awesome-llm-apps/rag-as-a-service

🖇️ RAG-as-a-Service with Claude 3.5 Sonnet

Build and deploy a production-ready Retrieval-Augmented Generation (RAG) service using Claude 3.5 Sonnet and Ragie.ai. This implementation allows you to create a document querying system with a user-friendly Streamlit interface in less than 50 lines of Python code.

Features

Production-ready RAG pipeline Integration with Claude 3.5 Sonnet for response generation Document upload from URLs Real-time document querying

How to get Started?

1. Clone the GitHub repository

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd rag-as-a-service

2. Install the required dependencies:

pip install -r requirements.txt

3. Get your OpenAI API and Ragie API Key

• Sign up for an Anthropic account and get your API key
• Sign up for an Ragie account and get your API key

4. Run the Streamlit app

streamlit run rag_app.py