📜 Doc_Query_Genie

🚀 A Powerful Retrieval-Augmented Generation (RAG) API using LLama3, LangChain, Ollama, and ChromaDB

🔍 About The Project

Doc_Query_Genie is a cutting-edge RAG-based Python solution that enhances information retrieval and generation using Flask API. With the power of LLama3, LangChain, Ollama, and ChromaDB, this tool provides a seamless experience for querying both general knowledge and custom document uploads.

✨ Key Features

✅ AI-Powered Chat – Use it like OpenAI's ChatGPT to ask any question.
✅ PDF Intelligence – Upload a PDF and ask context-specific questions.
✅ Source Referencing – Get precise answers with citations from the document (paragraph/line references).
✅ Fast & Efficient – Optimized for quick and reliable response generation.
✅ Easy Integration – Simple API setup to integrate with other applications.

This project brings the best of AI-driven retrieval and context-aware generation, making it a versatile tool for researchers, students, and professionals.

🚀 Getting Started

1. Clone the repository

   git clone https://github.com/yourusername/Doc_Query_Genie.git  
   cd Doc_Query_Genie  

2. Install dependencies

   pip install -r requirements.txt  

3. Run the application

   python app.py  

4. Use the API
   • Access it at http://127.0.0.1:5000/
   • Upload PDFs and start querying

🤝 Contributing

We welcome contributions! Feel free to submit issues or pull requests.

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