.nvidia.com/dynamo" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1240"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Datacenter Scale Distributed Inference Serving Framework.

NVIDIA Dynamo is a high-throughput low-latency inference framework designed for serving generative AI and reasoning models in multi-node distributed environments. Dynamo is designed to be inference engine agnostic (supports TRT-LLM, vLLM, SGLang or others) and captures LLM-specific capabilities.

- [Dynamo @ GitHub](https://github.com/ai-dynamo/dynamo).

Related contents:

- [A closer look at Dynamo, Nvidia&amp;#039;s &amp;#039;operating system&amp;#039; for AI inference @ The register](https://www.theregister.com/2025/03/23/nvidia_dynamo/).]]>
            </summary>
            <updated>2025-08-28T19:23:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1253</id>
            <title type="text"><![CDATA[Amurex]]></title>
            <link rel="alternate" href="https://www.amurex.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1253"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Invisible Companion.

Amurex is your simple yet powerful AI meeting assistant that seamlessly integrates into your workflow. Built with cutting-edge AI, Amurex ensures you never miss a detail, always stay on top of action items, and make every meeting more productive.

- [Amurex @ GitHub](https://github.com/thepersonalaicompany/amurex).
- [Amurex Backend @ GitHub](https://github.com/thepersonalaicompany/amurex-backend).]]>
            </summary>
            <updated>2025-08-28T19:24:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1260</id>
            <title type="text"><![CDATA[Auntie PDF]]></title>
            <link rel="alternate" href="https://auntiepdf.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1260"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your all-knowing guide that unpacks every PDF into clear, actionable insights. 

Auntie PDF is a web application that helps users extract information and insights from PDF documents. With a sassy, helpful personality, Auntie PDF makes understanding complex documents easier and more engaging.]]>
            </summary>
            <updated>2025-08-28T19:27:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1274</id>
            <title type="text"><![CDATA[RubyLLM]]></title>
            <link rel="alternate" href="https://rubyllm.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1274"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A delightful Ruby way to work with AI through a unified interface to OpenAI, Anthropic, Google, and DeepSeek.
 A delightful Ruby way to work with AI. No configuration madness, no complex callbacks, no handler hell – just beautiful, expressive Ruby code. 

- [RubyLLM @ GitHub](https://github.com/crmne/ruby_llm).

Related contents:

- [Episode 639: RubyLLM with Carmine Paolino @ Coder Radio](https://coder.show/639).]]>
            </summary>
            <updated>2026-03-12T19:34:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1276</id>
            <title type="text"><![CDATA[Local Deep Research]]></title>
            <link rel="alternate" href="https://github.com/LearningCircuit/local-deep-research" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1276"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A powerful AI-powered research assistant that performs deep, iterative analysis using multiple LLMs and web searches. The system can be run locally for privacy or configured to use cloud-based LLMs for enhanced capabilities.

Related contents:

- [Local Deep Research - L&amp;#039;assistant de recherche IA open-source qui cite ses sources @ Korben :fr:](https://korben.info/local-deep-research-alternative-gratuite-recherche-ia-sourcee.html).]]>
            </summary>
            <updated>2025-08-28T19:29:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1286</id>
            <title type="text"><![CDATA[Avid]]></title>
            <link rel="alternate" href="https://www.getavid.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1286"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-Powered Mobile App Builder.

Transform your ideas into polished mobile applications with our intuitive mobile app generator. No complex setup required.]]>
            </summary>
            <updated>2025-08-28T19:31:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1288</id>
            <title type="text"><![CDATA[Factorio Learning Environment]]></title>
            <link rel="alternate" href="https://jackhopkins.github.io/factorio-learning-environment/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1288"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A non-saturating, open-ended environment for evaluating LLMs in Factorio.

 Large Language Models (LLMs) are rapidly saturating existing benchmarks, necessitating new open-ended evaluations. We introduce the Factorio Learning Environment (FLE), based on the game of Factorio, that tests agents in long-term planning, program synthesis, and resource optimization. 

- [Factorio Learning Environment @ GitHub](https://github.com/JackHopkins/factorio-learning-environment).]]>
            </summary>
            <updated>2025-08-28T19:31:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1303</id>
            <title type="text"><![CDATA[Sidekick]]></title>
            <link rel="alternate" href="https://github.com/johnbean393/Sidekick" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1303"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A native macOS app that allows users to chat with a local LLM that can respond with information from files, folders and websites on your Mac without installing any other software. Powered by llama.cpp. 

Chat with an local LLM that can respond with information from your files, folders and websites on your Mac without installing any other software. All conversations happen offline, and your data is saved locally.]]>
            </summary>
            <updated>2025-08-28T19:33:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1327</id>
            <title type="text"><![CDATA[Alerte GenIA :fr:]]></title>
            <link rel="alternate" href="https://next.ink/171509/alerte-genia-notre-extension-debarque-sur-firefox-android-et-identifie-2-000-sites/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1327"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Affiche une alerte sur des sites générés tout ou partie par des IA. Liste gérée par [Next.ink](https://next.ink/).

Related contents:

- [Alerte sur les sites GenAI @ Firefox Browser Add-Ons](https://addons.mozilla.org/fr/firefox/addon/alerte-sur-les-sites-genai/).
- [Alerte sur les sites GenAI, par Next.ink @ Chrome Web Store](https://chromewebstore.google.com/detail/alerte-sur-les-sites-gena/bcmpghnhminmlljeomngepamejbopffc).
- [Est-on plus efficace en utilisant une IA type ChatGPT ? @ Tugaleres.com :fr:](https://tugaleres.com/2025/03/04/est-on-plus-efficace-en-utilisant-une-ia-type-chatgpt/).]]>
            </summary>
            <updated>2025-08-28T19:37:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1334</id>
            <title type="text"><![CDATA[Evolving Agents Framework]]></title>
            <link rel="alternate" href="https://github.com/matiasmolinas/evolving-agents" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1334"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Evolving agents is a production-grade environment for orchestrating, evolving, and managing AI agents.

A production-grade framework for creating, managing, and evolving AI agents with intelligent agent-to-agent communication. The framework enables you to build collaborative agent ecosystems that can semantically understand requirements, evolve based on past experiences, and communicate effectively to solve complex tasks.]]>
            </summary>
            <updated>2025-08-28T19:39:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1335</id>
            <title type="text"><![CDATA[Building an Agentic System]]></title>
            <link rel="alternate" href="https://gerred.github.io/building-an-agentic-system/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1335"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An in-depth book and reference on building agentic systems like Claude Code.
A deep-dive guide into architecture patterns for building responsive, reliable AI coding agents.

There&amp;#039;s been a lot of asking about how Claude Code works under the hood. Usually, people see the prompts, but they don&amp;#039;t see how it all comes together. This is that book. All of the systems, tools, and commands that go into building one of these.

A practical deep dive and code review into how to build a self-driving coding agent, execution engine, tools and commands. Rather than the prompts and AI engineering, this is the systems and design decisions that go into making agents that are real-time, self-corrective, and useful for productive work.

- [Building an Agentic System @ GitHub](https://github.com/gerred/building-an-agentic-system).]]>
            </summary>
            <updated>2025-08-28T19:39:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1337</id>
            <title type="text"><![CDATA[ANON KODE]]></title>
            <link rel="alternate" href="https://github.com/dnakov/anon-kode" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1337"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Terminal-based AI coding tool that can use any model that supports the OpenAI-style API.]]>
            </summary>
            <updated>2025-08-28T19:39:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1338</id>
            <title type="text"><![CDATA[Letta]]></title>
            <link rel="alternate" href="https://www.letta.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1338"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Platform for Building Stateful Agents.
Build agents with infinite context and human-like memory, that can learn from data and improve with experience.
 Letta (formerly MemGPT) is a framework for creating LLM services with memory. 

👾 Letta is an open source framework for building stateful LLM applications. You can use Letta to build stateful agents with advanced reasoning capabilities and transparent long-term memory. The Letta framework is white box and model-agnostic.

- [Letta @ GitHub](https://github.com/letta-ai/letta).
- [Letta documentation](https://docs.letta.com/).

Related contents:

- [Letta Filesystem @ Letta documentation](https://docs.letta.com/guides/agents/filesystem).]]>
            </summary>
            <updated>2025-10-17T05:38:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1342</id>
            <title type="text"><![CDATA[CAMEL-AI Framework]]></title>
            <link rel="alternate" href="https://camel-ai.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1342"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Finding the Scaling Laws of Agents. The first and the best multi-agent framework.

 🐫 CAMEL is an open-source community dedicated to finding the scaling laws of agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

The framework enables multi-agent systems to continuously evolve by generating data and interacting with environments. This evolution can be driven by reinforcement learning with verifiable rewards or supervised learning.

- [CAMEL-AI @ GitHub](https://github.com/camel-ai/camel).]]>
            </summary>
            <updated>2025-08-28T19:40:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1350</id>
            <title type="text"><![CDATA[OASIS]]></title>
            <link rel="alternate" href="https://github.com/psyray/oasis" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1350"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Ollama Automated Security Intelligence Scanner.

 🛡️ An AI-powered security auditing tool that leverages Ollama models to detect and analyze potential security vulnerabilities in your code.

Advanced code security analysis through the power of AI

Related contents:

- [OASIS - Sécurisez votre code avec l&amp;#039;IA et Ollama @ Korben :fr:](https://korben.info/oasis-outil-ia-securite-code-ollama.html).]]>
            </summary>
            <updated>2025-08-28T19:41:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1361</id>
            <title type="text"><![CDATA[Arch Gateway]]></title>
            <link rel="alternate" href="https://www.archgw.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1361"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Go beyond nascent AI demos. The intelligent AI-native gateway for prompts and agentic apps.

Effortlessly build AI apps that can answer questions and help users get things done. Arch is the AI-native proxy that handles the pesky heavy-lifting so that you can move faster in building agentic apps, prevent harmful outcomes, and rapidly incorporate latest models. 

 AI-native (edge and LLM) proxy for agents. Move faster by letting Arch handle the pesky heavy lifting in building agentic apps -- ⚡️ query understanding and routing, seamless integration of prompts with tools, and unified access and observability of LLMs. Built by the contributors of Envoy proxy. 

- [Arch Gateway @ GitHub](https://github.com/katanemo/archgw).]]>
            </summary>
            <updated>2025-08-28T19:43:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1362</id>
            <title type="text"><![CDATA[Nut]]></title>
            <link rel="alternate" href="https://nut.new/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1362"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt, run, edit, and deploy full-stack web applications using any LLM you want! 

Nut is an open source fork of Bolt.new for helping you develop full stack apps using AI. AI developers frequently struggle with fixing even simple bugs when they don&amp;#039;t know the cause, and get stuck making ineffective changes over and over. We want to crack these tough nuts, so to speak, so you can get back to building.

- [Nut @ GitHub](https://github.com/replayio/nut.new).]]>
            </summary>
            <updated>2025-08-28T19:43:13+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1364</id>
            <title type="text"><![CDATA[Opsy]]></title>
            <link rel="alternate" href="https://github.com/datolabs-io/opsy" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1364"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Opsy - Your AI-Powered SRE Colleague.

Opsy is an intelligent command-line assistant designed for Site Reliability Engineers (SREs), DevOps professionals, and platform engineers. It uses AI to help you navigate operational challenges, troubleshoot issues, and automate routine workflows. Opsy integrates with your existing tools and provides contextual assistance to make your daily operations more efficient.]]>
            </summary>
            <updated>2025-08-28T19:43:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1369</id>
            <title type="text"><![CDATA[agents.json]]></title>
            <link rel="alternate" href="https://docs.wild-card.ai/agentsjson/introduction" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1369"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The agents.json Specification is an open specification that formally describes contracts for API and agent interactions, built on top of the OpenAPI standard.

- [agents.json @ GitHub](https://github.com/wild-card-ai/agents-json).]]>
            </summary>
            <updated>2025-08-28T19:44:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1371</id>
            <title type="text"><![CDATA[⚔️ Chatbot Arena]]></title>
            <link rel="alternate" href="https://lmarena.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1371"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[⚔️ Chatbot Arena (formerly LMSYS): Free AI Chat to Compare &amp;amp; Test Best AI Chatbots.

Related contents:

- [Evals are not all you need @ Andrew Marble](https://www.marble.onl/posts/evals_are_not_all_you_need.html).]]>
            </summary>
            <updated>2025-08-28T19:45:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1372</id>
            <title type="text"><![CDATA[Ollama Function Caller (ofc)]]></title>
            <link rel="alternate" href="https://github.com/elijah-potter/ofc" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1372"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A command-line Ollama client for scripting.

The Ollama function caller, otherwise known as ofc, is a command-line tool for prompting Ollama models locally on your system. There are other programs out there that do similar things, but they either don&amp;#039;t support streaming or don&amp;#039;t give me access to important settings, like context length or temperature.]]>
            </summary>
            <updated>2025-08-28T19:45:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1375</id>
            <title type="text"><![CDATA[Plauna]]></title>
            <link rel="alternate" href="https://github.com/ozangulle/plauna" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1375"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Plauna is a privacy focused service that helps you categorize your e-mails. All of its data is stored only on your computer.

You can parse your e-mails from mbox files or directly by connecting to your IMAP servers. Plauna helps you categorize your e-mails and automates the process so that incoming e-mails are moved to their respective folders on your IMAP server.]]>
            </summary>
            <updated>2025-08-28T19:45:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1383</id>
            <title type="text"><![CDATA[open-playground]]></title>
            <link rel="alternate" href="https://github.com/prvnsmpth/open-playground" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1383"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM playground to experiment with local models and build fine-tuning datasets and benchmarks.

A playground that gives you full control over the contents of a chat conversation: add, remove and edit messages (system, user and assistant) and shape the flow of the conversation to be exactly what you need.]]>
            </summary>
            <updated>2025-08-28T19:47:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1397</id>
            <title type="text"><![CDATA[Windsurf AI IDE]]></title>
            <link rel="alternate" href="https://windsurfai.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1397"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Revolutionize Your Development with Windsurf AI IDE

As the first truly intelligent development environment, Codeium Windsurf AI combines powerful AI agents with intuitive co-pilots to create an unparalleled coding experience that adapts to your needs and enhances your productivity.

Related contents:

- [Windsurf: An Agentic IDE That Thinks and Codes With You @ The New Stack](https://thenewstack.io/windsurf-an-agentic-ide-that-thinks-and-codes-with-you/).]]>
            </summary>
            <updated>2025-08-28T19:49:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1402</id>
            <title type="text"><![CDATA[Orbit by Mozilla]]></title>
            <link rel="alternate" href="https://orbitbymozilla.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1402"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI you can trust

Easily summarize emails, docs, articles, and videos across the web — without sacrificing your privacy

Related contents:

- [Orbit - Résumez vos emails, documents, articles et vidéos sans sacrifier votre vie privée @ Korben :fr:](https://korben.info/orbit-resume-intelligent-mozilla-vie-privee.html).]]>
            </summary>
            <updated>2025-08-28T19:51:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1412</id>
            <title type="text"><![CDATA[CodeWeaver]]></title>
            <link rel="alternate" href="https://github.com/tesserato/CodeWeaver" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1412"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Generate a Markdown Document of Your Codebase Structure and Content.

CodeWeaver is a command-line tool designed to weave your codebase into a single, easy-to-navigate Markdown document. It recursively scans a directory, generating a structured representation of your project&amp;#039;s file hierarchy and embedding the content of each file within code blocks. This tool simplifies codebase sharing, documentation, and integration with AI/ML code analysis tools by providing a consolidated and readable Markdown output.]]>
            </summary>
            <updated>2025-08-28T19:51:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1422</id>
            <title type="text"><![CDATA[Spaces @ Hugging Face]]></title>
            <link rel="alternate" href="https://huggingface.co/spaces" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1422"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The AI App Directory.

Related contents:

- [\#106 - Les news web dev pour février 2025 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-feb25/).]]>
            </summary>
            <updated>2025-08-28T19:53:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1445</id>
            <title type="text"><![CDATA[AIBrix]]></title>
            <link rel="alternate" href="https://aibrix.github.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1445"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Cost-efficient and pluggable Infrastructure components for GenAI inference.
AIBrix is a open source cost-efficient, scalable and pluggable Infrastructure for GenAI applications.

AIBrix is an open-source initiative designed to provide essential building blocks to construct scalable GenAI inference infrastructure. AIBrix delivers a cloud-native solution optimized for deploying, managing, and scaling large language model (LLM) inference, tailored specifically to enterprise needs.

- [AIBrix @ GitHub](https://github.com/vllm-project/aibrix).
- [AIBrix @ Read the Docs](https://aibrix.readthedocs.io/latest/).]]>
            </summary>
            <updated>2025-08-28T19:57:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1460</id>
            <title type="text"><![CDATA[AntiSquat]]></title>
            <link rel="alternate" href="https://github.com/redhuntlabs/antisquat" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1460"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AntiSquat leverages AI techniques such as natural language processing (NLP), large language models (ChatGPT) and more to empower detection of typosquatting and phishing domains.

Related contents:

- [ 🚨🚨 AntiSquat : l’IA qui traque les faux sites avant qu’ils ne vous piégent ! 🚨🚨 @ Laurent Biagotti&amp;#039;s LinkedIn :fr:](https://www.linkedin.com/posts/laurent-biagiotti-19779284_cybersaezcuritaez-phishing-typosquatting-activity-7298965818971684864-Whqm/).]]>
            </summary>
            <updated>2025-08-28T19:59:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1471</id>
            <title type="text"><![CDATA[Gitingest]]></title>
            <link rel="alternate" href="https://gitingest.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1471"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn any Git repository into a simple text digest of its codebase.
Replace &amp;#039;hub&amp;#039; with &amp;#039;ingest&amp;#039; in any github url to get a prompt-friendly extract of a codebase.

This is useful for feeding a codebase into any LLM. 

- [Gitingest @ GitHub](https://github.com/cyclotruc/gitingest).

Related contents:

- [GitIngest - Transformez votre code en prompts pour LLM @ Korben :fr:](https://korben.info/gitingest-transformez-code-prompts-llm.html).]]>
            </summary>
            <updated>2025-08-28T20:01:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1480</id>
            <title type="text"><![CDATA[AI Engineering Landscape]]></title>
            <link rel="alternate" href="https://malywut.github.io/ai-engineering-landscape/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1480"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[curated list of resources for AI Engineering.

- [AI Engineering Landscape @ GitHub](https://github.com/malywut/ai-engineering-landscape).

Related contents:

- [The End of Programming as We Know It @ O&amp;#039;Reilly](https://www.oreilly.com/radar/the-end-of-programming-as-we-know-it/).]]>
            </summary>
            <updated>2025-08-28T20:03:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1481</id>
            <title type="text"><![CDATA[sketch.dev]]></title>
            <link rel="alternate" href="https://sketch.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1481"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Write Go, online, with LLMs.

sketch.dev is a new kind of Go playground that lets you write and run Go code in your browser, in a real editor. Build packages and modules, import dependencies, run tests, code with chat, and use a lightweight unix sandbox. 

Related contents:

- [Episode \#629: Programming with LLMs @ Changelog Interviews](https://changelog.com/podcast/629).]]>
            </summary>
            <updated>2025-08-28T20:03:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1505</id>
            <title type="text"><![CDATA[DeepEval]]></title>
            <link rel="alternate" href="https://docs.confident-ai.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1505"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Open-Source LLM Evaluation Framework.

DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that runs locally on your machine for evaluation.

- [DeepEval @ GitHub](https://github.com/confident-ai/deepeval).]]>
            </summary>
            <updated>2025-08-28T20:07:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1508</id>
            <title type="text"><![CDATA[GenSX]]></title>
            <link rel="alternate" href="https://www.gensx.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1508"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The TypeScript framework for agents &amp;amp; workflows with react-like components. Lightning fast dev loop. Easy to learn. Easy to extend. 

Build complex AI applications with React-like components.
GenSX is a simple typescript framework for building agents and workflows with reusable React-like components.
GenSX takes a lot of inspiration from React, but the programming model is very different - it’s a Node.js framework designed for data flow.

- [GenSX @ GitHub](https://github.com/gensx-inc/gensx).]]>
            </summary>
            <updated>2025-08-28T20:07:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1511</id>
            <title type="text"><![CDATA[Neon Core]]></title>
            <link rel="alternate" href="https://github.com/NeonGeckoCom/NeonCore" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1511"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Neon Core extends Mycroft core with more modular code, extended multi-user support, and more.

Neon AI is an open source voice assistant.]]>
            </summary>
            <updated>2025-08-28T20:08:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1512</id>
            <title type="text"><![CDATA[Open Voice OS]]></title>
            <link rel="alternate" href="https://www.openvoiceos.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1512"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🌟 OpenVoiceOS is an open-source platform for smart speakers and other voice-centric devices.

