An open-source engine for Retrieval-Augmented Generation (RAG) that integrates agent capabilities to enhance LLM context.
RAGFlow offers a sophisticated context layer for LLMs by combining RAG with agentic workflows. It processes and retrieves information to ground LLM responses, allowing for more informed and accurate outputs. Key functionalities involve document indexing and intelligent retrieval mechanisms.
An open-source engine for Retrieval-Augmented Generation (RAG) that integrates agent capabilities to enhance LLM context.
Developers building AI applications that require accurate, context-aware LLM interactions.
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