Financial News RAG System

This project consists of two main components:

1. News Ingestion Service - Continuously fetches financial news from Alpaca and stores it in QdrantDB
2. News RAG Service - Provides question-answering capabilities using the stored news data

Setup

1. Clone the repository
2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Copy .env.example to .env and fill in your API keys:
   • ALPACA_API_KEY
   • ALPACA_SECRET_KEY
   • QDRANT_API_KEY
   • QDRANT_URL
   • OPENAI_API_KEY

Running the Services

News Ingestion Service

python news_ingestion_service.py

This will start the continuous news ingestion process.

News RAG Service

python news_rag_service.py

Workflow Logic:

1. News Ingestion Service (news_ingestion_service.py):

2. News RAG Service (news_rag_service.py):