OpenVoiceOS is a community-driven, open-source voice AI platform for creating custom voice-controlled ​interfaces across devices with NLP, a customizable UI, and a focus on privacy and security.

- [Open Voice OS core @ GitHub](https://github.com/OpenVoiceOS/ovos-core).]]>
            </summary>
            <updated>2025-08-28T20:08:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1514</id>
            <title type="text"><![CDATA[Distributed Llama]]></title>
            <link rel="alternate" href="https://github.com/b4rtaz/distributed-llama" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1514"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Connect home devices into a powerful cluster to accelerate LLM inference. More devices mean faster performance, leveraging tensor parallelism and high-speed synchronization over Ethernet.

Supports Linux, macOS, and Windows. Optimized for ARM and x86_64 AVX2 CPUs.

Related contents:

- [L’Europe relance par centaines de milliards @ Tech Café :fr:](https://techcafe.fr/leurope-relance-par-centaines-de-milliards/).]]>
            </summary>
            <updated>2025-08-28T20:08:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1521</id>
            <title type="text"><![CDATA[R1 1776]]></title>
            <link rel="alternate" href="https://huggingface.co/perplexity-ai/r1-1776" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1521"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[R1 1776 is a DeepSeek-R1 reasoning model that has been post-trained by Perplexity AI to remove Chinese Communist Party censorship. The model provides unbiased, accurate, and factual information while maintaining high reasoning capabilities.

Related content:

- [Today we&amp;#039;re open-sourcing R1 1776, a version of the DeepSeek-R1 model that has been post-trained to provide unbiased, accurate, and factual information. Download the model weights on our HuggingFace Repo or consider using the model via our Sonar API. @ perplexity](https://www.perplexity.ai/fr/hub/blog/open-sourcing-r1-1776).]]>
            </summary>
            <updated>2025-08-28T20:09:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1538</id>
            <title type="text"><![CDATA[VimLM]]></title>
            <link rel="alternate" href="https://github.com/JosefAlbers/VimLM" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1538"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Local LLM-Powered Coding Assistant for Vim.

 VimLM is a Vim plugin that provides an LLM-powered assistant for code editing by allowing users to interact with a local LLM model through Vim commands and automatically ingesting code context.]]>
            </summary>
            <updated>2025-08-28T20:12:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1539</id>
            <title type="text"><![CDATA[Scira]]></title>
            <link rel="alternate" href="https://scira.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1539"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Scira (Formerly MiniPerplx) is a minimalistic AI-powered search engine that helps you find information on the internet. Powered by Vercel AI SDK! Search with models like Grok 2.0. 

- [Scira @ GitHub](https://github.com/zaidmukaddam/scira).]]>
            </summary>
            <updated>2025-08-28T20:12:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1555</id>
            <title type="text"><![CDATA[Sparrow]]></title>
            <link rel="alternate" href="https://sparrow.katanaml.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1555"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Data processing with ML, LLM and Vision LLM.

Sparrow is an innovative open-source solution for efficient data extraction and processing from various documents and images. It seamlessly handles forms, bank statements, invoices, receipts, and other unstructured data sources. Sparrow stands out with its modular architecture, offering independent services and pipelines all optimized for robust performance.

- [Sparrow @ GitHub](https://github.com/katanaml/sparrow).

Related contents:

- [Sparrow - Pour extraire des données avec l&amp;#039;IA @ Korben :fr:](https://korben.info/sparrow-outil-extraction-donnees-ia.html).]]>
            </summary>
            <updated>2025-08-28T20:15:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1558</id>
            <title type="text"><![CDATA[talkflow-n8n]]></title>
            <link rel="alternate" href="https://github.com/jimmartinquisitive/talkflow-n8n" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1558"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A real-time chat application integrated with N8N workflows for automated responses and processing.]]>
            </summary>
            <updated>2025-08-28T20:15:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1559</id>
            <title type="text"><![CDATA[UglyFeed]]></title>
            <link rel="alternate" href="https://github.com/fabriziosalmi/UglyFeed" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1559"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Retrieve, aggregate, filter, evaluate, rewrite and serve RSS feeds using Large Language Models for fun, research and learning purposes.

UglyFeed is a simple application designed to retrieve, aggregate, filter, rewrite, evaluate and serve content (RSS feeds) written by a large language model.]]>
            </summary>
            <updated>2025-08-28T20:16:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1578</id>
            <title type="text"><![CDATA[Data Formulator]]></title>
            <link rel="alternate" href="https://github.com/microsoft/data-formulator" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1578"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🪄 Create rich visualizations with AI

Data Formulator is an application from Microsoft Research that uses large language models to transform data, expediting the practice of data visualization.

Data Formulator is an AI-powered tool for analysts to iteratively create rich visualizations. Unlike most chat-based AI tools where users need to describe everything in natural language, Data Formulator combines user interface interactions (UI) and natural language (NL) inputs for easier interaction. This blended approach makes it easier for users to describe their chart designs while delegating data transformation to AI.]]>
            </summary>
            <updated>2025-09-04T09:35:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1584</id>
            <title type="text"><![CDATA[SillyTavern]]></title>
            <link rel="alternate" href="https://sillytavern.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1584"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM Frontend for Power Users.

SillyTavern provides a single unified interface for many LLM APIs (KoboldAI/CPP, Horde, NovelAI, Ooba, Tabby, OpenAI, OpenRouter, Claude, Mistral and more), a mobile-friendly layout, Visual Novel Mode, Automatic1111 &amp;amp; ComfyUI API image generation integration, TTS, WorldInfo (lorebooks), customizable UI, auto-translate, more prompt options than you&amp;#039;d ever want or need, and endless growth potential via third-party extensions.

- [SillyTavern @ GitHub](https://github.com/SillyTavern/SillyTavern).]]>
            </summary>
            <updated>2025-08-28T20:20:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1585</id>
            <title type="text"><![CDATA[Novelcrafter]]></title>
            <link rel="alternate" href="https://www.novelcrafter.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1585"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Novel Writing Toolbox. Write, without restriction.

Novelcrafter&amp;#039;s got your back, arming you with the tools you need to dream, draft, and deliver your story.]]>
            </summary>
            <updated>2025-08-28T20:20:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1590</id>
            <title type="text"><![CDATA[smolmodels ✨]]></title>
            <link rel="alternate" href="https://github.com/plexe-ai/smolmodels" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1590"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[build ml models in natural language and minimal code.

Create machine learning models with minimal code by describing what you want them to do in plain words. You explain the task, and the library builds a model for you, including data generation, feature engineering, training, and packaging.]]>
            </summary>
            <updated>2025-08-28T20:21:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1602</id>
            <title type="text"><![CDATA[open Deep Research]]></title>
            <link rel="alternate" href="https://m-ric-open-deep-research.hf.space/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1602"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[OpenAI just published Deep Research, a very nice assistant that can perform deep searches on the web to answer user questions.

However, their agent has a huge downside: it&amp;#039;s not open. So we&amp;#039;ve started a 24-hour rush to replicate and open-source it. Our resulting open-Deep-Research agent took the #1 rank of any open submission on the GAIA leaderboard! ✨

- [open Deep Research @ HuggingFace smolagents&amp;#039; GitHub](https://github.com/huggingface/smolagents/tree/main/examples/open_deep_research).

Related contents:

- [Open-source DeepResearch – Freeing our search agents @ Hugging Face](https://huggingface.co/blog/open-deep-research).]]>
            </summary>
            <updated>2025-08-28T20:23:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1606</id>
            <title type="text"><![CDATA[Open LLM Lists]]></title>
            <link rel="alternate" href="https://openllmlist.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1606"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Trending Open AI Models.]]>
            </summary>
            <updated>2025-08-28T20:23:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1611</id>
            <title type="text"><![CDATA[Modern-Day Oracles or Bullshit Machines ?]]></title>
            <link rel="alternate" href="https://thebullshitmachines.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1611"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[For better or for worse, LLMs are here to stay. We all read content that they produce online, most of us interact with LLM chatbots, and many of us use them to produce content of our own.

In a series of five- to ten-minute lessons, we will explain what these machines are, how they work, and how to thrive in a world where they are everywhere.

You will learn when these systems can save you a lot of time and effort. You will learn when they are likely to steer you wrong. And you will discover how to see through the hype to tell the difference. ?]]>
            </summary>
            <updated>2025-08-28T20:24:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1665</id>
            <title type="text"><![CDATA[LiteLLM]]></title>
            <link rel="alternate" href="https://www.litellm.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1665"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM Gateway to provide model access, logging and usage tracking across 100+ LLMs. All in the OpenAI format.

- [LiteLLM @ GitHub](https://github.com/BerriAI/litellm).

Related contents:

- [You need more than a vector database @ Redis](https://redis.io/blog/you-need-more-than-a-vector-database/).
- [À la découverte de liteLLM, une plateforme pour les gouverner tous @ Arneo&amp;#039;s YouTube :fr:](https://www.youtube.com/watch?v=L8CeGZ0Pf5o).
- [TeamPCP supply chain attack spreads to PyPI @ Reversing Labs](https://www.reversinglabs.com/blog/teampcp-supply-chain-attack-spreads).
- [How a Poisoned Security Scanner Became the Key to Backdooring LiteLLM @ snyk](https://snyk.io/fr/articles/poisoned-security-scanner-backdooring-litellm/).
- [Building a Kubernetes-native pattern for AI infrastructure at scale @ The New Stack](https://thenewstack.io/kubernetes-native-ai-infrastructure/).
- [My minute-by-minute response to the LiteLLM malware attack @ futuresearch](https://futuresearch.ai/blog/litellm-attack-transcript/).
- [A popular Python library just became a backdoor to your entire machine @ XDA](https://www.xda-developers.com/popular-python-library-backdoor-machine/).
- [LLMs on Kubernetes Part 1: Understanding the threat model @ CNCF](https://www.cncf.io/blog/2026/03/30/llms-on-kubernetes-part-1-understanding-the-threat-model/).]]>
            </summary>
            <updated>2026-04-07T05:46:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1666</id>
            <title type="text"><![CDATA[Cohere]]></title>
            <link rel="alternate" href="https://cohere.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1666"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The World&amp;#039;s Leading AI Platform for Enterprise.
The all-in-one platform for private and secure AI.

Cohere brings you cutting-edge multilingual models, advanced retrieval, and an AI workspace tailored for the modern enterprise — all within a single, secure platform.

Related contents:

- [You need more than a vector database @ Redis](https://redis.io/blog/you-need-more-than-a-vector-database/).]]>
            </summary>
            <updated>2025-08-28T20:33:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1671</id>
            <title type="text"><![CDATA[llama.cpp]]></title>
            <link rel="alternate" href="https://llama.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1671"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM inference in C/C++.

The main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware - locally and in the cloud.

- [llama.cpp @ GitHUb](https://github.com/ggml-org/llama.cpp).

Related contents:

- [Everything I&amp;#039;ve learned so far about running local LLMs @ null program](https://nullprogram.com/blog/2024/11/10/).
- [Run large and small language models with llama.cpp (DeepSeek-R1, Phi-4) @ Modal  Docs](https://modal.com/docs/examples/llama_cpp).
- [Faire tourner un LLM localement sur votre ordinateur @ Quoi de neuf les devs ? :fr:](https://happytodev.substack.com/p/brent-roose-est-linvite-du-n147-de?open=false#%C2%A7faire-tourner-un-llm-localement-sur-votre-ordinateur).
- [Optimizing Performance with llama.cpp @ Home Assistant community](https://community.home-assistant.io/t/my-journey-to-a-reliable-and-enjoyable-locally-hosted-voice-assistant/944860/123).
- [Grand saut dans le déploiement sur site d&amp;#039;un serveur LLM à moindres privilèges @ Synacktiv :fr:](https://www.synacktiv.com/publications/grand-saut-dans-le-deploiement-sur-site-dun-serveur-llm-a-moindres-privileges).
- [INSTALLER llama.cpp SUR LINUX POUR DE L&amp;#039;IA EN LOCAL (INFÉRENCE) @ Adrien Linuxtricks&amp;#039; YouTube :fr:](https://www.youtube.com/watch?v=NFB-c7CoGm4).]]>
            </summary>
            <updated>2026-07-15T06:52:55+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1672</id>
            <title type="text"><![CDATA[bragdoc.ai]]></title>
            <link rel="alternate" href="https://www.bragdoc.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1672"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Never Forget Your Achievements.
Get recognized for all your hard work.

Bragdoc helps you get recognized for your hard work by tracking your achievements and creating beautiful documents to share with your boss.]]>
            </summary>
            <updated>2025-08-28T20:35:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1677</id>
            <title type="text"><![CDATA[How To Scale Your Model]]></title>
            <link rel="alternate" href="https://jax-ml.github.io/scaling-book/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1677"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Systems View of LLMs on TPUs.

This book aims to demystify the art of scaling LLMs on TPUs. We try to explain how TPUs work, how LLMs actually run at scale, and how to pick parallelism schemes during training and inference that avoid communication bottlenecks.

- [How To Scale Your Model @ GitHub](https://github.com/jax-ml/scaling-book/).]]>
            </summary>
            <updated>2025-08-28T20:35:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1679</id>
            <title type="text"><![CDATA[KitOps]]></title>
            <link rel="alternate" href="https://kitops.ml/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1679"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Simple, secure, and reproducible packaging for AI/ML projects.

 KitOps is an open source DevOps tool that packages and versions your AI/ML model, datasets, code, and configuration into a reproducible artifact called a ModelKit. ModelKits are built on existing standards, ensuring compatibility with the tools your data scientists and developers already use. 

- [KitOps @ GitHub](https://github.com/jozu-ai/kitops).]]>
            </summary>
            <updated>2025-08-28T20:35:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1683</id>
            <title type="text"><![CDATA[RunPod]]></title>
            <link rel="alternate" href="https://www.runpod.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1683"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Cloud Built for AI.

Train, fine-tune and deploy AI models with RunPod.

Globally distributed GPU cloud for your AI workloads.
Deploy any GPU workload seamlessly, so you can focus less on
infrastructure and more on running ML models.]]>
            </summary>
            <updated>2025-08-28T20:36:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1684</id>
            <title type="text"><![CDATA[Vast.ai]]></title>
            <link rel="alternate" href="https://vast.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1684"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Rent GPUs.

Vast.ai is the market leader in low-cost cloud GPU rental.
Use one simple interface to save 5-6X on GPU compute.]]>
            </summary>
            <updated>2025-08-28T20:36:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1693</id>
            <title type="text"><![CDATA[promptfoo]]></title>
            <link rel="alternate" href="https://www.promptfoo.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1693"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Secure &amp;amp; reliable LLMs.
Test &amp;amp; secure your LLM apps.
Open-source LLM testing used by 51,000+ developers.

 Test your prompts, agents, and RAGs. Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration. 

- [promptfoo @ GitHub](https://github.com/promptfoo/promptfoo).

Related contents:

- [L’IA Deepseek censurée à propos de la Chine ? @ Choses à Savoir TECH :fr:](https://shows.acast.com/choses-a-savoir-technologie/episodes/lia-deepseek-censuree-a-propos-de-la-chine).
- [Promptfoo - Fini le doigt mouillé pour tester vos LLM @ Korben :fr:](https://korben.info/promptfoo-tester-evaluer-llm.html).]]>
            </summary>
            <updated>2026-03-23T15:24:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1698</id>
            <title type="text"><![CDATA[Oumi]]></title>
            <link rel="alternate" href="https://oumi.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1698"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Universal Machine Intellingence.
E2E Foundation Model Research Platform.
Everything you need to build state-of-the-art foundation models, end-to-end. 

Oumi is a fully open-source platform that streamlines the entire lifecycle of foundation models - from data preparation and training to evaluation and deployment. Whether you&amp;#039;re developing on a laptop, launching large scale experiments on a cluster, or deploying models in production, Oumi provides the tools and workflows you need.

- [Oumi @ GitHub](https://github.com/oumi-ai/oumi).]]>
            </summary>
            <updated>2025-08-28T20:39:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1701</id>
            <title type="text"><![CDATA[(WIP) A Little Bit of Reinforcement Learning from Human Feedback]]></title>
            <link rel="alternate" href="https://rlhfbook.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1701"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A short introduction to RLHF and post-training focused on language models.]]>
            </summary>
            <updated>2025-08-28T20:39:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1704</id>
            <title type="text"><![CDATA[Page Assist]]></title>
            <link rel="alternate" href="https://github.com/n4ze3m/page-assist" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1704"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Use your locally running AI models to assist you in your web browsing.

Page Assist is an open-source browser extension that provides a sidebar and web UI for your local AI model. It allows you to interact with your model from any webpage.]]>
            </summary>
            <updated>2025-08-28T20:39:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1707</id>
            <title type="text"><![CDATA[Leon]]></title>
            <link rel="alternate" href="https://getleon.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1707"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Open-Source Personal Assistant.

Leon is your open-source personal assistant who can live on your server.
He does stuff when you ask him to.

- [Leon @ GitHub](https://github.com/leon-ai/leon).]]>
            </summary>
            <updated>2025-08-28T20:40:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1708</id>
            <title type="text"><![CDATA[Browser Use]]></title>
            <link rel="alternate" href="https://browser-use.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1708"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Enable AI to control your browser. Make websites accessible for AI agents.

We make websites accessible for AI agents by extracting all interactive elements, so agents can focus on what makes their beer taste better.

- [Browser Use @ GitHub](https://github.com/browser-use/browser-use).

Related contents:

- [Browser Use, one of the tools powering Manus, is also going viral @ TechCrunch](https://techcrunch.com/2025/03/12/browser-use-one-of-the-tools-powering-manus-is-also-going-viral/).
- [Episode 616: From Boston to bootc @ Linux Unplugged](https://linuxunplugged.com/616).]]>
            </summary>
            <updated>2026-03-28T08:18:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1729</id>
            <title type="text"><![CDATA[Langfuse]]></title>
            <link rel="alternate" href="https://langfuse.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1729"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source LLM Engineering Platform.
Traces, evals, prompt management and metrics to debug and improve your LLM application.

🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23 

- [Langfuse @ GitHub](https://github.com/langfuse/langfuse).

Related contents:

- [Self-hosting Langfuse with Kubernetes @ Xebia](https://xebia.com/blog/setting-up-local-langfuse-server/).]]>
            </summary>
            <updated>2025-08-28T20:43:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1730</id>
            <title type="text"><![CDATA[Agenta]]></title>
            <link rel="alternate" href="https://agenta.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1730"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt Engineering, Evaluation, and Observability for LLM apps.

Your End-to-End Collaborative Open Source End-to-End LLM Engineering Platform.
Agenta provides integrated tools for prompt engineering, versioning, evaluation, and observability—all in one place.

The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM Observability all in one place. 

- [Agenta @ GitHub](https://github.com/agenta-ai/agenta).]]>
            </summary>
            <updated>2025-08-28T20:44:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1732</id>
            <title type="text"><![CDATA[PromptPal]]></title>
            <link rel="alternate" href="https://promptpal.github.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1732"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Prompt Manager that focuses on On-Premise and developer experience.

- [PromptPal @ GitHub](https://github.com/PromptPal/PromptPal).]]>
            </summary>
            <updated>2025-08-28T20:44:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1733</id>
            <title type="text"><![CDATA[Embedditor]]></title>
            <link rel="alternate" href="https://embedditor.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1733"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Embedditor is the open-source MS Word equivalent for embedding that helps you get the most out of your vector search.

⚡ GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team. 

- [Embedditor @ GitHub](https://github.com/IngestAI/Embedditor).]]>
            </summary>
            <updated>2025-08-28T20:44:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1748</id>
            <title type="text"><![CDATA[🦜🕸️LangGraph]]></title>
            <link rel="alternate" href="https://langchain-ai.github.io/langgraph/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1748"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows.

- [🦜🕸️LangGraph @ GitHub](https://github.com/langchain-ai/langgraph).

Related contents:

- [Building effective agents @ Anthropic](https://www.anthropic.com/research/building-effective-agents).]]>
            </summary>
            <updated>2025-08-28T20:47:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1749</id>
            <title type="text"><![CDATA[Vellum AI]]></title>
            <link rel="alternate" href="https://www.vellum.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1749"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build and ship AI products on a single, collaborative platform

Take AI products from early-stage ideas to production-grade features with tooling for experimentation, evaluation, deployment, monitoring, and collaboration.

Related contents:

- [Building effective agents @ Anthropic](https://www.anthropic.com/research/building-effective-agents).]]>
            </summary>
            <updated>2025-08-28T20:47:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1750</id>
            <title type="text"><![CDATA[Rivet]]></title>
            <link rel="alternate" href="https://rivet.ironcladapp.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1750"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The open-source visual AI programming environment and TypeScript library.

Rivet, the IDE for creating complex AI agents and prompt chaining, and embedding it in your application. 

- [Rivet @ GitHub](https://github.com/Ironclad/rivet).

