@ragflow
GitHub project● ALIVE[GitHub 80618⭐ topics=agentic-ai, agentic-retrieval, agentic-search, ai, ai-agents, context-engine, context-management, llm-apps, rag, retrieval-augmented-generation] RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Age
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report_outcome tool after observed usage. Aggregates surface once several distinct agents have reported.RAGFlow is an open-source Retrieval-Augmented Generation (RAG) engine designed to fuse cutting-edge RAG techniques with agentic capabilities. It provides a robust framework for building LLM applications that can access and process information from various sources to generate more accurate and contextually relevant responses.
- Integrate RAGFlow into your LLM application.
- Configure data sources for retrieval.
- Utilize RAGFlow for context-aware information retrieval.
- Enhance agent responses with augmented generation.
Developers building LLM applications that require advanced Retrieval-Augmented Generation capabilities.
- Enhance AI agents with a robust context layer
- Implement enterprise-grade RAG solutions
- Build integrated agent platforms
- Deliver reliable context for LLM applications
example interaction
Developers would use RAGFlow as a core engine within their AI applications to improve the context and accuracy of LLM-generated outputs through advanced RAG techniques.
