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🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.

🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/

Semantic cache for LLMs. Fully integrated with LangChain and llama_index.

🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓

Data framework for your LLM applications. Focus on server side solution

🧠 AI-powered enterprise search engine 🔎

💬 RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram

The Continuous-Improvement Stack for Agents. Our environment data and evals power agent improvement and monitoring.

An LLM-powered repository agent designed to assist developers and teams in generating documentation and understanding repositories quickly.

ChatGPT for lecture slides