Awesome Chatgpt

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

[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation

Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain

📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG

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

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.

Unified framework for building enterprise RAG pipelines with small, specialized models

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

Retrieval and Retrieval-augmented LLMs

Pocket Flow: 100-line LLM framework. Let Agents build Agents!

~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.

AutoRAG: Now your agent can find anything in your computer. It gets smarter if you are using it frequently.

Harness LLMs with Multi-Agent Programming

All-in-one platform for search, recommendations, RAG, and analytics offered via API

The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together seamlessly to build and iterate on AI applications.