Related contents:

- [Building effective agents @ Anthropic](https://www.anthropic.com/research/building-effective-agents).]]>
            </summary>
            <updated>2025-08-28T20:47:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1751</id>
            <title type="text"><![CDATA[Amazon Bedrock Agents]]></title>
            <link rel="alternate" href="https://aws.amazon.com/bedrock/agents/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1751"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Enable generative AI applications to automate multistep tasks by seamlessly connecting with company systems, APIs, and data sources.

Related contents:

- [Building effective agents @ Anthropic](https://www.anthropic.com/research/building-effective-agents).]]>
            </summary>
            <updated>2025-08-28T20:47:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1759</id>
            <title type="text"><![CDATA[codename goose]]></title>
            <link rel="alternate" href="https://block.github.io/goose/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1759"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your on-machine AI agent, automating engineering tasks seamlessly.
an open-source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM.

- [codename goose @ GitHub](https://github.com/block/goose).

Related contents:

- [Introducing codename goose @ codename goose blog](https://block.github.io/goose/blog/2025/01/28/introducing-codename-goose/).]]>
            </summary>
            <updated>2025-08-28T20:49:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1766</id>
            <title type="text"><![CDATA[Laravel Faker OpenAI Provider]]></title>
            <link rel="alternate" href="https://github.com/jpcaparas/laravel-faker-openai" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1766"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An opinionated Laravel package that extends FakerPHP and uses openai-php/laravel to generate fake data.

A Laravel package that extends FakerPHP by adding an AI-powered data generator using OpenAI. This allows you to generate more realistic and context-aware fake data in your Laravel applications.

Related contents:

- [105 - les news web dev pour janvier 2025 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-janv25/).
- [Laravel Faker OpenAI @ Laravel News](https://laravel-news.com/laravel-faker-openai).]]>
            </summary>
            <updated>2025-08-28T20:51:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1769</id>
            <title type="text"><![CDATA[Cerebras]]></title>
            <link rel="alternate" href="https://cerebras.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1769"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Cerebras Inference
The world’s fastest inference -70x faster than GPU clouds,128K context, 16-bit precision.

Cerebras Inference Llama 3.3 70B runs at 2,200 tokens/s and Llama 3.1 405B at 969 tokens/s – over 70x faster than GPU clouds. Get instant responses to code-gen, summarization, and agentic tasks.

Related contents:

- [105 - les news web dev pour janvier 2025 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-janv25/).]]>
            </summary>
            <updated>2025-08-28T20:51:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1771</id>
            <title type="text"><![CDATA[GenAi France :fr:]]></title>
            <link rel="alternate" href="https://www.generativeai.paris/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1771"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Conférences sur la générative AI.

Related contents:

- [\#307.src - Langchain: Faire de l&amp;#039;IA comme des Lego avec Maxime Thoonsen @ &amp;lt;ifttd&amp;gt;](https://www.ifttd.io/episodes/langchain).]]>
            </summary>
            <updated>2025-08-28T20:51:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1779</id>
            <title type="text"><![CDATA[Haystack]]></title>
            <link rel="alternate" href="https://haystack.deepset.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1779"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Production-Ready Open Source AI Framework.

 AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it&amp;#039;s best suited for building RAG, question answering, semantic search or conversational agent chatbots. 

- [Haystack @ GitHub](https://github.com/deepset-ai/haystack).]]>
            </summary>
            <updated>2025-08-28T20:52:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1780</id>
            <title type="text"><![CDATA[OpenLIT]]></title>
            <link rel="alternate" href="https://openlit.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1780"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[OpenTelemetry-native GenAI and LLM Application Observability.

 Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers, VectorDBs, Agent Frameworks and GPUs. 

- [OpenLIT @ GitHub](https://github.com/openlit/openlit).

Related contents:

- [Monitor Model Context Protocol (MCP) servers with OpenLIT and Grafana Cloud  @ Grafana Labs&amp;#039; Blog](https://grafana.com/blog/ai-observability-MCP-servers/).]]>
            </summary>
            <updated>2026-03-23T14:57:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1781</id>
            <title type="text"><![CDATA[OpenLLMetry]]></title>
            <link rel="alternate" href="https://www.traceloop.com/openllmetry" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1781"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source observability for your LLM application, based on OpenTelemetry.

OpenLLMetry is a set of extensions built on top of OpenTelemetry that gives you complete observability over your LLM application. Because it uses OpenTelemetry under the hood, it can be connected to your existing observability solutions - Datadog, Honeycomb, and others.

- [OpenLLMetry @ GitHub](https://github.com/traceloop/openllmetry).]]>
            </summary>
            <updated>2025-08-28T20:52:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1784</id>
            <title type="text"><![CDATA[ONNX Runtime]]></title>
            <link rel="alternate" href="https://onnxruntime.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1784"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator.

ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. 

- [ONNX Runtime @ GitHub](https://github.com/microsoft/onnxruntime).

Related contents:

- [Running inference in web extensions @ dist://ed](https://blog.mozilla.org/en/mozilla/ai/ai-tech/running-inference-in-web-extensions/).]]>
            </summary>
            <updated>2025-08-28T20:53:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1785</id>
            <title type="text"><![CDATA[PocketPal AI 📱🚀]]></title>
            <link rel="alternate" href="https://github.com/a-ghorbani/pocketpal-ai" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1785"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An app that brings language models directly to your phone. 

PocketPal AI is a pocket-sized AI assistant powered by small language models (SLMs) that run directly on your phone. Designed for both iOS and Android, PocketPal AI lets you interact with various SLMs without the need for an internet connection.

Related contents:

- [PocketPal AI, l&amp;#039;assistant IA 100% local sur Android / iOS @ Korben :fr:](https://korben.info/pocketpal-ai-assistant-ia-local-smartphone.html).]]>
            </summary>
            <updated>2025-08-28T20:53:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1786</id>
            <title type="text"><![CDATA[Onlook]]></title>
            <link rel="alternate" href="https://onlook.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1786"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Cursor for Designers.

The power of Cursor for your own React website.
Onlook lets you visually edit your React website and 
write your changes back to code in real-time.

The open source Cursor for Designers. Design directly in your live React app and publish your changes to code. 

- [Onlook @ GitHub](https://github.com/onlook-dev/onlook).]]>
            </summary>
            <updated>2025-08-28T20:53:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1816</id>
            <title type="text"><![CDATA[Orange intelligence]]></title>
            <link rel="alternate" href="https://github.com/sharingan-no-kakashi/orange-intelligence" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1816"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Orange Intelligence is a powerful, fully customizable productivity tool for macOS. With its elegant floating window interface, you can capture, process, and replace text seamlessly across any application. Whether you&amp;#039;re running basic text processing, leveraging the power of large language models (LLMs) like OpenAI or local LLaMA, or creating complex agent systems, Orange Intelligence empowers you to work smarter, faster, and better.

Apple Intelligence is closed, limited, and inflexible. Orange Intelligence brings the power of customization and open source innovation to macOS, making it the perfect productivity tool for developers, researchers, and AI enthusiasts.]]>
            </summary>
            <updated>2025-08-28T20:59:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1834</id>
            <title type="text"><![CDATA[vLLM]]></title>
            <link rel="alternate" href="https://vllm.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1834"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Easy, fast, and cheap LLM serving for everyone.

vLLM is a fast and easy-to-use library for LLM inference and serving.

Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evloved into a community-driven project with contributions from both academia and industry.

- [vLLM @ GitHub](https://github.com/vllm-project/vllm).

Related contents:

- [How to serve LLMs with vLLM and OVHcloud AI Deploy @ OVHcloud](https://blog.ovhcloud.com/how-to-serve-llms-with-vllm-and-ovhcloud-ai-deploy/).
- [Episode 616: From Boston to bootc @ Linux Unplugged](https://linuxunplugged.com/616).
- [What is vLLM @ RedHat](https://www.redhat.com/en/topics/ai/what-is-vllm).
- [Faire tourner un LLM localement sur votre ordinateur @ Quoi de neuf les devs ? :fr:](https://happytodev.substack.com/p/brent-roose-est-linvite-du-n147-de?open=false#%C2%A7faire-tourner-un-llm-localement-sur-votre-ordinateur).
- [Inside vLLM: Anatomy of a High-Throughput LLM Inference System @ Aleksa Gordić blog](https://www.aleksagordic.com/blog/vllm).
- [vLLM : Maîtriser l&amp;#039;Inference Haute Performance pour les LLM @ DevSecOps :fr:](https://blog.stephane-robert.info/docs/developper/programmation/python/vllm/).
- [Docker Model Runner now supports vLLM on Windows @ Docker](https://www.docker.com/blog/docker-model-runner-vllm-windows/).
- [Running a self-hosted LLM in Kubernetes with vLLM @ CNCF](https://www.cncf.io/blog/2026/07/16/running-a-self-hosted-llm-in-kubernetes-with-vllm/).]]>
            </summary>
            <updated>2026-07-21T06:33:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1835</id>
            <title type="text"><![CDATA[Common Crawl]]></title>
            <link rel="alternate" href="https://commoncrawl.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1835"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Repository of Web Crawl Data.

Common Crawl maintains a free, open repository of web crawl data that can be used by anyone.

Related contents:

- [S5E7 - Sommes-nous à l&amp;#039;aube d&amp;#039;un effondrement des IA ? @ Underscore_&amp;#039;s acast :fr:](https://shows.acast.com/micode-underscore/episodes/s5e7-sommes-nous-a-laube-dun-effondrement-des-ia).]]>
            </summary>
            <updated>2025-08-28T21:01:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1836</id>
            <title type="text"><![CDATA[FineWeb]]></title>
            <link rel="alternate" href="https://huggingface.co/datasets/HuggingFaceFW/fineweb" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1836"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[15 trillion tokens of the finest data the 🌐 web has to offer.

The 🍷 FineWeb dataset consists of more than 15T tokens of cleaned and deduplicated english web data from CommonCrawl. The data processing pipeline is optimized for LLM performance and ran on the 🏭 datatrove library, our large scale data processing library.

🍷 FineWeb was originally meant to be a fully open replication of 🦅 RefinedWeb, with a release of the full dataset under the ODC-By 1.0 license. However, by carefully adding additional filtering steps, we managed to push the performance of 🍷 FineWeb well above that of the original 🦅 RefinedWeb, and models trained on our dataset also outperform models trained on other commonly used high quality web datasets (like C4, Dolma-v1.6, The Pile, SlimPajama, RedPajam2) on our aggregate group of benchmark tasks.

Related contents:

- [🍷 FineWeb: decanting the web for the finest text data at scale @ HugginFace](https://huggingface.co/spaces/HuggingFaceFW/blogpost-fineweb-v1).
- [S5E7 - Sommes-nous à l&amp;#039;aube d&amp;#039;un effondrement des IA ? @ Underscore_&amp;#039;s acast :fr:](https://shows.acast.com/micode-underscore/episodes/s5e7-sommes-nous-a-laube-dun-effondrement-des-ia).]]>
            </summary>
            <updated>2025-08-28T21:01:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1846</id>
            <title type="text"><![CDATA[NeurIPS Conference]]></title>
            <link rel="alternate" href="https://neurips.cc/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1846"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Annual Conference on Neural Information Processing Systems.

Related content:

- [S5E6 - On reçoit le PDG de Mistral, Arthur Mensch @ Underscore_&amp;#039;s acast :fr:](https://shows.acast.com/micode-underscore/episodes/s5e6-on-recoit-le-pdg-de-mistral-arthur-mensch).]]>
            </summary>
            <updated>2025-08-28T21:04:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1849</id>
            <title type="text"><![CDATA[DataBridge]]></title>
            <link rel="alternate" href="https://databridge.gitbook.io/databridge-docs" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1849"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Multi-modal modular data ingestion and retrieval.

DataBridge is an open source library for natural language search and management of multi-modal data. Get started by installing databridge now!

DataBridge is a powerful document processing and retrieval system designed for building intelligent document-based applications. It provides a robust foundation for semantic search, document processing, and AI-powered document interactions.]]>
            </summary>
            <updated>2025-08-28T21:04:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1862</id>
            <title type="text"><![CDATA[BrowserAI]]></title>
            <link rel="alternate" href="https://github.com/sauravpanda/BrowserAI" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1862"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run local LLMs inside your browser.]]>
            </summary>
            <updated>2025-08-28T21:07:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1875</id>
            <title type="text"><![CDATA[Replicate]]></title>
            <link rel="alternate" href="https://replicate.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1875"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run AI with an API.
Run and fine-tune open-source models. Deploy custom models at scale. All with one line of code.

Thousands of models contributed by our community.
All the latest open-source models are on Replicate.
They’re not just demos — they all actually work and have production-ready APIs.

AI shouldn’t be locked up inside academic papers and demos. Make it real by pushing it to Replicate.

Related contents:

- [\#104 Développer des projets IA - introduction @ Double Slash :fr:](https://double-slash.dev/podcasts/devia1-1/).]]>
            </summary>
            <updated>2025-08-28T21:09:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1880</id>
            <title type="text"><![CDATA[Repomix]]></title>
            <link rel="alternate" href="https://repomix.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1880"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Pack your codebase into AI-friendly formats.

 📦 Repomix (formerly Repopack) is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, and Gemini. 

- [Repomix @ GitHub](https://github.com/yamadashy/repomix).]]>
            </summary>
            <updated>2025-08-28T21:09:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1883</id>
            <title type="text"><![CDATA[Groq]]></title>
            <link rel="alternate" href="https://groq.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1883"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Groq is Fast AI Inference.

Related contents:

- [\#104 Développer des projets IA - introduction @ Double Slash :fr:](https://double-slash.dev/podcasts/devia1-1/).]]>
            </summary>
            <updated>2025-08-28T21:09:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1884</id>
            <title type="text"><![CDATA[LM Studio]]></title>
            <link rel="alternate" href="https://lmstudio.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1884"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Discover, download, and run local LLMs.

- [LM Studio @ GitHub](https://github.com/lmstudio-ai).

Related contents:

- [\#104 Développer des projets IA - introduction @ Double Slash :fr:](https://double-slash.dev/podcasts/devia1-1/).
- [Faire tourner un LLM localement sur votre ordinateur @ Quoi de neuf les devs ? :fr:](https://happytodev.substack.com/p/brent-roose-est-linvite-du-n147-de?open=false#%C2%A7faire-tourner-un-llm-localement-sur-votre-ordinateur).
- [Drames et dramas d’août @ Le RDV Tech podcast](https://frenchspin.fr/2025/08/drames-et-dramas-daout-rdv-tech/).
- [LM Studio : Faire tourner son IA (LLM) facilement (Chat, Developpement, ...) @ Adrien Linuxtricks&amp;#039; YouTube :fr:](https://www.youtube.com/watch?v=FFEzgPG1AZM).]]>
            </summary>
            <updated>2025-10-21T06:18:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1890</id>
            <title type="text"><![CDATA[DeepSeek-R1]]></title>
            <link rel="alternate" href="https://github.com/deepseek-ai/DeepSeek-R1" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1890"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step, demonstrated remarkable performance on reasoning. With RL, DeepSeek-R1-Zero naturally emerged with numerous powerful and interesting reasoning behaviors. However, DeepSeek-R1-Zero encounters challenges such as endless repetition, poor readability, and language mixing. To address these issues and further enhance reasoning performance, we introduce DeepSeek-R1, which incorporates cold-start data before RL.

Related contents:

- [DeepSeek Crushes OpenAI o1 with an MIT-Licensed Model—Developers Are Losing It @ AIM](https://analyticsindiamag.com/ai-news-updates/deepseek-crushes-openai-o1-with-an-mit-licensed-model-developers-are-losing-it/).]]>
            </summary>
            <updated>2025-08-28T21:12:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1897</id>
            <title type="text"><![CDATA[yek]]></title>
            <link rel="alternate" href="https://github.com/bodo-run/yek" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1897"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A fast tool to read text-based files in a repository or directory, chunk them, and serialize them for LLM consumption.]]>
            </summary>
            <updated>2025-08-28T21:12:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1898</id>
            <title type="text"><![CDATA[Agent Recipes]]></title>
            <link rel="alternate" href="https://www.agentrecipes.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1898"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Explore Agent Recipes

Explore common agent recipes with ready to copy code to improve your LLM applications. 

Related contents:

- [Building effective agents @ Anthropic](https://www.anthropic.com/research/building-effective-agents).]]>
            </summary>
            <updated>2025-08-28T21:13:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1927</id>
            <title type="text"><![CDATA[Realtime API Agents Demo]]></title>
            <link rel="alternate" href="https://github.com/openai/openai-realtime-agents" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1927"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[This is a simple demonstration of more advanced, agentic patterns built on top of the Realtime API. - openai/openai-realtime-agents]]>
            </summary>
            <updated>2025-08-28T21:17:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1938</id>
            <title type="text"><![CDATA[Rowfill]]></title>
            <link rel="alternate" href="https://www.rowfill.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1938"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source document processing platform built for knowledge workers.

Rowfill helps extract, analyze, and process data from complex documents, images, PDFs and more with advanced AI capabilities.

- [Rowfill @ GitHub](https://github.com/harishdeivanayagam/rowfill).]]>
            </summary>
            <updated>2025-08-28T21:20:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1950</id>
            <title type="text"><![CDATA[structured-logprobs]]></title>
            <link rel="alternate" href="https://arena-ai.github.io/structured-logprobs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1950"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[structured-logprobs is an open-source Python library that enhances OpenAI&amp;#039;s structured outputs by providing detailed information about token log probabilities.

This library is designed to offer valuable insights into the reliability of an LLM&amp;#039;s structured outputs. It works with OpenAI&amp;#039;s Structured Outputs, a feature that ensures the model consistently generates responses adhering to a supplied JSON Schema. This eliminates concerns about missing required keys or hallucinating invalid values.

- [structured-logprobs @ GitHub](https://github.com/arena-ai/structured-logprobs).]]>
            </summary>
            <updated>2025-08-28T21:21:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1954</id>
            <title type="text"><![CDATA[Inbox Zero]]></title>
            <link rel="alternate" href="https://www.getinboxzero.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1954"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Automate and clean your inbox. Clean Up Your Inbox In Minutes.

Bulk unsubscribe from newsletters, automate your emails with AI, block cold emails, and view your analytics. Open-source.

- [Inbox Zero @ GitHub](https://github.com/elie222/inbox-zero).]]>
            </summary>
            <updated>2025-08-28T21:22:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1972</id>
            <title type="text"><![CDATA[🚀 E2M]]></title>
            <link rel="alternate" href="https://github.com/wisupai/e2m" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1972"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Everything to Markdown.

 E2M converts various file types (doc, docx, epub, html, htm, url, pdf, ppt, pptx, mp3, m4a) into Markdown. It’s easy to install, with dedicated parsers and converters, supporting custom configs. E2M offers an all-in-one, flexible, and open-source solution.]]>
            </summary>
            <updated>2025-08-28T21:25:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1974</id>
            <title type="text"><![CDATA[Lucie LLM]]></title>
            <link rel="alternate" href="https://huggingface.co/collections/OpenLLM-France/lucie-llm-67099ba7b992dee2c32b1f92" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1974"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open weights LLM for French, English, German, Spanish and Italian.

- [Lucie Training @ GitHub](https://github.com/OpenLLM-France/Lucie-Training).
 
Related contents:

- [C’est un grand jour pour LINAGORA et la communauté OpenLLM 🇫🇷 🇪🇺-france @ Jean-Pierre LORRE&amp;#039;s LinkedIn](https://www.linkedin.com/posts/jplorre_llm-opensource-ia-activity-7284686154807869440-40OZ/).
- [OpenLLM-France homepage :fr:](https://www.openllm-france.fr/).]]>
            </summary>
            <updated>2025-08-28T21:25:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1975</id>
            <title type="text"><![CDATA[OpenLLM France :fr:]]></title>
            <link rel="alternate" href="https://www.openllm-france.fr/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1975"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM génératifs ouverts et performants.

Le Consortium OpenLLM France réunit 17 acteurs qui se sont rassemblés dans le prolongement de la création de la communauté OpenLLM France qui fédère à ce jour un écosystème de près de 200 entités (laboratoires publics de recherche, fournisseurs potentiels de données, acteurs technologiques spécialisés, fournisseurs de cas d&amp;#039;usage...). Ces acteurs échangent de manière publique et transparente depuis le début de l’été 2023 sur le serveur Discord de la communauté.]]>
            </summary>
            <updated>2025-08-28T21:25:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1977</id>
            <title type="text"><![CDATA[OpenRouter]]></title>
            <link rel="alternate" href="https://openrouter.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1977"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A unified interface for LLMs.
Better prices, better uptime, no subscription.

- [OpenRouter @ GitHub](https://github.com/OpenRouterTeam).
- [llm-openrouter @ GitHub](https://github.com/simonw/llm-openrouter).

