Chain of Agents Stock Analysis System

A modern stock analysis application powered by a chain of AI agents to collect data, perform analysis, and create visualizations.

Overview

This application uses a pipeline of specialized agents to analyze stocks:

1. Data Collector Agent: Fetches historical stock data, news, and fundamentals from Alpha Vantage
2. Analysis Agent: Examines the data and generates insights and recommendations
3. Visualization Agent: Creates interactive charts and visual representations of the analysis

Features

• Modern, responsive UI with sleek animations and visual feedback
• Real-time agent status visualization to show pipeline progress
• Interactive stock charts with price history and technical indicators
• Comprehensive analysis with buy/sell/hold recommendations
• Support for various time periods (1 week to 10 years)

Requirements

• Python 3.10+
• Alpha Vantage API key (free tier is sufficient)
• Ollama with deepseek-coder model (for LLM capabilities)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/ChainOfAgents.git
   cd ChainOfAgents

2. Create a virtual environment:

   python -m venv venv

3. Activate the virtual environment:

   # On macOS/Linux
   source venv/bin/activate
   
   # On Windows
   venv\Scripts\activate

4. Install the required dependencies:

   pip install -r requirements.txt

5. Configure your API keys in config.py:

   # Alpha Vantage API key
   ALPHA_VANTAGE_API_KEY = "your_api_key_here"

Running the Application

1. Ensure your virtual environment is activated:

   source venv/bin/activate

2. Start the Flask application:

   python app.py

3. Open your web browser and navigate to:

   http://127.0.0.1:5000
   

4. Enter a stock symbol (e.g., AAPL, MSFT, GOOG) and select a time period to analyze

5. To stop the application, press Ctrl+C in the terminal

6. When finished, deactivate the virtual environment:

   deactivate

Architecture

Agent Pipeline

The application uses a chain of agents, each with a specialized role:

1. Data Collector Agent:

   • Fetches stock data from Alpha Vantage
   • Retrieves news articles and fundamental data
   • Caches responses to minimize API calls

2. Analysis Agent:

   • Processes historical price data
   • Analyzes trends and patterns
   • Generates buy/sell/hold recommendations with confidence levels

3. Visualization Agent:

   • Creates interactive price charts
   • Visualizes key technical indicators
   • Provides visual insights to support the analysis

Technologies Used

• Frontend: HTML5, CSS3, JavaScript, Bootstrap 5
• Backend: Flask, Python
• Data Visualization: Plotly.js
• API Integration: Alpha Vantage, Yahoo Finance (fallback)
• LLM Integration: Ollama with deepseek-coder model

Troubleshooting

• Empty Charts: If charts appear empty, check your Alpha Vantage API key in config.py
• Slow Responses: The free tier of Alpha Vantage has rate limits; cached responses are used when available
• SSL/TLS Errors: These are handled by the application and can be safely ignored

License

MIT