LLM powered stock analysis agent
- LLM-powered analysis for stock trends
- Real-time data processing
- User-friendly interface for stock queries
- Light weight , uses in-device LLMs ( eg llama3:8b)
- In a nutshell
- Uses yfinance APIs to pull stock data
- Compares fundamentals to universally agreed thresholds and limits
- Creates a pipeline with LLM integration to compare data and generate text
- Consolidates the commentary
- Clone the repository:
git clone https://github.com/yourusername/finagent.git
- Navigate to the project directory:
cd finagent - Install the required dependencies:
pip install -r requirements.txt
To start the agent, run:
python main.py --symbol <stock ticker> --country <US/IN> --output_dir ./
eg : python main.py --symbol TATAMOTORS --country IN --output_dir ./
This work is heavily inspired by contents in this paper :
- Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews https://arxiv.org/abs/2502.05439
- Usefull pointers from https://github.com/hananedupouy/LLMs-in-Finance - mostly the pipeline components - this most likely will change.
I have used freely available tools , for example yfinance for indian stocks. LLM integration using OLAMA with LLAMA3. I have not used openAI APIs, LLAMAI Index pipelines - pipelines were handwritten. Everything is free!
I need to thank github co-pilot for massively improving my speed.
This is still work in progress. Use with caution :)
- Integration of technical analysis
- Provide buy/hold/sell recommendation
- Feedback from friends/colleagues.
- Migrate to bigger models for better output
- run on intel gaudi 3 accelerators