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  # 🤖 RAG Q&A API - Intelligent Document Query System
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  > A production-ready Retrieval-Augmented Generation (RAG) API that answers questions using custom knowledge bases. Built to demonstrate enterprise-grade AI/ML development skills.
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- <div style="display: flex; gap: 8px;">
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- <a href="./docs" target="_blank">
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- <img src="https://img.shields.io/badge/API-Try%20it%20Live-green?style=for-the-badge&logo=fastapi" alt="Try the Live API">
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- </a>
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- <a href="https://github.com/Manavraj-0/gemini_rag_api" target="_blank">
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- <img src="https://img.shields.io/badge/Code-View%20on%20GitHub-blue?style=for-the-badge&logo=github" alt="View on GitHub">
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- </a>
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- </div>
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+ title: Gemini RAG Q&A API
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+ emoji: 🤖
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+ sdk: static
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  # 🤖 RAG Q&A API - Intelligent Document Query System
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  > A production-ready Retrieval-Augmented Generation (RAG) API that answers questions using custom knowledge bases. Built to demonstrate enterprise-grade AI/ML development skills.
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+ [![Live Demo](https://img.shields.io/badge/Demo-Live-success)](https://huggingface.co/spaces/Manavraj/gemini_rag_api)
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+ [![Python 3.10+](https://img.shields.io/badge/Python-3.10+-blue)](https://www.python.org/)
 
 
 
 
 
 
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