ragflow and deep-thinking-rag
About ragflow
infiniflow/ragflow
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
This tool helps create advanced AI assistants that can accurately answer questions using your specific business documents and data. You input various documents like PDFs, Word files, web pages, and even structured data, and it outputs a system that provides precise, traceable answers. It's designed for business leaders, knowledge managers, or AI product developers who need to build reliable question-answering systems for internal teams or customers.
About deep-thinking-rag
FareedKhan-dev/deep-thinking-rag
A Deep Thinking RAG Pipeline to Solve Complex Queries
Implements a multi-stage agentic RAG system that decomposes complex queries into structured research plans, then iteratively retrieves, reranks, and synthesizes evidence using supervisor agents, cross-encoders, and hybrid search strategies (vector/keyword/semantic). Built on LangChain with configurable LLM providers, it includes self-critique and policy-based control flow to decide when to refine the plan, continue research, or synthesize final answers—enabling multi-hop reasoning across both internal documents and web sources.
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