Related contents:

- [How I don&amp;#039;t use LLMs @ argmin gravitas](https://www.gleech.org/llms).]]>
            </summary>
            <updated>2026-07-21T06:27:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1980</id>
            <title type="text"><![CDATA[Giskard]]></title>
            <link rel="alternate" href="https://docs.giskard.ai/en/stable/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1980"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🐢 Open-Source Evaluation &amp;amp; Testing for AI &amp;amp; LLM systems.

The testing framework dedicated to ML models, from tabular to LLMs.
Control risks of performance, bias and security issues in AI systems.

- [Giskard @ GitHub](https://github.com/Giskard-AI/giskard).]]>
            </summary>
            <updated>2025-08-28T21:26:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1985</id>
            <title type="text"><![CDATA[sitefetch]]></title>
            <link rel="alternate" href="https://github.com/egoist/sitefetch" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1985"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fetch an entire site and save it as a text file (to be used with AI models).]]>
            </summary>
            <updated>2025-08-28T21:28:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1988</id>
            <title type="text"><![CDATA[LackSynth]]></title>
            <link rel="alternate" href="https://github.com/aielte-research/HackSynth" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1988"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLM Agent and Evaluation Framework for Autonomous Penetration Testing.

We introduce HackSynth, a novel Large Language Model (LLM)-based agent capable of autonomous penetration testing. HackSynth&amp;#039;s dual-module architecture includes a Planner and a Summarizer, which enable it to generate commands and process feedback iteratively. To benchmark HackSynth, we propose two new Capture The Flag (CTF)-based benchmark sets utilizing the popular platforms PicoCTF and OverTheWire. These benchmarks include two hundred challenges across diverse domains and difficulties, providing a standardized framework for evaluating LLM-based penetration testing agents.]]>
            </summary>
            <updated>2025-08-28T21:28:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1998</id>
            <title type="text"><![CDATA[Vera :fr:]]></title>
            <link rel="alternate" href="https://www.askvera.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1998"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Le numéro de confiance pour vérifier les faits.

Un seul numéro (gratuit) pour contrer la désinformation et apaiser le débat public.

- [VERA - L&amp;#039;IA qui chasse les fake news @ Korben :fr:](https://korben.info/vera-ia-lutte-contre-fake-news-smartphone.html).]]>
            </summary>
            <updated>2025-08-28T21:29:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2008</id>
            <title type="text"><![CDATA[Model Context Protocol]]></title>
            <link rel="alternate" href="https://modelcontextprotocol.io/docs/getting-started/intro" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2008"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.

- [Model Context Protocol @ GitHub](https://github.com/modelcontextprotocol).
- [Model Context Protocol servers @ GitHub](https://github.com/modelcontextprotocol/servers).

Related contents:

- [Model Context Protocol (MCP) Course @ Hugging Face](https://huggingface.co/learn/mcp-course/unit0/introduction).
- [Introducing the Model Context Protocol @ Anthropic](https://www.anthropic.com/news/model-context-protocol).
- [LLM Agent Assisted Coding @ stafford williams](https://staffordwilliams.com/blog/2025/01/12/llm-agent-assisted-coding/).
- [Everyone is talking about MCP @ Adam Silverman&amp;#039;s X](https://x.com/AtomSilverman/status/1897409286466363626).
- [What is Model Context Protocol (MCP)? How it simplifies AI integrations compared to APIs @ Norah Sakal](https://norahsakal.com/blog/mcp-vs-api-model-context-protocol-explained/).
- [What is MCP by Anthropic?(Model Context Protocol) @ Toward AI](https://pub.towardsai.net/what-is-mcp-by-anthropic-model-context-protocol-356cf5130612).
- [A Deep Dive Into MCP and the Future of AI Tooling @ Andreessen Horowitz](https://a16z.com/a-deep-dive-into-mcp-and-the-future-of-ai-tooling/).
- [What is MCP (Model Context Protocol)? @ daily.dev](https://daily.dev/blog/what-is-mcp-model-context-protocol).
- [230. MCP - It&amp;#039;s Hot, But Will It Win? @ Hardcore Software by Steven Sinofsky](https://hardcoresoftware.learningbyshipping.com/p/230-mcp-its-hot-but-will-it-win).
- [MCP (Model Context Protocol): Simply explained in 5 minutes @ High Growth Engineer](https://read.highgrowthengineer.com/p/mcps-simply-explained).
- [The “S” in MCP Stands for Security @ Elena Cross&amp;#039; Medium](https://elenacross7.medium.com/%EF%B8%8F-the-s-in-mcp-stands-for-security-91407b33ed6b).
- [Everything Wrong with MCP @ Shrivu&amp;#039;s Substack](https://blog.sshh.io/p/everything-wrong-with-mcp).
- [MCPs, Gatekeepers, and the Future of AI @ I Am Charlie Graham](https://www.iamcharliegraham.com/mcps-gatekeepers-and-the-future-of-ai/).
- [A Critical Look at MCP @ Raz Blog](https://raz.sh/blog/2025-05-02_a_critical_look_at_mcp).
- [MCP vs API @ Glama](https://glama.ai/blog/2025-06-06-mcp-vs-api).
- [MCP explained without hype or fluff @ nilenso](https://blog.nilenso.com/blog/2025/05/12/mcp-explained-without-hype-or-fluff/).
- [What are MCP Servers? @ The Fly Blog](https://fly.io/blog/mcps-everywhere/).
- [Block&amp;#039;s Playbook for Designing MCP Servers @ Block Engineering Blog](https://engineering.block.xyz/blog/blocks-playbook-for-designing-mcp-servers).
- [MCP is eating the world—and it&amp;#039;s here to stay @ Stainless](https://www.stainless.com/blog/mcp-is-eating-the-world--and-its-here-to-stay).
- [MCP: An (Accidentally) Universal Plugin System @ Works on My Machine](https://worksonmymachine.substack.com/p/mcp-an-accidentally-universal-plugin).
- [MCP is eating the world—and it&amp;#039;s here to stay @ Stainless](https://www.stainless.com/blog/mcp-is-eating-the-world-and-its-here-to-stay).
- [MCP Vulnerabilities Every Developer Should Know @ Composio](https://composio.dev/blog/mcp-vulnerabilities-every-developer-should-know).
- [Your MCP Doesn’t Need 30 Tools: It Needs Code @ Armin Ronacher&amp;#039;s Thoughts and Writings](https://lucumr.pocoo.org/2025/8/18/code-mcps/).
- [The State of MCP Security @ Pynt](https://www.pynt.io/blog/llm-security-blogs/state-of-mcp-security).
- [MCPs Are Just Other People&amp;#039;s Prompts Pointing to Other People&amp;#039;s Code @ Daniel Miessler](https://danielmiessler.com/blog/mcps-are-just-other-peoples-prompts-and-apis).
- [you need to learn MCP RIGHT NOW!! (Model Context Protocol) @ NetworkChuck&amp;#039;s YouTube](https://www.youtube.com/watch?v=GuTcle5edjk).
- [Episode \#112: A new direction for AI developer tooling @ Changelog &amp;amp; Friends](https://changelog.com/friends/112).
- [What is special about MCP? @ Jessitron](https://jessitron.com/2025/11/09/what-is-special-about-mcp/).
- [Code execution with MCP: Building more efficient agents @ Engineering @ Anthropic](https://www.anthropic.com/engineering/code-execution-with-mcp).
- [MCP Apps: Extending servers with interactive user interfaces @ mcp blog](https://blog.modelcontextprotocol.io/posts/2025-11-21-mcp-apps/).
- [Model Context Protocol (MCP) Tutorial: Build Your First MCP Server in 6 Steps @ towards data science](https://towardsdatascience.com/model-context-protocol-mcp-tutorial-build-your-first-mcp-server-in-6-steps/).
- [MCP is dead. Long live the CLI @ Eric Holmes](https://ejholmes.github.io/2026/02/28/mcp-is-dead-long-live-the-cli.html).]]>
            </summary>
            <updated>2026-03-02T12:59:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2012</id>
            <title type="text"><![CDATA[Tabby]]></title>
            <link rel="alternate" href="https://www.tabbyml.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2012"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Opensource, self-hosted AI coding assistant.
Secure, flexible, and transparent AI coding.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot.

- [Tabby @ GitHub](https://github.com/TabbyML/tabby).]]>
            </summary>
            <updated>2026-01-23T10:58:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2034</id>
            <title type="text"><![CDATA[code2prompt]]></title>
            <link rel="alternate" href="https://github.com/mufeedvh/code2prompt" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2034"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.]]>
            </summary>
            <updated>2025-08-28T21:36:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2039</id>
            <title type="text"><![CDATA[paperless-gpt]]></title>
            <link rel="alternate" href="https://github.com/icereed/paperless-gpt" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2039"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Use LLMs and LLM Vision (OCR) to handle paperless-ngx - Document Digitalization powered by AI.

paperless-gpt seamlessly pairs with paperless-ngx to generate AI-powered document titles and tags, saving you hours of manual sorting. While other tools may offer AI chat features, paperless-gpt stands out by supercharging OCR with LLMs—ensuring high accuracy, even with tricky scans. If you’re craving next-level text extraction and effortless document organization, this is your solution.]]>
            </summary>
            <updated>2025-08-28T21:36:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2053</id>
            <title type="text"><![CDATA[Epigram]]></title>
            <link rel="alternate" href="https://epigram.news/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2053"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-Source, Free, and AI-Powered News in Short.

Your open-source, AI-powered news companion that redefines how you consume news. Get bite-sized summaries from trusted sources worldwide, personalized to your interests. Stay informed without the overwhelm.

- [Epigram @ GitHub](https://github.com/panda-sandeep/epigram).]]>
            </summary>
            <updated>2025-08-28T21:38:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2057</id>
            <title type="text"><![CDATA[Paperless-AI]]></title>
            <link rel="alternate" href="https://clusterzx.github.io/paperless-ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2057"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An automated document analyzer for Paperless-ngx using OpenAI API and Ollama (Mistral, llama, phi 3, gemma 2) to automatically analyze and tag your documents.

 It features: Automode, Manual Mode, Ollama and OpenAI, a Chat function to query your documents with AI, a modern and intuitive Webinterface.

- [Paperless-AI @ GitHub](https://github.com/clusterzx/paperless-ai).]]>
            </summary>
            <updated>2025-08-28T21:40:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2066</id>
            <title type="text"><![CDATA[Storyteller]]></title>
            <link rel="alternate" href="https://smoores.gitlab.io/storyteller/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2066"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Storyteller is a self-hosted platform for creating and reading ebooks with
synced narration. It&amp;#039;s made of three components: the API server, the web
interface, and the mobile apps. Together, these components allow you to take
audiobooks and ebooks that you already own and automatically synchronize them,
as well as read or listen to (or both!) the resulting synced books.

- [Storyteller @ GitLab](https://gitlab.com/smoores/storyteller).

Related contents:

- [Episode 140: When Upgrades Go Wrong @ Self Hosted](https://selfhosted.show/140).]]>
            </summary>
            <updated>2025-08-28T21:40:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2084</id>
            <title type="text"><![CDATA[Windsurf Editor]]></title>
            <link rel="alternate" href="https://codeium.com/windsurf" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2084"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Built to keep you in flow state

The first agentic IDE, and then some. The Windsurf Editor is where the work of developers and AI truly flow together, allowing for a coding experience that feels like literal magic.]]>
            </summary>
            <updated>2025-08-28T21:44:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2091</id>
            <title type="text"><![CDATA[Crawl4AI]]></title>
            <link rel="alternate" href="https://crawl4ai.com/mkdocs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2091"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-Source LLM-Friendly Web Crawler &amp;amp; Scraper.

Crawl4AI delivers blazing-fast, AI-ready web crawling tailored for large language models, AI agents, and data pipelines. Fully open source, flexible, and built for real-time performance, Crawl4AI empowers developers with unmatched speed, precision, and deployment ease.

- [Crawl4AI @ GitHub](https://github.com/unclecode/crawl4ai).]]>
            </summary>
            <updated>2025-08-28T21:44:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2108</id>
            <title type="text"><![CDATA[Khoj AI]]></title>
            <link rel="alternate" href="https://khoj.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2108"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your AI Second Brain.
Ask anything, understand documents, create new content.

Khoj is a personal AI app to extend your capabilities. It smoothly scales up from an on-device personal AI to a cloud-scale enterprise AI.

 Your AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research. Turn any online or local LLM into your personal, autonomous AI (gpt, claude, gemini, llama, qwen, mistral). Get started - free. 

- [Khoj @ GitHub](https://github.com/khoj-ai/khoj).

Related contents:

- [Khoj - Un assistant IA privé qui vous accompagne au quotidien @ Korben :fr:](https://korben.info/khoj-assistant-ia-prive-productivite.html).]]>
            </summary>
            <updated>2025-08-28T21:48:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2111</id>
            <title type="text"><![CDATA[Airbyte]]></title>
            <link rel="alternate" href="https://airbyte.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2111"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-Source Data Movement for LLMs. AI Platform.
Data integration platform for ELT pipelines from APIs, databases &amp;amp; files to databases, warehouses &amp;amp; lakes.

The leading data integration platform for ETL / ELT data pipelines from APIs, databases &amp;amp; files to data warehouses, data lakes &amp;amp; data lakehouses. Both self-hosted and Cloud-hosted. 

- [Airbyte @ GitHub](https://github.com/airbytehq/airbyte).]]>
            </summary>
            <updated>2026-04-22T12:36:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2112</id>
            <title type="text"><![CDATA[Llama Coder]]></title>
            <link rel="alternate" href="https://llamacoder.together.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2112"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Code Generator.

An open source Claude Artifacts – generate small apps with one prompt. Powered by Llama 3 405B &amp;amp; Together.ai. 

- [Llama Coder @ GitHub](https://github.com/nutlope/llamacoder).]]>
            </summary>
            <updated>2025-08-28T21:48:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2126</id>
            <title type="text"><![CDATA[ChatterUI]]></title>
            <link rel="alternate" href="https://github.com/Vali-98/ChatterUI" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2126"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Simple frontend for LLMs built in react-native.

ChatterUI is a native mobile frontend for LLMs.

Run LLMs on device or connect to various commercial or open source APIs. ChatterUI aims to provide a mobile-friendly interface with fine-grained control over chat structuring.

Related contents:

- [Meta-Llama-3.1-8B-Instruct.Q4_0_4_8.gguf @ Hugging Face](https://huggingface.co/gbueno86/Meta-Llama-3.1-8B-Instruct.Q4_0_4_8.gguf).
- [Meta veut une meilleure réalitée @ Tech Café :fr:](https://open.spotify.com/episode/1oDttN1dZwwJlCcqs5Np59).]]>
            </summary>
            <updated>2025-08-28T21:50:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2154</id>
            <title type="text"><![CDATA[Neural Networks: Zero to Hero]]></title>
            <link rel="alternate" href="https://github.com/karpathy/nn-zero-to-hero" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2154"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A course on neural networks that starts all the way at the basics. The course is a series of YouTube videos where we code and train neural networks together. The Jupyter notebooks we build in the videos are then captured here inside the lectures directory. Every lecture also has a set of exercises included in the video description. (This may grow into something more respectable).]]>
            </summary>
            <updated>2025-08-28T21:56:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2160</id>
            <title type="text"><![CDATA[MMAudio]]></title>
            <link rel="alternate" href="https://hkchengrex.com/MMAudio/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2160"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[MMAudio generates synchronized audio given video and/or text inputs.

Taming Multimodal Joint Training for High-Quality Video-to-Audio Synthesis.

- [MMAudio @ GitHub](https://github.com/hkchengrex/MMAudio).

Related contents:

- [MMAudio - Un outil pour synchroniser l&amp;#039;audio et la vidéo @ Korben :fr:](https://korben.info/mmaudio-outil-synchronisation-audio-video.html).]]>
            </summary>
            <updated>2025-08-28T21:56:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2199</id>
            <title type="text"><![CDATA[API Parrot]]></title>
            <link rel="alternate" href="https://apiparrot.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2199"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[API Parrot is the tool specifically designed to reverse engineer the HTTP APIs of any website. Making life easier for developers looking to automate, integrate or scrape websites without public APIs.]]>
            </summary>
            <updated>2025-08-28T22:02:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2208</id>
            <title type="text"><![CDATA[Pathway]]></title>
            <link rel="alternate" href="https://pathway.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2208"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Power Your AI with Live Data.

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. 

- [Pathway @ GitHub](https://github.com/pathwaycom/pathway).]]>
            </summary>
            <updated>2025-09-10T11:29:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2219</id>
            <title type="text"><![CDATA[Browserbase]]></title>
            <link rel="alternate" href="https://www.browserbase.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2219"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A web browser for AI agents &amp;amp; applications.
An AI web browsing framework focused on simplicity and extensibility. 

- [🤘 Stagehand @ GitHub](https://github.com/browserbase/stagehand).]]>
            </summary>
            <updated>2025-08-28T22:06:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2220</id>
            <title type="text"><![CDATA[MarkItDown]]></title>
            <link rel="alternate" href="https://github.com/microsoft/markitdown" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2220"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Python tool for converting files and office documents to Markdown.
MarkItDown is a utility for converting various files to Markdown (e.g., for indexing, text analysis, etc).

- [MarkItDown-MCP @ GitHub](https://github.com/microsoft/markitdown/tree/main/packages/markitdown-mcp).

Related contents:

- [MarkItDown - Convertissez tous vos documents en Markdown très facilement @ Korben :fr:](https://korben.info/markitdown-convertisseur-fichiers-markdown.html).
- [Convertir un document au format Markdown avec MarkItDown : Word, PDF, PowerPoint, Excel, etc. @ IT-Connect :fr:](https://www.it-connect.fr/convertir-un-document-au-format-markdown-avec-markitdown/).]]>
            </summary>
            <updated>2026-03-06T14:52:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2223</id>
            <title type="text"><![CDATA[OmniParse]]></title>
            <link rel="alternate" href="https://omniparse.cognitivelab.in/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2223"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Convert Anything into Structured Actionable Data.

 Ingest, parse, and optimize any data format ➡️ from documents to multimedia ➡️ for enhanced compatibility with GenAI frameworks.

OmniParse is a platform that ingests and parses any unstructured data into structured, actionable data optimized for GenAI (LLM) applications. Whether you are working with documents, tables, images, videos, audio files, or web pages, OmniParse prepares your data to be clean, structured, and ready for AI applications such as RAG, fine-tuning, and more

-  [OmniParse @ GitHub](https://github.com/adithya-s-k/omniparse).]]>
            </summary>
            <updated>2025-08-28T22:06:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2228</id>
            <title type="text"><![CDATA[Amurex @ Chrome Web Store]]></title>
            <link rel="alternate" href="https://chromewebstore.google.com/detail/amurex-early-preview/dckidmhhpnfhachdpobgfbjnhfnmddmc" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2228"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your AI Meeting Copilot (Early Preview)

Take the hassle out of meetings with Amurex, the ultimate Chrome extension that transforms how you manage and stay productive during meetings.

Amurex is your simple yet powerful AI meeting assistant that seamlessly integrates into your workflow. Built with cutting-edge AI, Amurex ensures you never miss a detail, always stay on top of action items, and make every meeting more productive.

- [Amurex @ GitHub](https://github.com/thepersonalaicompany/amurex).]]>
            </summary>
            <updated>2025-08-28T22:08:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2243</id>
            <title type="text"><![CDATA[bolt.diy]]></title>
            <link rel="alternate" href="https://stackblitz-labs.github.io/bolt.diy/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2243"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt, run, edit, and deploy full-stack web applications using any LLM you want! 

bolt.diy allows you to choose the LLM that you use for each prompt! Currently, you can use OpenAI, Anthropic, Ollama, OpenRouter, Gemini, LMStudio, Mistral, xAI, HuggingFace, DeepSeek, or Groq models - and it is easily extended to use any other model supported by the Vercel AI SDK! See the instructions below for running this locally and extending it to include more models.

- [bolt.diy @ GitHub](https://github.com/stackblitz-labs/bolt.diy).

Source: [Bolt.diy - Créez des apps full-stack en un clic avec l&amp;#039;IA, directement dans votre navigateur @ Korben :fr:](https://korben.info/bolt-diy-assistant-ia-developpement-web.html).]]>
            </summary>
            <updated>2025-08-28T22:10:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2270</id>
            <title type="text"><![CDATA[OpenVINO]]></title>
            <link rel="alternate" href="https://docs.openvino.ai/2024/index.html" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2270"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference.

OpenVINO is an open-source toolkit for optimizing and deploying deep learning models from cloud to edge. It accelerates deep learning inference across various use cases, such as generative AI, video, audio, and language with models from popular frameworks like PyTorch, TensorFlow, ONNX, and more. Convert and optimize models, and deploy across a mix of Intel® hardware and environments, on-premises and on-device, in the browser or in the cloud.

