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This project implements a Retrieval-Augmented Generation (RAG) system using a Python backend built with FastAPI and Langchain. It allows users to ask questions about documents stored locally, leveraging various LLM and embedding providers like Ollama, OpenAI, Azure, and Bedrock.

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savg92/ai_agent_app

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This project implements a Retrieval-Augmented Generation (RAG) system using a Python backend built with FastAPI and Langchain. It allows users to ask questions about documents stored locally, leveraging various LLM and embedding providers like Ollama, OpenAI, Azure, and Bedrock.

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