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CAL AI 2025 - Financial Information Agent

A comprehensive financial information system built using Google's Agent Development Kit (ADK) that provides current valuation, future outlook, and stock history analysis.

Prerequisites

  • Python 3.8 or higher
  • Google Cloud Platform account
  • Google ADK API access

Getting a Google ADK API Key

Step 1: Set up Google Cloud Platform

  1. Go to the Google Cloud Console
  2. Create a new project or select an existing one
  3. Enable billing for your project (required for API usage)

Step 2: Enable the ADK API

  1. In the Google Cloud Console, navigate to "APIs & Services" > "Library"
  2. Search for "Agent Development Kit" or "ADK"
  3. Click on the ADK API and press "Enable"

Step 3: Create API Credentials

  1. Go to "APIs & Services" > "Credentials"
  2. Click "Create Credentials" > "API Key"
  3. Copy the generated API key
  4. (Optional) Restrict the API key to specific APIs and IP addresses for security

Step 4: Set up Environment Variables

  1. Navigate to the parent_folder/financial_information_agent/ directory
  2. Create a .env file if it doesn't exist
  3. Add your API key to the .env file:
    GOOGLE_ADK_API_KEY=your_api_key_here
    

Installation

  1. Clone this repository:

    git clone <repository-url>
    cd CAL_AI_2025
  2. Install required dependencies:

    pip install -r requirements.txt
  3. Set up your environment variables as described above

Project Structure

CAL_AI_2025/
├── parent_folder/
│   └── financial_information_agent/
│       ├── agent.py                 # Main agent implementation
│       ├── api_functions.py         # API integration functions
│       ├── current_valuation_agent/ # Current valuation analysis
│       ├── future_outlook_agent/    # Future outlook predictions
│       ├── stock_history_agent/     # Historical data analysis
│       ├── shared_tools.py          # Shared utilities
│       └── .env                     # Environment variables (create this)
├── scraper/                         # Web scraping utilities
├── storage/                         # Data storage
└── documentation.md                 # Project documentation

Usage

  1. Ensure your .env file is properly configured with your Google ADK API key

  2. Run the main agent:

    python parent_folder/financial_information_agent/agent.py
  3. For specific functionality, you can run individual agents:

    # Current valuation analysis
    python parent_folder/financial_information_agent/current_valuation_agent/agent.py
    
    # Future outlook analysis
    python parent_folder/financial_information_agent/future_outlook_agent/agent.py
    
    # Stock history analysis
    python parent_folder/financial_information_agent/stock_history_agent/agent.py

Features

  • Current Valuation Agent: Analyzes current stock valuations and market conditions
  • Future Outlook Agent: Provides predictions and future market analysis
  • Stock History Agent: Processes historical stock data and trends
  • Web Scraping: Automated data collection from financial websites

Security Notes

  • Never commit your .env file to version control
  • Keep your API keys secure and restrict them appropriately
  • Monitor your API usage to avoid unexpected charges

Troubleshooting

API Key Issues

  • Ensure your API key is correctly formatted in the .env file
  • Verify that the ADK API is enabled in your Google Cloud Console
  • Check that billing is enabled for your Google Cloud project

Common Errors

  • ModuleNotFoundError: Install missing dependencies with pip install -r requirements.txt
  • API Key not found: Verify your .env file exists and contains the correct API key
  • Permission denied: Check that your API key has the necessary permissions

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Test thoroughly
  5. Submit a pull request

License

[Add your license information here]

Support

For issues related to Google ADK, refer to the official documentation.

About

Building an AI agent with Google ADK, powered by Google Gemini, yfinance API, and real-time web scraping

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