- [OpenVINO @ GitHub](https://github.com/openvinotoolkit/openvino).
- [OpenVINO @ Hugging Face](https://huggingface.co/OpenVINO).]]>
            </summary>
            <updated>2026-01-23T10:38:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2289</id>
            <title type="text"><![CDATA[Flowise]]></title>
            <link rel="alternate" href="https://flowiseai.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2289"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Low code LLM Apps Builder. Build LLM Apps Easily.

Open source low-code tool for developers to build customized LLM orchestration flow &amp;amp; AI agents.

- [Flowise @ GitHub](https://github.com/FlowiseAI/Flowise).

Related contents:

- [CVE-2024–8182 : Accidental Discovery of an Unauthenticated DoS @ Tenable TechBlog&amp;#039;s Medium](https://medium.com/tenable-techblog/cve-2024-8182-accidental-discovery-of-an-unauthenticated-dos-1d89947a09a4).]]>
            </summary>
            <updated>2025-08-28T22:17:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2311</id>
            <title type="text"><![CDATA[PydanticAI]]></title>
            <link rel="alternate" href="https://ai.pydantic.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2311"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Agent Framework / shim to use Pydantic with LLMs.

PydanticAI is a Python Agent Framework designed to make it less painful to build production grade applications with Generative AI.

- [PydanticAI @ GitHub](https://github.com/pydantic/pydantic-ai).

Related contents:

- [PydanticAI: A New Python Framework for Streamlined Generative AI Development @ InfoQ](https://www.infoq.com/news/2024/12/pydanticai-framework-gen-ai/).
- [Building your own CLI Coding Agent with Pydantic-AI @ martinFowler.com](https://martinfowler.com/articles/build-own-coding-agent.html).]]>
            </summary>
            <updated>2025-09-09T15:34:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2440</id>
            <title type="text"><![CDATA[BashSenpai]]></title>
            <link rel="alternate" href="https://bashsenpai.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2440"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Terminal Assistant.

BashSenpai is a command-line tool that utilizes the power of ChatGPT, bringing it straight to your terminal. You can ask questions and receive insightful responses related to shell scripting, making it an indispensable asset for both beginners and seasoned users alike.

- [BashSenpai @ GitHub](https://github.com/BashSenpai/cli).]]>
            </summary>
            <updated>2025-08-28T22:42:55+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2473</id>
            <title type="text"><![CDATA[DataFuel]]></title>
            <link rel="alternate" href="https://www.datafuel.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2473"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn websites into LLM - ready   data.

DataFuel API scrapes entire websites and knowledge bases in a single query. Get clean, markdown-structured web data instantly for your RAG systems and AI models. No complex scraping code needed.]]>
            </summary>
            <updated>2025-08-28T22:48:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2487</id>
            <title type="text"><![CDATA[brainstorm]]></title>
            <link rel="alternate" href="https://github.com/Invicti-Security/brainstorm/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2487"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A smarter web fuzzing tool that combines local LLM models and ffuf to optimize directory and file discovery.

This tool enhances traditional web fuzzing by using local AI language models (via Ollama) to generate intelligent guesses for potential paths and filenames. 

- [Brainstorm tool release: Optimizing web fuzzing with local LLMs @ invicti](https://www.invicti.com/blog/security-labs/brainstorm-tool-release-optimizing-web-fuzzing-with-local-llms/).]]>
            </summary>
            <updated>2025-08-28T22:50:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2488</id>
            <title type="text"><![CDATA[burpference]]></title>
            <link rel="alternate" href="https://github.com/dreadnode/burpference" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2488"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A research project to add some brrrrrr to Burp.

&amp;quot;burpference&amp;quot; started as a research idea of offensive agent capabilities and is a fun take on Burp Suite and running inference. The extension is open-source and designed to capture in-scope HTTP requests and responses from Burp&amp;#039;s proxy history and ship them to a remote LLM API in JSON format. It&amp;#039;s designed with a flexible approach where you can configure custom system prompts, store API keys and select remote hosts from numerous model providers as well as the ability for you to create your own API configuration. The idea is for an LLM to act as an agent in an offensive web application engagement to leverage your skills and surface findings and lingering vulnerabilities. By being able to create your own configuration and model provider allows you to also host models locally via Ollama to prevent potential high inference costs and potential network delays or rate limits.]]>
            </summary>
            <updated>2026-02-12T12:58:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2489</id>
            <title type="text"><![CDATA[LaVague]]></title>
            <link rel="alternate" href="https://www.lavague.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2489"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source framework for building Web Agents.
Build and deploy Web Agents in a few lines of code.

- [LaVague @ GitHub](https://github.com/lavague-ai/LaVague).
- [LaVague documentation](https://docs.lavague.ai/en/latest/).]]>
            </summary>
            <updated>2025-08-28T22:50:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2490</id>
            <title type="text"><![CDATA[Wren AI]]></title>
            <link rel="alternate" href="https://getwren.ai/oss" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2490"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source sQL AI Agent. Text2SQL made Easy!

Wren AI is an open-source SQL AI Agent that empowers data, product, and business teams to access insights through AI chat, built-in well designed intuitive UI and UX, integrating seamlessly with tools like Excel and Google Sheets.

- [Wren AI @ GitHub](https://github.com/Canner/WrenAI).]]>
            </summary>
            <updated>2025-08-28T22:50:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2503</id>
            <title type="text"><![CDATA[Otoroshi LLM Extension]]></title>
            <link rel="alternate" href="https://cloud-apim.github.io/otoroshi-llm-extension/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2503"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A set of Otoroshi plugins to interact with LLMs.

Connect, setup, secure and seamlessly manage LLM models using an Universal/OpenAI compatible API.

- [Otoroshi LLM Extension @ GitHub](https://github.com/cloud-apim/otoroshi-llm-extension).
- [Otoroshi with LLM : Pilotez et sécurisez vos modèles d&amp;#039;IA @ CleverCloud&amp;#039;s YouTube :fr:](https://www.youtube.com/watch?v=Gm0mblQWwSc).]]>
            </summary>
            <updated>2025-08-28T22:53:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2510</id>
            <title type="text"><![CDATA[FinGPT]]></title>
            <link rel="alternate" href="https://github.com/AI4Finance-Foundation/FinGPT" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2510"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.]]>
            </summary>
            <updated>2025-08-28T22:54:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2511</id>
            <title type="text"><![CDATA[🌟 Awesome LLM Apps]]></title>
            <link rel="alternate" href="https://github.com/Shubhamsaboo/awesome-llm-apps" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2511"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Collection of awesome LLM apps with RAG using OpenAI, Anthropic, Gemini and opensource models. 

A curated collection of awesome LLM apps built with RAG and AI agents. This repository features LLM apps that use models from OpenAI, Anthropic, Google, and even open-source models like LLaMA that you can run locally on your computer.]]>
            </summary>
            <updated>2025-08-28T22:54:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2518</id>
            <title type="text"><![CDATA[Oat 🌾]]></title>
            <link rel="alternate" href="https://github.com/sail-sg/oat" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2518"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Online AlignmenT for LLMs.

Oat 🌾 is a simple yet efficient system for running online LLM alignment algorithms.]]>
            </summary>
            <updated>2025-08-28T22:57:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2526</id>
            <title type="text"><![CDATA[ClearerVoice-Studio]]></title>
            <link rel="alternate" href="https://github.com/modelscope/ClearerVoice-Studio" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2526"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[ClearerVoice-Studio is an open-source, AI-powered speech processing toolkit designed for researchers, developers, and end-users. It provides capabilities of speech enhancement, speech separation, target speaker extraction, and more. The toolkit provides state-of-the-art pre-trained models, along with training and inference scripts, all accessible from this repository.]]>
            </summary>
            <updated>2025-08-28T22:57:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2527</id>
            <title type="text"><![CDATA[mPLUG-DocOwl]]></title>
            <link rel="alternate" href="https://github.com/X-PLUG/mPLUG-DocOwl" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2527"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Powerful Multi-modal LLM Family for OCR-free Document Understanding.
Modularized Multimodal Large Language Model for Document Understanding.]]>
            </summary>
            <updated>2025-08-28T22:58:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2534</id>
            <title type="text"><![CDATA[Countless.dev]]></title>
            <link rel="alternate" href="https://countless.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2534"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Model Comparison.

See and compare every AI model easily. 100% free &amp;amp; open-source.

- [Countless.dev @ GitHub](https://github.com/Ahmet-Dedeler/ai-llm-comparison).]]>
            </summary>
            <updated>2025-08-28T22:58:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2550</id>
            <title type="text"><![CDATA[Open Notebook]]></title>
            <link rel="alternate" href="https://www.open-notebook.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2550"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Take Control of Your Learning. Privately.

A powerful open-source, AI-powered note-taking/research platform that respects your privacy.
An Open Source implementation of Notebook LM with more flexibility and features.

- [Open Notebook @ GitHub](https://github.com/lfnovo/open-notebook).

Related contents:

- [Open Notebook: A True Open Source Private NotebookLM Alternative? @ KD nuggets](https://www.kdnuggets.com/open-notebook-a-true-open-source-private-notebooklm-alternative).]]>
            </summary>
            <updated>2026-01-27T07:35:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2561</id>
            <title type="text"><![CDATA[Oversight]]></title>
            <link rel="alternate" href="https://github.com/user1342/Oversight" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2561"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Completely Modular LLM Reverse Engineering, Red Teaming, and Vulnerability Research Framework.]]>
            </summary>
            <updated>2025-08-28T23:03:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2594</id>
            <title type="text"><![CDATA[Promptim]]></title>
            <link rel="alternate" href="https://github.com/hinthornw/promptimizer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2594"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt optimization scratch.
Promptim is an experimental prompt optimization library to help you systematically improve your AI systems.

Promptim automates the process of improving prompts on specific tasks. You provide initial prompt, a dataset, and custom evaluators (and optional human feedback), and promptim runs an optimization loop to produce a refined prompt that aims to outperform the original.

Related contents:

- [Promptim: an experimental library for prompt optimization @ LangChain](https://blog.langchain.dev/promptim/).
- [Promptimizer - Optimisez vos prompts IA automatiquement @ Korben :fr:](https://korben.info/promptimizer-optimisation-automatique-prompts-ia.html).]]>
            </summary>
            <updated>2025-08-28T23:09:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2610</id>
            <title type="text"><![CDATA[COMandA]]></title>
            <link rel="alternate" href="https://github.com/kris-hansen/comanda" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2610"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Execute agentic workflows defined in simple YAML files.

COMandA is a command-line tool that enables the composition of Large Language Model (LLM) operations using a YAML-based Domain Specific Language (DSL). It simplifies the process of creating and managing agentic workflows composed of downloads, files, text, images, documents, multiple providers and multiple models.]]>
            </summary>
            <updated>2025-08-28T23:11:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2620</id>
            <title type="text"><![CDATA[Prism]]></title>
            <link rel="alternate" href="https://prism.echolabs.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2620"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Laravel x LLMs. A unified interface for working with LLMs in Laravel.

Prism is a powerful Laravel package for integrating Large Language Models (LLMs) into your applications.

- [Prism @ GitHub](https://github.com/echolabsdev/prism).]]>
            </summary>
            <updated>2025-08-28T23:13:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2631</id>
            <title type="text"><![CDATA[Steel]]></title>
            <link rel="alternate" href="https://steel.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2631"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source Headless Browser API.

 🚧 Open Source Browser API for AI Agents &amp;amp; Apps. Steel Browser is a batteries-included browser instance that lets you build automate the web without worrying about infrastructure. 

- [Steel @ GitHub](https://github.com/steel-dev/steel-browser).]]>
            </summary>
            <updated>2025-10-14T11:28:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2666</id>
            <title type="text"><![CDATA[Cali]]></title>
            <link rel="alternate" href="https://github.com/callstackincubator/cali" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2666"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI agent for building React Native apps.

Cali is an AI agent that helps you build React Native apps. It takes all the utilities and functions of a React Native CLI and exposes them as tools to an LLM.

Thanks to that, an LLM can help you with your React Native app development, without the need to remember commands, spending time troubleshooting errors, and in the future, much more.]]>
            </summary>
            <updated>2025-08-28T23:21:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2670</id>
            <title type="text"><![CDATA[aisuite]]></title>
            <link rel="alternate" href="https://github.com/andrewyng/aisuite" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2670"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Simple, unified interface to multiple Generative AI providers.

aisuite makes it easy for developers to use multiple LLM through a standardized interface. Using an interface similar to OpenAI&amp;#039;s, aisuite makes it easy to interact with the most popular LLMs and compare the results. It is a thin wrapper around python client libraries, and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. Today, the library is primarily focussed on chat completions. We will expand it cover more use cases in near future.]]>
            </summary>
            <updated>2026-06-15T11:54:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2685</id>
            <title type="text"><![CDATA[The Open Interpreter Project]]></title>
            <link rel="alternate" href="https://www.openinterpreter.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2685"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A natural language interface for computers.

Open Interpreter lets LLMs run code (Python, Javascript, Shell, and more) locally. You can chat with Open Interpreter through a ChatGPT-like interface in your terminal by running $ interpreter after installing.

- [Open Interpreter @ GitHub](https://github.com/OpenInterpreter/open-interpreter).]]>
            </summary>
            <updated>2025-08-28T23:25:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2711</id>
            <title type="text"><![CDATA[Mastra]]></title>
            <link rel="alternate" href="https://mastra.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2711"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Typescript AI framework.

Mastra is an opinionated Typescript framework that helps you build AI applications and features quickly. It gives you the set of primitives you need: workflows, agents, RAG, integrations, syncs and evals. You can run Mastra on your local machine, or deploy to a serverless cloud.

- [Mastra @ GitHub](https://github.com/mastra-ai/mastra).

Related contents:

- [\#107 - Les news web dev pour mars 2025 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-mar-25/).
- [Mastra 101: Learn how to build agents @ Mastra University](https://mastra.ai/course).]]>
            </summary>
            <updated>2025-08-28T23:29:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2712</id>
            <title type="text"><![CDATA[garak]]></title>
            <link rel="alternate" href="https://github.com/NVIDIA/garak" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2712"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[the LLM vulnerability scanner. Generative AI Red-teaming &amp;amp; Assessment Kit

garak checks if an LLM can be made to fail in a way we don&amp;#039;t want. garak probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. If you know nmap, it&amp;#039;s nmap for LLMs.]]>
            </summary>
            <updated>2025-08-28T23:29:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2722</id>
            <title type="text"><![CDATA[TiDB]]></title>
            <link rel="alternate" href="https://tidb.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2722"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Assistant. Knowledge Graph based RAG built with TiDB Serverless Vector Storage and LlamaIndex.

An open source GraphRAG (Knowledge Graph) built on top of TiDB Vector and LlamaIndex and DSPy.
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage.

- [autoflow @ GitHub](https://github.com/pingcap/autoflow).]]>
            </summary>
            <updated>2025-08-28T23:30:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2733</id>
            <title type="text"><![CDATA[AIOps modules]]></title>
            <link rel="alternate" href="https://github.com/awslabs/aiops-modules?tab=readme-ov-file" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2733"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AIOps modules is a collection of reusable Infrastructure as Code (IaC) modules for Machine Learning (ML), Foundation Models (FM), Large Language Models (LLM) and GenAI development and operations on AWS]]>
            </summary>
            <updated>2025-08-28T23:33:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2770</id>
            <title type="text"><![CDATA[Willow]]></title>
            <link rel="alternate" href="https://heywillow.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2770"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Willow Is a Practical, Open Source, Privacy-focused Platform for Voice Assistants and Other Applications.
Open source, local, and self-hosted Amazon Echo/Google Home competitive Voice Assistant alternative.

Willow is an ESP IDF based project primarily targeting the ESP32-S3-BOX hardware family from Espressif. Our goal is to provide Amazon Echo/Google Home competitive performance, accuracy, cost and functionality with Home Assistant, openHAB and other platforms.

- [Willow @ GitHub](https://github.com/toverainc/willow).]]>
            </summary>
            <updated>2025-08-28T23:38:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2774</id>
            <title type="text"><![CDATA[Screenshot to Code]]></title>
            <link rel="alternate" href="https://screenshottocode.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2774"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Drop in a screenshot and convert it to clean code (HTML/Tailwind/React/Vue).

A simple tool to convert screenshots, mockups and Figma designs into clean, functional code using AI.

- [Screenshot to Code @ GitHub](https://github.com/abi/screenshot-to-code).]]>
            </summary>
            <updated>2025-08-28T23:38:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2812</id>
            <title type="text"><![CDATA[Common Corpus]]></title>
            <link rel="alternate" href="https://huggingface.co/datasets/PleIAs/common_corpus" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2812"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Common Corpus is the largest open and permissible licensed text dataset, comprising over 2 trillion tokens (2,003,039,184,047 tokens). It is a diverse dataset, consisting of books, newspapers, scientific articles, government and legal documents, code, and more. 

- [Announcing Common Corpus: A 2+ trillion token dataset that&amp;#039;s fully open and accessible @ moz://a](https://future.mozilla.org/builders/news_insights/announcing-common-corpus-a-2-trillion-token-dataset-thats-fully-open-and-accessible/).]]>
            </summary>
            <updated>2025-08-28T23:45:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2814</id>
            <title type="text"><![CDATA[Chroma]]></title>
            <link rel="alternate" href="https://www.trychroma.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2814"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[the AI-native open-source embedding database.  The fastest way to build Python or JavaScript LLM apps with memory! 
Chroma is the open-source AI application database. Batteries included.

Embeddings, vector search, document storage, full-text search, metadata filtering, and multi-modal. All in one place. Retrieval that just works. As it should be.

- [Chroma @ GitHub](https://github.com/chroma-core/chroma).

Related contents:

- [ChromaDB: An Open-source vector embedding database @ Futuresmart AI Blog](https://blog.futuresmart.ai/chromadb-an-open-source-vector-embedding-database).
- [How to Build a Local RAG App with Ollama and ChromaDB in the R Programming Language @ freeCodeCamp](https://www.freecodecamp.org/news/build-a-local-rag-app-with-ollama-and-chromadb-in-r/).]]>
            </summary>
            <updated>2026-02-09T16:46:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2819</id>
            <title type="text"><![CDATA[Documind]]></title>
            <link rel="alternate" href="https://www.documind.xyz/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2819"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Extract structured data from PDFs.
Stop wasting time extracting PDFs.
Transform your PDF documents into structured data with Documind. Simple, powerful and open-source.

Documind is an advanced document processing tool that leverages AI to extract structured data from PDFs. It is built to handle PDF conversions, extract relevant information, and format results as specified by customizable schemas.

- [Documind @ GitHub](https://github.com/DocumindHQ/documind/).]]>
            </summary>
            <updated>2025-08-28T23:46:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2820</id>
            <title type="text"><![CDATA[Fast GraphRAG]]></title>
            <link rel="alternate" href="https://github.com/circlemind-ai/fast-graphrag" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2820"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[RAG that intelligently adapts to your use case, data, and queries.

Streamlined and promptable Fast GraphRAG framework designed for interpretable, high-precision, agent-driven retrieval workflows.]]>
            </summary>
            <updated>2025-08-28T23:46:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2832</id>
            <title type="text"><![CDATA[MinerU]]></title>
            <link rel="alternate" href="https://mineru.readthedocs.io/en/latest/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2832"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[MinerU is a tool that converts PDFs into machine-readable formats (e.g., markdown, JSON), allowing for easy extraction into any format. MinerU was born during the pre-training process of InternLM. We focus on solving symbol conversion issues in scientific literature and hope to contribute to technological development in the era of large models. Compared to well-known commercial products, MinerU is still young. If you encounter any issues or if the results are not as expected, please submit an issue on issue and attach the relevant PDF.

- [MinerU @ GitHub](https://github.com/opendatalab/MinerU).]]>
            </summary>
            <updated>2025-08-28T23:49:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2877</id>
            <title type="text"><![CDATA[OpenAI PHP]]></title>
            <link rel="alternate" href="https://github.com/openai-php/client" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2877"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[⚡️ OpenAI PHP is a supercharged community-maintained PHP API client that allows you to interact with OpenAI API.

OpenAI PHP is a community-maintained PHP API client that allows you to interact with the Open AI API.]]>
            </summary>
            <updated>2025-08-28T23:55:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2884</id>
            <title type="text"><![CDATA[PandasAI]]></title>
            <link rel="alternate" href="https://pandas-ai.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2884"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Conversational Data Analysis.

PandasAI is a Python platform that makes it easy to ask questions to your data in natural language. It helps non-technical users to interact with their data in a more natural way, and it helps technical users to save time, and effort when working with data.

PandasAI is a Python library that integrates generative artificial intelligence capabilities into pandas, making dataframes conversational.
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG. 

