A full-stack application for automated financial analysis. It parses market news/signals from text files, determines affected S&P 500 stocks, fetches market data, performs sentiment analysis, and generates an AI summary using the Gemini pipeline.

• app/ - The FastAPI Python backend
• frontend/ - The Next.js React frontend

1. Navigate to the project root:

   cd HackAI

2. Create and activate a virtual environment, then install dependencies:

   pip install -r requirements.txt

3. Copy .env.example to .env and fill in your API keys:
   • GEMINI_API_KEY
   • MASSIVE_API_KEY
   • ALPHA_VANTAGE_API_KEY
4. Run the server:

   uvicorn app.main:app --reload

   The backend will be available at http://localhost:8000.

1. Navigate to the frontend directory:

   cd HackAI/frontend

2. Install Node dependencies:

   npm install

3. Create a .env.local file to specify the API URL (optional if running backend locally at port 8000):

   NEXT_PUBLIC_API_URL=http://localhost:8000
   

4. Run the development server:

   npm run dev

   The frontend will be available at http://localhost:3000.

• Frontend: Designed for instant deployment on Vercel.
• Backend: Can be easily hosted on Railway, Render, or any standard Python hosting service. Update the frontend's NEXT_PUBLIC_API_URL to point to the production backend URL when deploying.