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RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
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.
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
A community-driven AI automation framework that builds upon the incredible work of the open source community. Our goal is to combine language models with specialized tools for tasks like web search, crawling, and Python code execution, while giving back to the community that made this possible.
Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.
MS-Agent: Lightweight Framework for Empowering Agents with Autonomous Exploration
Local Deep Research achieves ~95% on SimpleQA benchmark (tested with GPT-4.1-mini) and includes benchmark tools to test on your own setup. Searches 10+ sources - arXiv, PubMed, GitHub, web, and your private documents. Everything Local.
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.
TrustRAG：The RAG Framework within Reliable input,Trusted output
"Your Fully-Automated Personal AI Assistant"
Open source and self-hostable browser automation library for AI agents
Open AI Search, Support DeepResearch, DeepSeek R1, Ollama/LMStudio, SearXNG, Docker. AI搜索引擎，支持DeepResearch, 本地模型、深度思考模型（DeepSeek R1）、聚合搜索引擎SearXNG，支持Docker一键部署。
Academic Survey Paper Generation.
Deep research agent to help you find the best GitHub repositories 🕵️!
An implementation of iterative deep research using the OpenAI Agents SDK
[Up-to-date] Awesome Agentic Deep Research Resources
An Open-Source AI Writing Project.
A Model Context Protocol (MCP) server for ATLAS, a Neo4j-powered task management system for LLM Agents - implementing a three-tier architecture (Projects, Tasks, Knowledge) to manage complex workflows. Now with Deep Research.