- [PandasAI @ GitHub](https://github.com/Sinaptik-AI/pandas-ai).]]>
            </summary>
            <updated>2025-08-28T23:57:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2887</id>
            <title type="text"><![CDATA[LLM Prompt Tuning Playbook]]></title>
            <link rel="alternate" href="https://github.com/varungodbole/prompt-tuning-playbook" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2887"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A playbook for effectively prompting post-trained LLMs.

This document is for anyone who would like to get better at prompting post-trained LLMs. We assume that readers have had some basic interactions with some sort of LLM (e.g. Gemini), but we do not assume a rigorous technical understanding.]]>
            </summary>
            <updated>2025-08-28T23:57:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2894</id>
            <title type="text"><![CDATA[WebLLM Chat]]></title>
            <link rel="alternate" href="https://chat.webllm.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2894"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chat with AI large language models running natively in your browser. Enjoy private, server-free, seamless AI conversations. 

WebLLM Chat is a private AI chat interface that combines WebLLM with a user-friendly design, leveraging WebGPU to run large language models (LLMs) natively in your browser. Enjoy an unprecedented, private, and accessible AI conversation experience.

- [WebLLM Chat @ GitHub](https://github.com/mlc-ai/web-llm-chat).]]>
            </summary>
            <updated>2025-08-28T23:58:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2900</id>
            <title type="text"><![CDATA[Chonkie]]></title>
            <link rel="alternate" href="https://github.com/bhavnicksm/chonkie" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2900"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🦛 CHONK your texts with Chonkie ✨ - The no-nonsense RAG chunking library.
The no-nonsense RAG chunking library that&amp;#039;s lightweight, lightning-fast, and ready to CHONK your texts]]>
            </summary>
            <updated>2025-08-28T23:59:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2918</id>
            <title type="text"><![CDATA[OpenHands (by All Hands AI)]]></title>
            <link rel="alternate" href="https://www.all-hands.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2918"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source Agents for Developers

Use AI to tackle the toil in your backlog, so you can focus on what matters: hard problems, creative challenges, and over-engineering your dotfiles.

- [OpenHands @ GitHub](https://github.com/All-Hands-AI/OpenHands).

Related contents:

- [Devstral @ Mistral](https://mistral.ai/news/devstral).]]>
            </summary>
            <updated>2025-08-29T00:02:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2948</id>
            <title type="text"><![CDATA[Aide]]></title>
            <link rel="alternate" href="https://aide.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2948"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The open-source AI-native IDE. Powered by the state-of-the-art agentic framework on swebench-lite.

Aide is the Open Source AI-native code editor. It is a fork of VS Code, and integrates tightly with the leading agentic framework on swebench-lite.

- [Aide @ GitHub](https://github.com/codestoryai/aide).]]>
            </summary>
            <updated>2025-08-29T00:07:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2949</id>
            <title type="text"><![CDATA[Docling]]></title>
            <link rel="alternate" href="https://docling-project.github.io/docling/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2949"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Docling parses documents and exports them to the desired format with ease and speed.
🗂️ Reads popular document formats (PDF, DOCX, PPTX, Images, HTML, AsciiDoc, Markdown) and exports to Markdown and JSON.

- [Docling @ GitHub](https://github.com/docling-project/docling).

Related contents:

- [Docling - Pour convertir vos documents sans prise de tête @ Korben :fr:](https://korben.info/docling-convertisseur-documents-multi-formats.html).
- [Episode \#125: The state of homelab tech (2026) @ Changelog &amp;amp; Friends](https://changelog.com/friends/125).]]>
            </summary>
            <updated>2026-01-27T07:14:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2960</id>
            <title type="text"><![CDATA[🌐 Browser-Use]]></title>
            <link rel="alternate" href="https://github.com/gregpr07/browser-use" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2960"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-Source Web Automation library with any LLM.

Let LLMs interact with websites through a simple interface.]]>
            </summary>
            <updated>2025-08-29T00:10:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2975</id>
            <title type="text"><![CDATA[Hertz-dev]]></title>
            <link rel="alternate" href="https://github.com/Standard-Intelligence/hertz-dev" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2975"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Hertz-dev is an open-source, first-of-its-kind base model for full-duplex conversational audio.]]>
            </summary>
            <updated>2025-08-29T00:12:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3000</id>
            <title type="text"><![CDATA[Investbrain]]></title>
            <link rel="alternate" href="https://investbra.in/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3000"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Investbrain is a smart open-source platform that consolidates your portfolios from different brokerages, tracks market performance across your portfolios, and gives you an AI-powered investment best friend. 

- [Investbrain @ GitHub](https://github.com/investbrainapp/investbrain).

Related contents:

- [This Week in Self-Hosted (December 13, 2024) @ RSS.com](https://rss.com/podcasts/theselfhostcast/1799877/).]]>
            </summary>
            <updated>2025-08-29T00:16:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3050</id>
            <title type="text"><![CDATA[Zerox OCR]]></title>
            <link rel="alternate" href="https://github.com/getomni-ai/zerox" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3050"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Zero shot pdf OCR with gpt-4o-mini.

A dead simple way of OCR-ing a document for AI ingestion. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. The vision models just make sense!]]>
            </summary>
            <updated>2025-08-29T00:24:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3058</id>
            <title type="text"><![CDATA[STORM]]></title>
            <link rel="alternate" href="https://storm.genie.stanford.edu/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3058"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[STORM: Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking.

An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations. 

 STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. Co-STORM further enhanced its feature by enabling human to collaborative LLM system to support more aligned and preferred information seeking and knowledge curation. 

- [STORM @ GitHub](https://github.com/stanford-oval/storm).]]>
            </summary>
            <updated>2025-08-29T00:26:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3064</id>
            <title type="text"><![CDATA[Outlines]]></title>
            <link rel="alternate" href="https://dottxt-ai.github.io/outlines/latest/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3064"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Structured text generation and robust prompting for language models.

Outlines is a Python library that allows you to use Large Language Model in a simple and robust way (with structured generation). It is built by .txt, and is already used in production by many companies.

- [Outlines @ GitHub](https://github.com/dottxt-ai/outlines).

Related contents:

- [7 Lessons from building a small-scale AI application @ Richard Li](https://www.thelis.org/blog/lessons-from-ai).]]>
            </summary>
            <updated>2025-08-29T00:28:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3070</id>
            <title type="text"><![CDATA[Marly AI]]></title>
            <link rel="alternate" href="https://www.marly.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3070"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Data Processor for Agents.

Marly allows your agents to extract tables &amp;amp; text from your PDFs, Powerpoints, etc in a structured format making it easy for them to take subsequent actions (database call, API call, creating a chart etc).

- [Marly @ GitHub](https://github.com/marly-ai/marly).]]>
            </summary>
            <updated>2025-08-29T00:28:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3071</id>
            <title type="text"><![CDATA[TrafficLLM]]></title>
            <link rel="alternate" href="https://github.com/ZGC-LLM-Safety/TrafficLLM" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3071"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The repository of TrafficLLM, a universal LLM adaptation framework to learn robust traffic representation for all open-sourced LLM in real-world scenarios and enhance the generalization across diverse traffic analysis tasks. 

 The repository of TrafficLLM, a universal LLM adaptation framework to learn robust traffic representation for all open-sourced LLM in real-world scenarios and enhance the generalization across diverse traffic analysis tasks.]]>
            </summary>
            <updated>2025-08-29T00:28:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3074</id>
            <title type="text"><![CDATA[Amazon SageMaker]]></title>
            <link rel="alternate" href="https://aws.amazon.com/sagemaker/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3074"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows.

Amazon SageMaker is a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML) for any use case. With SageMaker, you can build, train and deploy ML models at scale using tools like notebooks, debuggers, profilers, pipelines, MLOps, and more – all in one integrated development environment (IDE). 

- [Déployez vos modèles de Machine Learning avec Amazon SageMaker @ Cockpit io :fr:](https://blog.cockpitio.com/artificial-intelligence/introduction-sagemaker/).]]>
            </summary>
            <updated>2025-08-29T00:28:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3085</id>
            <title type="text"><![CDATA[Vulnhuntr]]></title>
            <link rel="alternate" href="https://github.com/protectai/vulnhuntr" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3085"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Zero shot vulnerability discovery using LLMs. A tool to identify remotely exploitable vulnerabilities using LLMs and static code analysis.

Vulnhuntr leverages the power of LLMs to automatically create and analyze entire code call chains starting from remote user input and ending at server output for detection of complex, multi-step, security-bypassing vulnerabilities that go far beyond what traditional static code analysis tools are capable of performing. 

Related contents:

- [VulnHuntr - L&amp;#039;IA qui trouve des failles 0day dans votre code Python @ Korben :fr:](https://korben.info/vulnhuntr-ia-detecteur-vulnerabilites-0day-python.html).]]>
            </summary>
            <updated>2025-08-29T00:30:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3103</id>
            <title type="text"><![CDATA[GenAIScript]]></title>
            <link rel="alternate" href="https://microsoft.github.io/genaiscript/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3103"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Generative AI Scripting.

Programmatically assemble prompts for LLMs using JavaScript.

- [GenAIScript @ GitHub](https://github.com/microsoft/genaiscript/).]]>
            </summary>
            <updated>2025-08-29T00:33:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3117</id>
            <title type="text"><![CDATA[Vanna.AI]]></title>
            <link rel="alternate" href="https://vanna.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3117"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄. 

Personalized AI SQL Agent. Let Vanna.AI write your SQL for you

The fastest way to get actionable insights from your database just by asking questions.

- [Vanna @ GitHub](https://github.com/vanna-ai/vanna).]]>
            </summary>
            <updated>2025-08-29T00:36:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3146</id>
            <title type="text"><![CDATA[📦 Repopack]]></title>
            <link rel="alternate" href="https://github.com/yamadashy/repopack" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3146"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[📦 Repopack is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, and Gemini.]]>
            </summary>
            <updated>2025-08-29T00:40:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3157</id>
            <title type="text"><![CDATA[cli-ai]]></title>
            <link rel="alternate" href="https://github.com/fmdz387/cli-ai" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3157"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🤖 CLI AI Assistant

A simple command-line AI assistant that translates natural language into shell commands. Supports all Windows and Unix-based systems (Linux, MacOS). 

- [Episode 585 - Choosy Moms Choose Ubuntu @ Linux Unplugged](https://linuxunplugged.com/585).]]>
            </summary>
            <updated>2025-08-29T00:42:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3161</id>
            <title type="text"><![CDATA[Patched&amp;#039;s Patchwork]]></title>
            <link rel="alternate" href="https://www.patched.codes/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3161"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open source AI. Code Reviews and Docs.
Customizable LLM-enabled workflows to automate reviews, docs and patches.

Patchwork automates development gruntwork like PR reviews, bug fixing, security patching, and more using a self-hosted CLI agent and your preferred LLMs. Try the hosted version here.

- [Patchwork @ GitHub](https://github.com/patched-codes/patchwork).
- [Build your own AutoFix with Patchwork @ Patched](https://www.patched.codes/blog/build-your-own-autofix-with-patchwork).]]>
            </summary>
            <updated>2025-08-29T00:44:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3164</id>
            <title type="text"><![CDATA[Meta Lingua]]></title>
            <link rel="alternate" href="https://github.com/facebookresearch/lingua" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3164"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Meta Lingua: a lean, efficient, and easy-to-hack codebase to research LLMs. 

Meta Lingua is a minimal and fast LLM training and inference library designed for research. Meta Lingua uses easy-to-modify PyTorch components in order to try new architectures, losses, data, etc. We aim for this code to enable end to end training, inference and evaluation as well as provide tools to better understand speed and stability. While Meta Lingua is currently under development, we provide you with multiple apps to showcase how to use this codebase.]]>
            </summary>
            <updated>2025-08-29T00:44:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3204</id>
            <title type="text"><![CDATA[🍓 Ichigo]]></title>
            <link rel="alternate" href="https://github.com/homebrewltd/ichigo" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3204"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Llama3.1 learns to Listen. Local real-time voice AI (Formerly llama3-s).

🍓 Ichigo is an open, ongoing research experiment to extend a text-based LLM to have native &amp;quot;listening&amp;quot; ability. Think of it as an open data, open weight, on device Siri.]]>
            </summary>
            <updated>2025-08-29T00:50:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3212</id>
            <title type="text"><![CDATA[Evidently]]></title>
            <link rel="alternate" href="https://www.evidentlyai.com/evidently-oss" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3212"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-Source ML Monitoring and LLM Observability.

Open-source evaluation and observability for ML and LLM systems
Evaluate, test, and monitor AI-powered systems. From tabular data to LLMs. Built for data scientists, AI, and ML engineers.

- [Evidently @ GitHub](https://github.com/evidentlyai/evidently).]]>
            </summary>
            <updated>2025-08-29T00:52:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3228</id>
            <title type="text"><![CDATA[Arch]]></title>
            <link rel="alternate" href="https://archgw.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3228"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Intelligent Prompt Gateway.

Arch is an intelligent prompt gateway. Engineered with (fast) LLMs for the secure handling, robust observability, and seamless integration of prompts with APIs - all outside business logic. Built by the core contributors of Envoy proxy, on Envoy. 

Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications (agents, assistants, co-pilots) with your APIs.

- [Arch @ GitHub](https://github.com/katanemo/arch).]]>
            </summary>
            <updated>2025-08-29T00:54:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3239</id>
            <title type="text"><![CDATA[OmniParse]]></title>
            <link rel="alternate" href="https://docs.cognitivelab.in/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3239"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[OmniParse is a platform that ingests/parses any unstructured data into structured, actionable data optimized for GenAI (LLM) applications. Whether working with documents, tables, images, videos, audio files, or web pages, OmniParse prepares your data to be clean, structured and ready for AI applications, such as RAG , fine-tuning and more.

- [OmniParse @ GitHub](https://github.com/adithya-s-k/omniparse).]]>
            </summary>
            <updated>2025-08-29T00:56:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3240</id>
            <title type="text"><![CDATA[exo]]></title>
            <link rel="alternate" href="https://github.com/exo-explore/exo" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3240"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚ 

Forget expensive NVIDIA GPUs, unify your existing devices into one powerful GPU: iPhone, iPad, Android, Mac, Linux, pretty much any device!

Related contents:

- [Exo - Pour créer un super cluster IA avec tous les appareils qui trainent chez vous @ Korben :fr:](https://korben.info/exo-cluster-ia-distribue-appareils-gpu.html).
- [I built an AI supercomputer with 5 Mac Studios @ NetworkChuck&amp;#039;s YouTube](https://www.youtube.com/watch?v=Ju0ndy2kwlw).]]>
            </summary>
            <updated>2026-01-15T07:43:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3253</id>
            <title type="text"><![CDATA[Chub - Charater Hub]]></title>
            <link rel="alternate" href="https://www.characterhub.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3253"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[hub to share llm charaters.]]>
            </summary>
            <updated>2025-08-29T00:58:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3254</id>
            <title type="text"><![CDATA[Chub AI]]></title>
            <link rel="alternate" href="https://www.chub.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3254"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Chub is platform that allows you to interact with characters through the use of Artificial Intelligence (AI) Large Language Models (LLMs). These models are accessed through the use of APIs which Chub streamlines into a convenient to use chatbot service.

Chub is uncensored. We do not restrict in any meaningful capacity the variety of characters that are allowed to be posted on the platform nor the type of interactions you are allowed to have with said characters.

Chub AI supports numerous APIs such as OpenAI or Anthropic (Claude), features such as chat trees, exporting/importing chats from existing services, and much more!

- [Chub AI documentation](https://docs.chub.ai/docs).]]>
            </summary>
            <updated>2025-08-29T00:58:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3278</id>
            <title type="text"><![CDATA[Swarm]]></title>
            <link rel="alternate" href="https://github.com/openai/swarm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3278"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.

Related contents:

- [Don’t Build Multi-Agents @ Cognition](https://cognition.ai/blog/dont-build-multi-agents#principles-of-context-engineering).]]>
            </summary>
            <updated>2025-09-17T14:31:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3300</id>
            <title type="text"><![CDATA[Continue]]></title>
            <link rel="alternate" href="https://www.continue.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3300"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Amplified developers, AI-enhanced development.

 ⏩ Continue is the leading open-source AI code assistant. You can connect any models and any context to build custom autocomplete and chat experiences inside VS Code and JetBrains.

- [Continue @ GitHub](https://github.com/continuedev/continue).]]>
            </summary>
            <updated>2025-08-29T01:06:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3301</id>
            <title type="text"><![CDATA[NotebookLM]]></title>
            <link rel="alternate" href="https://notebooklm.google.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3301"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[NotebookLM is an AI-powered research and writing assistant that works best with the sources you import.

- [Behind the product: NotebookLM | Raiza Martin (Senior Product Manager, AI @ Google Labs) @ Lenny&amp;#039;s Newsletter](https://www.lennysnewsletter.com/p/googles-notebooklm-raiza-martin).]]>
            </summary>
            <updated>2025-08-29T01:06:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3308</id>
            <title type="text"><![CDATA[Donobu]]></title>
            <link rel="alternate" href="https://www.donobu.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3308"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Automate dogfoodingfor your team.  Get more eyes on your web app.
Testing your product is now just a simple command away. Get more eyes on your website. Ship with confidence.

Donobu simplifies automation through intuitive prompts, getting you started in no time.]]>
            </summary>
            <updated>2025-08-29T01:08:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3312</id>
            <title type="text"><![CDATA[bolt.new]]></title>
            <link rel="alternate" href="https://bolt.new/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3312"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt, run, edit &amp;amp; deploy web apps.

Bolt.new is an AI-powered web development agent that allows you to prompt, run, edit, and deploy full-stack applications directly from your browser—no local setup required. If you&amp;#039;re here to build your own AI-powered web dev agent using the Bolt open source codebase, click here to get started!

- [bolt.new @ GitHub](https://github.com/stackblitz/bolt.new).

Related contents:

- [098 - Les news web dev pour octobre 2024 - 2.0 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-oct24-2/).
- [No code is dead. Long live vibe coding @ kenneth.io](https://kenneth.io/post/no-code-is-dead-long-live-vibe-coding).]]>
            </summary>
            <updated>2025-08-29T01:08:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3349</id>
            <title type="text"><![CDATA[assistant-ui]]></title>
            <link rel="alternate" href="https://www.assistant-ui.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3349"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build in-app AI chatbots in days, not weeks.

assistant-ui is a chatbot UI for your React app

- [assistant-ui @ GitHub](https://github.com/Yonom/assistant-ui).

Related contents:

- [I Want Everything Local — Building My Offline AI Workspace @ InstaVM](https://instavm.io/blog/building-my-offline-ai-workspace).]]>
            </summary>
            <updated>2025-08-29T01:14:55+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3380</id>
            <title type="text"><![CDATA[screenpipe]]></title>
            <link rel="alternate" href="https://screenpi.pe/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3380"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI powered by what you&amp;#039;ve seen, said, or heard. Alternative to Rewind.ai.

screenpipe records your screens and mics 24/7 safely on your computer, and connects it to AI, creating magic from your data.

- [screenpipe @ GitHub](https://github.com/mediar-ai/screenpipe).]]>
            </summary>
            <updated>2025-08-29T01:20:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3383</id>
            <title type="text"><![CDATA[AutoArena]]></title>
            <link rel="alternate" href="https://www.kolena.com/autoarena/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3383"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Rank LLMs, RAG systems, and prompts using automated judge evaluation.

- [AutoArena @ GitHub](https://github.com/kolenaIO/autoarena).
- [Your October Dose of Data - October 2024 @ Data Council](https://mailchi.mp/datacouncil/october-2024).]]>
            </summary>
            <updated>2025-08-29T01:21:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3400</id>
            <title type="text"><![CDATA[K8sGPT]]></title>
            <link rel="alternate" href="https://k8sgpt.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3400"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Giving Kubernetes Superpowers to everyone.

k8sgpt is a tool for scanning your Kubernetes clusters, diagnosing, and triaging issues in simple English.
It has SRE experience codified into its analyzers and helps to pull out the most relevant information to enrich it with AI.

- [K8sGPT @ GitHub](https://github.com/k8sgpt-ai/k8sgpt).
- [Veille de la semaine du 23 septembre 2024 @ Veille de la semaine&amp;#039;s Substack :fr:](https://guikingone.substack.com/p/veille-de-la-semaine-du-23-septembre).]]>
            </summary>
            <updated>2025-08-29T01:22:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3403</id>
            <title type="text"><![CDATA[PearAI]]></title>
            <link rel="alternate" href="https://trypear.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3403"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source AI Code Editor for Fast Development. The Open Source AI-Powered Code Editor. A fork of VSCode and Continue. 

