Financial AI Agent

An AI-powered financial assistant built with PhiData, Groq, YFinance, and DuckDuckGo.

What it does

• Fetches real-time stock prices, fundamentals, and analyst recommendations via YFinance
• Searches the web for latest company news via DuckDuckGo
• Gives Buy / Hold / Sell recommendations with reasoning

Setup

1. Clone the repo

git clone https://github.com/YOUR_USERNAME/financial-agent.git
cd financial-agent

2. Create and activate a virtual environment

conda create -p venv python=3.12
conda activate ./venv

3. Install dependencies

pip install -r requirements.txt

4. Set up your API keys

Create a .env file in the project root:

GROQ_API_KEY=your_groq_api_key_here

Get your free Groq API key at: https://console.groq.com

5. Run the agent

python financial_agent.py

Project Structure

financial_agent.py   # Main financial AI agent
pdf_assistant.py     # PDF Q&A assistant
requirements.txt     # Python dependencies
.env                 # API keys (never commit this!)

Models Used

• llama-3.3-70b-versatile via Groq API

Note

-Never commit your .env file. It is already excluded in .gitignore.

Error incase

1. For incase .venv files not reading inside: .vscode folder >> settings.json>> { "python.terminal.useEnvFile": true } paste this command for reading env api keys in terminal
2. Install multipart for playground.py functioning use command: pip install python-multipart