langchain
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
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LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows.
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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.
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- #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:.
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.