- [PearAI @ GitHub](https://github.com/trypear/pearai-app).
- [Veille de la semaine du 23 septembre 2024 @ Veille de la semaine&amp;#039;s Substack :fr:](https://guikingone.substack.com/p/veille-de-la-semaine-du-23-septembre).]]>
            </summary>
            <updated>2025-08-29T01:24:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3411</id>
            <title type="text"><![CDATA[HumanifyJS]]></title>
            <link rel="alternate" href="https://github.com/jehna/humanify" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3411"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Deobfuscate Javascript code using LLMs (&amp;quot;AI&amp;quot;)

This tool uses large language modeles (like ChatGPT &amp;amp; llama) and other tools to deobfuscate, unminify, transpile, decompile and unpack Javascript code. Note that LLMs don&amp;#039;t perform any structural changes – they only provide hints to rename variables and functions. The heavy lifting is done by Babel on AST level to ensure code stays 1-1 equivalent.]]>
            </summary>
            <updated>2025-08-29T01:25:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3424</id>
            <title type="text"><![CDATA[Crew AI]]></title>
            <link rel="alternate" href="https://www.crewai.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3424"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. 

- [Crew AI @ GitHub](https://github.com/crewAIInc/crewAI).

Related contents:

- [S5E8 - Votre téléphone vous ment (et c&amp;#039;est fascinant) @ Underscore_&amp;#039;s acast :fr:](https://shows.acast.com/micode-underscore/episodes/s5e8-votre-telephone-vous-ment-et-cest-fascinant).
- [Tour d&amp;#039;horizon des frameworks pour créer des applications basées sur les LLM @ Data-Crafting.io :fr:](https://datacrafting.substack.com/p/tour-dhorizon-des-frameworks-pour).]]>
            </summary>
            <updated>2025-08-29T01:27:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3425</id>
            <title type="text"><![CDATA[AutoGen]]></title>
            <link rel="alternate" href="https://microsoft.github.io/autogen/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3425"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An Open-Source Programming Framework for Agentic AI

- [AutoGen @ GitHub](https://github.com/microsoft/autogen).
- [Tour d&amp;#039;horizon des frameworks pour créer des applications basées sur les LLM @ Data-Crafting.io :fr:](https://datacrafting.substack.com/p/tour-dhorizon-des-frameworks-pour).]]>
            </summary>
            <updated>2025-08-29T01:27:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3426</id>
            <title type="text"><![CDATA[LlamaIndex]]></title>
            <link rel="alternate" href="https://www.llamaindex.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3426"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Data Framework for LLM Applications.

LlamaIndex (GPT Index) is a data framework for your LLM application. Building with LlamaIndex typically involves working with LlamaIndex core and a chosen set of integrations (or plugins). There are two ways to start building with LlamaIndex in Python:

- [LlamaIndex @ GitHub](https://github.com/run-llama/llama_index).

Related contents:

- [Tour d&amp;#039;horizon des frameworks pour créer des applications basées sur les LLM @ Data-Crafting.io :fr:](https://datacrafting.substack.com/p/tour-dhorizon-des-frameworks-pour).
- [7 Lessons from building a small-scale AI application @ Richard Li](https://www.thelis.org/blog/lessons-from-ai).
- [Production RAG: what I learned from processing 5M+ documents @ Abdellatif Abdelfattah](https://blog.abdellatif.io/production-rag-processing-5m-documents).]]>
            </summary>
            <updated>2025-10-21T11:49:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3427</id>
            <title type="text"><![CDATA[🦜️🔗 LangChain]]></title>
            <link rel="alternate" href="https://www.langchain.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3427"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The largest community building the future of LLM apps

LangChain’s flexible abstractions and AI-first toolkit make it the #1 choice for developers when building with GenAI.
Join 1M+ builders standardizing their LLM app development
in LangChain&amp;#039;s Python and JavaScript frameworks.

- [LangChain @ GitHub](https://github.com/langchain-ai).

Related contents:

- [\#307.src - Langchain: Faire de l&amp;#039;IA comme des Lego avec Maxime Thoonsen @ &amp;lt;ifttd&amp;gt;](https://www.ifttd.io/episodes/langchain).
- [Tour d&amp;#039;horizon des frameworks pour créer des applications basées sur les LLM @ Data-Crafting.io :fr:](https://datacrafting.substack.com/p/tour-dhorizon-des-frameworks-pour).
- [\#304.bin - Bilan 2024: Le début de la révolution avec Quentin Adam @ &amp;lt;ifttd&amp;gt;](https://www.ifttd.io/episodes/bilan-2024).
- [Construire son RAG (Retrieval Augmented Generation) grâce à langchain: L’exemple de l’Helpdesk d’OCTO @ OCTO talks :fr:](https://blog.octo.com/le-chatbot-docto-langchain-rag-et-code-associe).
- [CLI Chatbot with LangChain and OpenAI in Node.js @ rw;eruch](https://www.robinwieruch.de/langchain-node-js-openai/).
- [Meetup GenAI - Découverte de LangChain @ Flint&amp;#039;s YouTube :fr:](https://www.youtube.com/watch?v=0ImjWIo5fyM).
- [Agents 2.0: From Shallow Loops to Deep Agents @ PHILSCHMID](https://www.philschmid.de/agents-2.0-deep-agents).
- [Production RAG: what I learned from processing 5M+ documents @ Abdellatif Abdelfattah](https://blog.abdellatif.io/production-rag-processing-5m-documents).
- [Intégration de Google Drive avec langchain @ Octo talks! :fr:](https://blog.octo.com/integration-de-google-drive-avec-langchain).
- [Deux techniques pour ingérer des pages web pour le RAG : BeautifulSoup vs Docling @ lbke :fr:](https://links.biapy.com/links/3427/edit).
- [Créer un RAG avec LangChain en 5 étapes @ lbke :fr:](https://www.lbke.fr/formations/rag-introduction-langchain/rag-avec-langchain).
- [RAG Against The Machine @ Quoi de neuf les devs ? :fr:](https://happytodev.substack.com/p/quoi-de-neuf-les-devs-153-veille?open=false#%C2%A7rag-against-the-machine).
- [LangChain, LangGraph Flaws Expose Files, Secrets, Databases in Widely Used AI Frameworks @ The Hacker News](https://thehackernews.com/2026/03/langchain-langgraph-flaws-expose-files.html).]]>
            </summary>
            <updated>2026-03-30T18:57:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3453</id>
            <title type="text"><![CDATA[Kotaemon]]></title>
            <link rel="alternate" href="https://cinnamon.github.io/kotaemon/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3453"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open-source RAG-based tool for chatting with your documents. 

An open-source clean &amp;amp; customizable RAG UI for chatting with your documents. Built with both end users and developers in mind.

- [Kotaemon @ GitHub](https://github.com/Cinnamon/kotaemon).]]>
            </summary>
            <updated>2025-08-29T01:33:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3455</id>
            <title type="text"><![CDATA[Priompt]]></title>
            <link rel="alternate" href="https://github.com/anysphere/priompt" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3455"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt design using JSX.

Priompt (priority + prompt) is a JSX-based prompting library. It uses priorities to decide what to include in the context window.

Priompt is an attempt at a prompt design library, inspired by web design libraries like React.

- [Prompt Design @ Cursor](https://www.cursor.com/blog/prompt-design).]]>
            </summary>
            <updated>2025-08-29T01:33:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3462</id>
            <title type="text"><![CDATA[Prompt Engineering Guide]]></title>
            <link rel="alternate" href="https://www.promptingguide.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3462"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🐙 Guides, papers, lecture, notebooks and resources for prompt engineering.

Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs).

- [Prompt Engineering Guide @ GitHub](https://github.com/dair-ai/Prompt-Engineering-Guide).
- [AI tools for software engineers, but without the hype – with Simon Willison (co-creator of Django) @ The Pragmatic Engineer](https://newsletter.pragmaticengineer.com/p/ai-tools-for-software-engineers-simon-willison).]]>
            </summary>
            <updated>2025-08-29T01:33:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3467</id>
            <title type="text"><![CDATA[BAML]]></title>
            <link rel="alternate" href="https://docs.boundaryml.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3467"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[BAML is an expressive language for structured text generation.
BAML is a domain-specific language to write and test LLM functions.

In BAML, prompts are treated like functions. An LLM function is a prompt template with some defined input variables, and a specific output type like a class, enum, union, optional string, etc.

With BAML you can write and test a complex LLM function in 1/10 of the time it takes to setup a python LLM testing environment.

- [BAML @ GitHub](https://github.com/boundaryml/baml).]]>
            </summary>
            <updated>2025-08-29T01:34:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3488</id>
            <title type="text"><![CDATA[🤖 Claude Engineer]]></title>
            <link rel="alternate" href="https://github.com/Doriandarko/claude-engineer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3488"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Claude Engineer is an advanced interactive command-line interface (CLI) that harnesses the power of Anthropic&amp;#039;s Claude 3 and Claude 3.5 models to assist with a wide range of software development tasks. This tool seamlessly combines the capabilities of state-of-the-art large language models with practical file system operations, web search functionality, intelligent code analysis, and execution capabilities.

- [Claude Engineer - L&amp;#039;IA qui crée ses propres outils @ Korben :fr:](https://korben.info/claude-engineer-ia-creation-outils-automatisation.html).]]>
            </summary>
            <updated>2025-08-29T01:38:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3499</id>
            <title type="text"><![CDATA[Void]]></title>
            <link rel="alternate" href="https://voideditor.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3499"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The open source AI code editor.

Void is an open source Cursor alternative. Write code with the best AI tools, retain full control over your data, and access powerful AI features.

- [Void @ GitHub](https://github.com/voideditor/void).]]>
            </summary>
            <updated>2025-08-29T01:41:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3531</id>
            <title type="text"><![CDATA[v0]]></title>
            <link rel="alternate" href="https://v0.dev/chat" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3531"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[v0 is a generative user interface system by Vercel powered by AI. It generates copy-and-paste friendly React code based on shadcn/ui and Tailwind CSS that people can use in their projects.

- [094 - Les news web dev pour septembre 2024 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-sept24/).]]>
            </summary>
            <updated>2025-08-29T01:45:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3536</id>
            <title type="text"><![CDATA[Supermaven]]></title>
            <link rel="alternate" href="https://supermaven.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3536"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Free AI Code Completion.

The fastest copilot. Supermaven lets you write code 2x faster with AI.

Related contents:

- [094 - Les news web dev pour septembre 2024 @ Double Slash :fr:](https://double-slash.dev/podcasts/news-sept24/).
- [Sunsetting Supermaven @ Supermaven](https://supermaven.com/blog/sunsetting-supermaven).]]>
            </summary>
            <updated>2025-11-24T12:55:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3537</id>
            <title type="text"><![CDATA[PrivateGPT.dev]]></title>
            <link rel="alternate" href="https://privategpt.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3537"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Local &amp;amp; OnPremise AI. Run LLMs offline. Tap into your private knowledge base.
Interact with your documents using the power of GPT, 100% privately, no data leaks 

PrivateGPT is a production-ready AI project that allows you to ask questions about your documents using the power of Large Language Models (LLMs), even in scenarios without an Internet connection. 100% private, no data leaves your execution environment at any point.

- [PrivateGPT @ GitHub](https://github.com/zylon-ai/private-gpt).]]>
            </summary>
            <updated>2025-08-29T01:46:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3557</id>
            <title type="text"><![CDATA[ell]]></title>
            <link rel="alternate" href="https://docs.ell.so/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3557"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[ell is a lightweight prompt engineering library treating prompts as functions.

- [ell @ GitHub](https://github.com/MadcowD/ell).]]>
            </summary>
            <updated>2025-08-29T01:49:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3576</id>
            <title type="text"><![CDATA[Dot]]></title>
            <link rel="alternate" href="https://dotapp.uk/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3576"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Text-To-Speech, RAG, and LLMs. All local!

Dot is a standalone, open-source application designed for seamless interaction with documents and files using local LLMs and Retrieval Augmented Generation (RAG). It is inspired by solutions like Nvidia&amp;#039;s Chat with RTX, providing a user-friendly interface for those without a programming background. Using the Phi-3 LLM by default, Dot ensures accessibility and simplicity right out of the box.

- [Dot – L’app IA locale pour interagir avec vos documents (RAG) @ Korben :fr:](https://korben.info/dot-app-ia-locale-interagir-documents.html).]]>
            </summary>
            <updated>2025-08-29T01:53:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3666</id>
            <title type="text"><![CDATA[Firecrawl]]></title>
            <link rel="alternate" href="https://www.firecrawl.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3666"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Turn websites into LLM-ready data.

Power your AI apps with clean data crawled from any website. It&amp;#039;s also open-source.
 🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API. 

- [Firecrawl @ GitHub](https://github.com/mendableai/firecrawl).

Related contents:

- [Firecrawl @ GitHub](https://github.com/firecrawl/firecrawl).
- [Firecrawl Observer @ GitHub](https://github.com/firecrawl/firecrawl-observer).

Related contents:

- [🚨 Someone built a tool that turns any website into clean data your AI can actually use @ Nav Toor&amp;#039;s X](https://nitter.net/heynavtoor/status/2031626457110425760).
- [Hermes Agent : veille technique auto-hébergée avec Matrix, FreshRSS et Firecrawl @ Cryptolab :fr:](https://cryptolab.re/posts/2026/hermes-agent-framework-self-hosted/).]]>
            </summary>
            <updated>2026-06-23T05:55:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3685</id>
            <title type="text"><![CDATA[Plandex]]></title>
            <link rel="alternate" href="https://plandex.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3685"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI coding engine for complex tasks. Build complex software with AI.

An open source, terminal-based AI coding engine.
Designed for real-world tasks that span many files.

- [Plandex @ GitHub](https://github.com/plandex-ai/plandex).

Related contents:

- [Plandex – L’assistant qui dev @ Korben :fr:](https://korben.info/plandex-ia-developpeurs-productivite-code.html).]]>
            </summary>
            <updated>2025-08-29T02:10:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3686</id>
            <title type="text"><![CDATA[LLocalSearch]]></title>
            <link rel="alternate" href="https://github.com/nilsherzig/LLocalSearch" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3686"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LLocalSearch is a completely locally running search aggregator using LLM Agents. The user can ask a question and the system will use a chain of LLMs to find the answer. The user can see the progress of the agents and the final answer. No OpenAI or Google API keys are needed. 

- [LLocalSearch – Le moteur de recherche local basé sur des agents IA @ Korben :fr:](https://korben.info/llocalsearch-moteur-recherche-local-agents-ia.html).]]>
            </summary>
            <updated>2025-08-29T02:11:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3699</id>
            <title type="text"><![CDATA[Visual Copilot]]></title>
            <link rel="alternate" href="https://www.builder.io/m/design-to-code" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3699"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Design to Code. Automated.

Turn days into minutes by bringing AI into your design-to-code workflow. Convert Figma designs into clean code with Visual Copilot.

- [Good Refactoring vs Bad Refactoring @ builder.io](https://www.builder.io/blog/good-vs-bad-refactoring).]]>
            </summary>
            <updated>2025-08-29T02:13:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3719</id>
            <title type="text"><![CDATA[GraphRAG]]></title>
            <link rel="alternate" href="https://microsoft.github.io/graphrag/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3719"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs.

GraphRAG is a structured, hierarchical approach to Retrieval Augmented Generation (RAG), as opposed to naive semantic-search approaches using plain text snippets. The GraphRAG process involves extracting a knowledge graph out of raw text, building a community hierarchy, generating summaries for these communities, and then leveraging these structures when perform RAG-based tasks.

- [GraphRAG @ GitHub](https://github.com/microsoft/graphrag).
- [GraphRAG: Microsoft’s Open-Source Solution for Enhanced Document Understanding @ Towards AI&amp;#039;s Medium](https://pub.towardsai.net/graphrag-microsofts-open-source-solution-for-enhanced-document-understanding-b42d05f5fec5).]]>
            </summary>
            <updated>2025-08-29T02:17:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3773</id>
            <title type="text"><![CDATA[InstructLab]]></title>
            <link rel="alternate" href="https://instructlab.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3773"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A new community-based approach to build truly open-source LLMs.

InstructLab Command-Line Interface. Use this to chat with a model and execute the InstructLab workflow to train a model using custom taxonomy data. 

- [InstructLab 🐶 (ilab) @ GitHub](https://github.com/instructlab/instructlab).
- [Spécial été 2024 : retour sur la conférence WeAreDevs et les tendances Tech @ AXOPEN YouTube :fr:](https://www.youtube.com/watch?v=daVHfuM1ios).
- [InstructLab: Advancing generative AI through open source @ Red Hat Developer](https://developers.redhat.com/articles/2024/05/07/instructlab-open-source-generative-ai).]]>
            </summary>
            <updated>2025-08-29T02:25:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3805</id>
            <title type="text"><![CDATA[Dioptra]]></title>
            <link rel="alternate" href="https://pages.nist.gov/dioptra/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3805"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Dioptra is a software test platform for assessing the trustworthy characteristics of artificial intelligence (AI). Trustworthy AI is: valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair - with harmful bias managed1. Dioptra supports the Measure function of the NIST AI Risk Management Framework by providing functionality to assess, analyze, and track identified AI risks.

- [Dioptra @ GitHub](https://github.com/usnistgov/dioptra).]]>
            </summary>
            <updated>2025-08-29T02:30:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3807</id>
            <title type="text"><![CDATA[X-CMD]]></title>
            <link rel="alternate" href="https://www.x-cmd.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3807"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your AI-Powered Excalibur in Cloud.  X bootstrap 1000+ tools and your scripts. 

Lightweight POSIX script for managing tools (500+) and providing classic command extensions in an open-source environment.

- [X-CMD @ GitHub](https://github.com/x-cmd/x-cmd).]]>
            </summary>
            <updated>2025-08-29T02:31:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3841</id>
            <title type="text"><![CDATA[Verba]]></title>
            <link rel="alternate" href="https://github.com/weaviate/Verba" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3841"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Retrieval Augmented Generation (RAG) chatbot powered by Weaviate.

Welcome to Verba: The Golden RAGtriever, an open-source application designed to offer an end-to-end, streamlined, and user-friendly interface for Retrieval-Augmented Generation (RAG) out of the box. In just a few easy steps, explore your datasets and extract insights with ease, either locally with HuggingFace and Ollama or through LLM providers such as OpenAI, Cohere, and Google.]]>
            </summary>
            <updated>2025-08-29T02:37:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3863</id>
            <title type="text"><![CDATA[CommandAI]]></title>
            <link rel="alternate" href="https://commandai.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3863"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Command Line Utilities With The Power of AI.

 Experience the power of Command AI: your AI-powered command line companion that makes complex tasks simple and intuitive. 

- [CommandAI @ GitHub](https://github.com/CommandAI/ai-cli).]]>
            </summary>
            <updated>2025-08-29T02:41:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3864</id>
            <title type="text"><![CDATA[Mutable.ai]]></title>
            <link rel="alternate" href="https://mutable.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3864"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Create an AI expert for any codebase]]>
            </summary>
            <updated>2025-08-29T02:41:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3867</id>
            <title type="text"><![CDATA[Perplexica]]></title>
            <link rel="alternate" href="https://github.com/ItzCrazyKns/Perplexica/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3867"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI.

Perplexica is an open-source AI-powered searching tool or an AI-powered search engine that goes deep into the internet to find answers. Inspired by Perplexity AI, it&amp;#039;s an open-source option that not just searches the web but understands your questions. It uses advanced machine learning algorithms like similarity searching and embeddings to refine results and provides clear answers with sources cited.

- [Perplexica – Le moteur de recherche open source propulsé à l’IA @ Korben :fr:](https://korben.info/perplexica-outil-open-source-revolutionne-recherche-web.html).]]>
            </summary>
            <updated>2025-08-29T02:41:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3880</id>
            <title type="text"><![CDATA[say]]></title>
            <link rel="alternate" href="https://github.com/8ta4/say" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3880"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[say is always on, recording and transcribing your voice 24/7. Whenever inspiration strikes, just say it.]]>
            </summary>
            <updated>2025-08-29T02:43:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3921</id>
            <title type="text"><![CDATA[Celp]]></title>
            <link rel="alternate" href="https://www.celp.ai/?sc=2710522184f852cc1f70f5bb8057466bc8ea5681d" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3921"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Write code, not tests.

Contextually Aware AI-Driven Unit Test Generation for Typescript Node.js projects.
Celp generates contextually relevant unit tests for Typescript node.js projects, saving you hours.]]>
            </summary>
            <updated>2025-08-29T02:49:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3922</id>
            <title type="text"><![CDATA[LLM Benchmark]]></title>
            <link rel="alternate" href="https://llm.aidatatools.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3922"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Benchmark Throughput Performance with running local large language models (LLMs) via ollama. 

- [llm-benchmark (ollama-benchmark) @ GitHub](https://github.com/aidatatools/ollama-benchmark).]]>
            </summary>
            <updated>2025-08-29T02:50:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3923</id>
            <title type="text"><![CDATA[translateLocally]]></title>
            <link rel="alternate" href="https://github.com/XapaJIaMnu/translateLocally" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3923"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fast and secure translation on your local machine, powered by marian and Bergamot.

