langchain
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.
Related contents:
The Context Optimization Layer for LLM Applications.
Cut your LLM costs by 50-90% without losing accuracy.
An Open-Source Asynchronous Coding Agent.
Open SWE is an open-source cloud-based asynchronous coding agent built with LangGraph. It autonomously understands codebases, plans solutions, and executes code changes across entire repositories—from initial planning to opening pull requests.
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
Related contents:
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows.
Related contents:
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's Python and JavaScript frameworks.
Related contents:
- #307.src - Langchain: Faire de l'IA comme des Lego avec Maxime Thoonsen @ <ifttd>.
- Tour d'horizon des frameworks pour créer des applications basées sur les LLM @ Data-Crafting.io :fr:.
- #304.bin - Bilan 2024: Le début de la révolution avec Quentin Adam @ <ifttd>.
- Construire son RAG (Retrieval Augmented Generation) grâce à langchain: L’exemple de l’Helpdesk d’OCTO @ OCTO talks :fr:.
- CLI Chatbot with LangChain and OpenAI in Node.js @ rw;eruch.
- Meetup GenAI - Découverte de LangChain @ Flint's YouTube :fr:.
- Agents 2.0: From Shallow Loops to Deep Agents @ PHILSCHMID.
- Production RAG: what I learned from processing 5M+ documents @ Abdellatif Abdelfattah.
- Intégration de Google Drive avec langchain @ Octo talks! :fr:.
- Deux techniques pour ingérer des pages web pour le RAG : BeautifulSoup vs Docling @ lbke :fr:.
- Créer un RAG avec LangChain en 5 étapes @ lbke :fr:.
- RAG Against The Machine @ Quoi de neuf les devs ? :fr:.
- LangChain, LangGraph Flaws Expose Files, Secrets, Databases in Widely Used AI Frameworks @ The Hacker News.
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.