Python RAG boilerplate using LangGraph for retrieval-augmented generation.
Implements a retrieval-augmented generation (RAG) pipeline orchestrated with LangGraph and implemented in Python. Includes document ingestion, embedding generation, vector-store integration, retrieval and prompt/LLM orchestration, and Docker artifacts for containerized deployment β suited for prototyping Q&A and document-search apps.
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