- [private.mt](https://private.mt/).
- [TranslateLocally – De la traduction rapide et sécurisée sur votre ordinateur @ Korben :fr:](https://korben.info/translatelocally-traduction-rapide-securisee-ordinateur.html).]]>
            </summary>
            <updated>2025-08-29T02:50:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3968</id>
            <title type="text"><![CDATA[ChatMD]]></title>
            <link rel="alternate" href="https://chatmd.forge.apps.education.fr/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3968"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open source chatbot that can be personalized using a markdown file.

- [ChatMD @ forge.apps.education.fr](https://forge.apps.education.fr/chatMD/chatMD.forge.apps.education.fr).]]>
            </summary>
            <updated>2025-08-29T02:57:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4027</id>
            <title type="text"><![CDATA[Open WebUI]]></title>
            <link rel="alternate" href="https://openwebui.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4027"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Unlock your LLM&amp;#039;s creativity.  User-friendly WebUI for LLMs (Formerly Ollama WebUI) 

Open WebUI is an extensible, self-hosted interface for AI that adapts to your workflow, all while operating entirely offline.

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted WebUI designed to operate entirely offline. It supports various LLM runners, including Ollama and OpenAI-compatible APIs. For more information, be sure to check out our Open WebUI Documentation.

- [Open WebUi @ GitHub](https://github.com/open-webui/open-webui).

Related contents:

- [host ALL your AI locally @ NetworkChuck&amp;#039;s YouTube](https://www.youtube.com/watch?v=Wjrdr0NU4Sk).
- [DeepSeek Local: How to Self-Host DeepSeek (Privacy and Control) @ LinuxBlog.io](https://linuxblog.io/deepseek-local-self-host/).
- [Self-Hosted Private LLM using Ollama and Open WebUI @ Getting Started](https://www.gettingstarted.ai/self-host-llm/)h
- [LLMs on Kubernetes Part 1: Understanding the threat model @ CNCF](https://www.cncf.io/blog/2026/03/30/llms-on-kubernetes-part-1-understanding-the-threat-model/).]]>
            </summary>
            <updated>2026-04-07T05:46:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4062</id>
            <title type="text"><![CDATA[C2PA]]></title>
            <link rel="alternate" href="https://c2pa.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4062"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Coalition for Content Provenance and Authenticity.

An open technical standard providing publishers, creators, and consumers the ability to trace the origin of different types of media. 

- [C2PA @ GitHub](https://github.com/c2pa-org).

Related contents:

- [481 : Episode du 12 février 2025 @ Les Technos :fr:](https://lestechnos.be/les-technos-481-episode-du-12-fevrier/).]]>
            </summary>
            <updated>2025-08-29T03:14:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4117</id>
            <title type="text"><![CDATA[Auto-News]]></title>
            <link rel="alternate" href="https://github.com/finaldie/auto-news" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4117"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An Automatic News Aggregator with LLM.

A personal news aggregator to pull information from multi-sources + LLM (ChatGPT via LangChain) to help us reading efficiently with less noises, the sources including: Tweets, RSS, YouTube, Web Articles, Reddit, and personal Journal notes. 

- [Auto-News – L’agrégateur de news qui vous permet d’éviter le « bruit » @ Korben :fr:](https://korben.info/auto-news-agregateur-news-automatise-ia-lecture-efficace-2.html).]]>
            </summary>
            <updated>2025-08-29T03:23:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4174</id>
            <title type="text"><![CDATA[Devika]]></title>
            <link rel="alternate" href="https://github.com/stitionai/devika" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4174"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika aims to be a competitive open-source alternative to Devin by Cognition AI.

- [Devika – Votre ingénieur logiciel personnel @ Korben :fr:](https://korben.info/devika-ia-revolutionnaire-developpement-logiciel.html).]]>
            </summary>
            <updated>2025-08-29T03:32:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4183</id>
            <title type="text"><![CDATA[Aider]]></title>
            <link rel="alternate" href="https://aider.chat/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4183"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Aider lets you pair program with LLMs, to edit code in your local git repository. Start a new project or work with an existing git repo. Aider works best with GPT-4o and Claude 3 Opus and can connect to almost any LLM.

- [Aider @ GitHub](https://github.com/paul-gauthier/aider).

Related contents:

- [Aider: Using uv as an installer @ Simon Willison’s Weblog](https://simonwillison.net/2025/Mar/6/aider-using-uv-as-an-installer/).]]>
            </summary>
            <updated>2025-08-29T03:34:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4243</id>
            <title type="text"><![CDATA[Activepieces]]></title>
            <link rel="alternate" href="https://www.activepieces.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4243"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open source no-code business automation · Zapier open source alternative.

 Your friendliest open source all-in-one automation tool ✨ Workflow automation tool 100+ integration / Enterprise automation tool / Zapier, n8n, ifttt Alternative 

- [Activepieces @ GitHub](https://github.com/activepieces/activepieces).]]>
            </summary>
            <updated>2025-08-29T03:44:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4300</id>
            <title type="text"><![CDATA[Albert]]></title>
            <link rel="alternate" href="https://github.com/etalab-ia/albert" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4300"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Backend ressources for Albert. Albert, also known as LIA (Legal Information Assistant), is a conversational agent that uses official French data sources to answer administrative agents questions.]]>
            </summary>
            <updated>2025-08-29T03:54:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4372</id>
            <title type="text"><![CDATA[Ferret]]></title>
            <link rel="alternate" href="https://github.com/apple/ml-ferret" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4372"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Refer and Ground Anything Anywhere at Any Granularity.

An End-to-End MLLM that Accept Any-Form Referring and Ground Anything in Response.

- [🚀🚀Introducing Ferret, a new MLLM that can refer and ground anything anywhere at any granularity @ Zhe Gan&amp;#039;s Twitter](https://twitter.com/zhegan4/status/1712345137983201716).
- [Apple&amp;#039;s &amp;#039;Ferret&amp;#039; is a new open-source machine learning model @ Apple Insider](https://appleinsider.com/articles/23/12/24/apples-ferret-is-a-new-open-source-machine-learning-model).
- [s4e13 - UNDERSCORE_ : $50 000 pour hacker l&amp;#039;IA de Google ! @ Micode&amp;#039;s Twitch :fr:](https://www.twitch.tv/videos/2103081056).]]>
            </summary>
            <updated>2025-08-29T04:06:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4389</id>
            <title type="text"><![CDATA[llamafile]]></title>
            <link rel="alternate" href="https://mozilla-ai.github.io/llamafile/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4389"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Distribute and run LLMs with a single file.

Our goal is to make open LLMs much more accessible to both developers and end users. We&amp;#039;re doing that by combining llama.cpp with Cosmopolitan Libc into one framework that collapses all the complexity of LLMs down to a single-file executable (called a &amp;quot;llamafile&amp;quot;) that runs locally on most computers, with no installation.

- [llamafile @ GitHub](https://github.com/mozilla-ai/llamafile).

Related contents:

- [LLaMA Now Goes Faster on CPUs @ justine&amp;#039;s web page](https://justine.lol/matmul/).
- [Justine Tunney booste encore une fois les performances de llama.cpp @ Korben :fr:](https://korben.info/justine-tunney-booste-performances-llama-cpp-nouveaux-kernels-algebre-lineaire.html).
- [Llamafile - Exécutez des modèles de langage en un seul fichier ! @ Korben :fr:](https://korben.info/llamafile-executez-modeles-langage-fichier.html).]]>
            </summary>
            <updated>2026-03-23T16:22:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4411</id>
            <title type="text"><![CDATA[Jan]]></title>
            <link rel="alternate" href="https://jan.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4411"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Rethink the Computer. Turn your computer into an AI machine.

Jan is an open source alternative to ChatGPT that runs 100% offline on your computer.

- [Jan @ GitHub](https://github.com/janhq/jan).

Related contents:

- [Jan – Le « ChatGPT » local et open source à installer sur votre machine @ Korben :fr:](https://korben.info/jan-open-source-chatgpt-alternative-hors-ligne-personnalisable.html).]]>
            </summary>
            <updated>2025-08-29T04:12:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4432</id>
            <title type="text"><![CDATA[MIA :fr:]]></title>
            <link rel="alternate" href="https://www.mia-app.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4432"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[La plateforme d&amp;#039;IA qui simplifie l&amp;#039;analyse des données à tous les métiers. Piloter aujourd&amp;#039;hui. Anticiper demain. Dès maintenant.

MIA est une solution No Code d’analyse de données, basée sur l’Intelligence Artificielle, qui s&amp;#039;adapte à votre profil. Simple. Efficace. Rapide

- [261 - No code pour l’IA - Pascal Corrotti @ &amp;lt;ifttd&amp;gt; :fr:](https://www.ifttd.io/episodes/no-code-pour-l-ia).]]>
            </summary>
            <updated>2025-08-29T04:15:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4493</id>
            <title type="text"><![CDATA[Floneum]]></title>
            <link rel="alternate" href="https://floneum.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4493"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A toolkit for controllable, private AI on consumer hardware in rust.

Floneum is a graph editor that makes it easy to develop your own AI workflows.
Floneum allows you to build workflows that use large language models with a simple drag and drop interface.

- [Floneum @ GitHub](https://github.com/floneum/floneum).
- [S4E10 - Quel destin pour l’Apple Vision Pro ? @ Underscore_&amp;#039;s Acast :fr:](https://shows.acast.com/micode-underscore/episodes/s4e10-quel-destin-pour-lapple-vision-pro).]]>
            </summary>
            <updated>2025-08-29T04:26:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4646</id>
            <title type="text"><![CDATA[Tabby]]></title>
            <link rel="alternate" href="https://tabby.tabbyml.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4646"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Opensource, self-hosted AI coding assistant.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. 

- [Tabby @ GitHub](https://github.com/TabbyML/tabby).
- [Tabby, mon Copilot libre @ Devoxx FR&amp;#039;s YouTube :fr:](https://www.youtube.com/watch?v=ZAVIXXQDtbM).
- [086 - Les news web dev pour Mai 2024 - partie 2 @ Double Slash :fr:](https://double-slash.dev/podcasts/news05-2-24/).]]>
            </summary>
            <updated>2025-08-29T04:50:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4727</id>
            <title type="text"><![CDATA[Mistral AI :fr:]]></title>
            <link rel="alternate" href="https://mistral.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4727"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open source models

- [Mistral Transformer @ GitHub](https://github.com/mistralai/mistral-src).

Related content:

- [S5E6 - On reçoit le PDG de Mistral, Arthur Mensch @ Underscore_&amp;#039;s acast :fr:](https://shows.acast.com/micode-underscore/episodes/s5e6-on-recoit-le-pdg-de-mistral-arthur-mensch).
- [Mistral AI lance son premier LLM : ouvert, mais jusqu’où ? @ Silicon :fr:](https://www.silicon.fr/mistral-ai-llm-471793.html).
- [Comment la communauté s’empare du modèle ouvert de Mistral AI @ Silicon :fr:](https://www.silicon.fr/communaute-modele-ouvert-mistral-ai-473858.html).]]>
            </summary>
            <updated>2025-08-29T05:04:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4733</id>
            <title type="text"><![CDATA[Vigil]]></title>
            <link rel="alternate" href="https://vigil.deadbits.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4733"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs.

Vigil is a Python library and REST API for assessing Large Language Model prompts and responses against a set of scanners to detect prompt injections, jailbreaks, and other potential risks. 

- [Vigil @ GitHub](https://github.com/deadbits/vigil-llm).
- [Vigil: Open-source LLM security scanner](https://www.helpnetsecurity.com/2023/11/29/vigil-llm-security-scanner/).]]>
            </summary>
            <updated>2025-08-29T05:06:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4776</id>
            <title type="text"><![CDATA[Giskard]]></title>
            <link rel="alternate" href="https://www.giskard.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4776"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source Solution for AI Quality.
The testing framework dedicated to ML models, from tabular to LLMs
Scan AI models to detect risks of biases, performance issues and errors. In 4 lines of code. 

- [Giskard @ GitHub](https://github.com/Giskard-AI/giskard).
- [Introduction to Giskard: Open-Source Quality Management for AI Models @ KDnuggets](https://www.kdnuggets.com/2023/11/giskard-introduction-giskard-opensource-quality-management-ai-models).]]>
            </summary>
            <updated>2025-08-29T05:12:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4786</id>
            <title type="text"><![CDATA[Doctor Dignity]]></title>
            <link rel="alternate" href="https://github.com/llSourcell/Doctor-Dignity/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4786"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Doctor Dignity is an LLM that can pass the US Medical Licensing Exam. It works offline, it&amp;#039;s cross-platform, &amp;amp; your health data stays private. 

- [Doctor Dignity – L’IA médicale open-source @ Korben :fr:](https://korben.info/doctor-dignity-intelligence-artificielle-medecine-open-source.html).]]>
            </summary>
            <updated>2025-08-29T05:15:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4794</id>
            <title type="text"><![CDATA[Pezzo]]></title>
            <link rel="alternate" href="https://pezzo.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4794"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Ship AI features in minutes.
Pezzo enables you to build, test, monitor and instantly ship AI all in one platform, while constantly optimizing for cost and performance.

 🕹️ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more. 

- [Pezzo @ GitHub](https://github.com/pezzolabs/pezzo).]]>
            </summary>
            <updated>2025-08-29T05:16:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4873</id>
            <title type="text"><![CDATA[CodeGeeX]]></title>
            <link rel="alternate" href="https://codegeex.cn/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4873"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Multilingual Code Generation Tool.

We introduce CodeGeeX, a large-scale multilingual code generation model with 13 billion parameters, pre-trained on a large code corpus of more than 20 programming languages. As of June 22, 2022, CodeGeeX has been trained on more than 850 billion tokens on a cluster of 1,536 Ascend 910 AI Processors.

- [CodeGeeX2  @ GitHub](https://github.com/THUDM/CodeGeeX2).
- [CodeGeeX @ GitHub](https://github.com/THUDM/CodeGeeX).]]>
            </summary>
            <updated>2025-08-29T05:29:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4934</id>
            <title type="text"><![CDATA[Text generation web UI]]></title>
            <link rel="alternate" href="https://github.com/oobabooga/text-generation-webui" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4934"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Gradio web UI for Large Language Models. Supports transformers, GPTQ, llama.cpp (GGUF), Llama models.]]>
            </summary>
            <updated>2025-08-29T05:39:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4975</id>
            <title type="text"><![CDATA[txtai]]></title>
            <link rel="alternate" href="https://neuml.github.io/txtai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4975"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.

[txtai @ GitHub](https://github.com/neuml/txtai).]]>
            </summary>
            <updated>2025-08-29T05:47:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4992</id>
            <title type="text"><![CDATA[promptmap]]></title>
            <link rel="alternate" href="https://github.com/utkusen/promptmap" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4992"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[automatically tests prompt injection attacks on ChatGPT instances.

Prompt injection is a type of security vulnerability that can be exploited to control the behavior of a ChatGPT instance. By injecting malicious prompts into the system, an attacker can force the ChatGPT instance to do unintended actions.]]>
            </summary>
            <updated>2025-08-29T05:49:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5013</id>
            <title type="text"><![CDATA[LIDA]]></title>
            <link rel="alternate" href="https://microsoft.github.io/lida/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5013"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Automatic Generation of Visualizations and Infographics with LLMs.

LIDA is a library for generating data visualizations and data-faithful infographics. LIDA is grammar agnostic (will work with any programming language and visualization libraries e.g. matplotlib, seaborn, altair, d3 etc) and works with multiple large language model providers (OpenAI, PaLM, Cohere, Huggingface). Details on the components of LIDA are described in the paper here and in this tutorial notebook. See the project page here for updates!.

[LIDA @ GitHub](https://github.com/microsoft/lida).]]>
            </summary>
            <updated>2025-08-29T05:52:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5021</id>
            <title type="text"><![CDATA[SQLCoder]]></title>
            <link rel="alternate" href="https://github.com/defog-ai/sqlcoder" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5021"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Defog&amp;#039;s SQLCoder is a state-of-the-art LLM for converting natural language questions to SQL queries.]]>
            </summary>
            <updated>2025-08-29T05:53:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5085</id>
            <title type="text"><![CDATA[Learn Prompting]]></title>
            <link rel="alternate" href="https://learnprompting.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5085"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Guide to Communicating with Artificial Intelligence.

Learn how to use ChatGPT and other AI tools to accomplish your goals using our free and open source curriculum, designed for all skill levels!

[Learn Prompting @ GitHub](https://github.com/trigaten/Learn_Prompting).]]>
            </summary>
            <updated>2025-08-29T06:04:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5155</id>
            <title type="text"><![CDATA[Ollama]]></title>
            <link rel="alternate" href="https://ollama.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5155"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Get up and running with large language models, locally.
Run Llama 2 and other models on macOS. Customize and create your own.

- [Ollama @ GitHub](https://github.com/jmorganca/ollama).
- [6 outils de FOU pour les DEVS 🤯 @ YoanDev&amp;#039;s YouTube](https://www.youtube.com/watch?v=x0niOhjzkxw).]]>
            </summary>
            <updated>2025-08-29T06:16:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5198</id>
            <title type="text"><![CDATA[OpenLLM]]></title>
            <link rel="alternate" href="https://github.com/bentoml/OpenLLM" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5198"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Operating LLMs in production.

An open platform for operating large language models (LLMs) in production.
Fine-tune, serve, deploy, and monitor any LLMs with ease.]]>
            </summary>
            <updated>2025-08-29T06:23:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5287</id>
            <title type="text"><![CDATA[LibreTranslate]]></title>
            <link rel="alternate" href="https://libretranslate.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5287"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Free and Open Source Machine Translation API. Self-hosted, offline capable and easy to setup. 

Unlike other APIs, it doesn&amp;#039;t rely on proprietary providers such as Google or Azure to perform translations. Instead, its translation engine is powered by the open source Argos Translate library.

- [LibreTranslate @ GitHub](https://github.com/LibreTranslate/LibreTranslate)]]>
            </summary>
            <updated>2025-08-29T06:37:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5387</id>
            <title type="text"><![CDATA[Milvus]]></title>
            <link rel="alternate" href="https://milvus.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5387"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment.

- [Milvus @ GitHub](https://github.com/milvus-io/milvus).

Related contents:

- [RAG Against The Machine @ Quoi de neuf les devs ? :fr:](https://happytodev.substack.com/p/quoi-de-neuf-les-devs-153-veille?open=false#%C2%A7rag-against-the-machine).]]>
            </summary>
            <updated>2025-10-29T13:14:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5400</id>
            <title type="text"><![CDATA[Faraday.dev]]></title>
            <link rel="alternate" href="https://faraday.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5400"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run open-source LLMs on your computer. Works offline. Zero configuration.]]>
            </summary>
            <updated>2025-08-29T06:56:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5403</id>
            <title type="text"><![CDATA[Falcon LLM]]></title>
            <link rel="alternate" href="https://falconllm.tii.ae/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5403"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Falcon LLM is a foundational large language model (LLM) with 40 billion parameters trained on one trillion tokens. TII has now released Falcon LLM – a 40B model.]]>
            </summary>
            <updated>2025-08-29T06:57:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5423</id>
            <title type="text"><![CDATA[RedPajama-Data]]></title>
            <link rel="alternate" href="https://github.com/togethercomputer/RedPajama-Data" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5423"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The RedPajama-Data repository contains code for preparing large datasets for training large language models.
RedPajama-Data: An Open Source Recipe to Reproduce LLaMA training dataset.]]>
            </summary>
            <updated>2025-08-29T07:00:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5502</id>
            <title type="text"><![CDATA[StableLM:]]></title>
            <link rel="alternate" href="https://github.com/stability-AI/stableLM/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5502"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Stability AI Language Models.

This repository contains Stability AI&amp;#039;s ongoing development of the StableLM series of language models and will be continuously updated with new checkpoints. The following provides an overview of all currently available models. More coming soon.]]>
            </summary>
            <updated>2025-08-29T07:14:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6633</id>
            <title type="text"><![CDATA[DeepPavlov]]></title>
            <link rel="alternate" href="https://deeppavlov.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6633"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An open source conversational AI framework.
DeepPavlov makes it easy for beginners and experts to create dialogue systems.

- [DeepPavlov @ GitHub](https://github.com/deeppavlov/DeepPavlov).
- [DeepPavlov Agent @ GitHub](https://github.com/deeppavlov/dp-agent).

Related contents:

- [DeepPavlov Agent: Open-source Framework for Multiskill Conversational AI - ML Conf EU 2020 @ GitNation](https://gitnation.com/contents/deeppavlov-agent-open-source-framework-for-multiskill-conversational-ai).]]>
            </summary>
            <updated>2025-08-29T10:22:41+00:00</updated>
        </entry>
    </feed>
