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RagFlow

A modular FastAPI-based backend for Retrieval-Augmented Generation (RAG) applications.
This project integrates LangChain, ChromaDB, and FastAPI to provide API endpoints and a simple app interface for LLM-powered Q&A systems.

Installation

1. Clone the repository

git clone <url>
cd rag_fastapi

2. Create & activate virtual environment

python3 -m venv .venv
source .venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Edit .env file

OPENAI_API_KEY=your_api_key_here

5. Run the server

cd api
uvicorn main:app --reload

6. Start the Streamlit

cd frontend
streamlit run app.py

After running, the terminal will prompt:

Click it (or copy it to your browser) and you’ll see the Streamlit interface.

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A modular FastAPI-based backend for Retrieval-Augmented Generation (RAG) applications.

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