iform

"iform" (Norwegian for "in shape") is a web application designed to provide personalized training insights. It connects to your Strava account, fetches your recent activities, and uses an AI-powered coach to analyze your performance and offer actionable suggestions for improvement.

This project was initially created as a demonstration of the Gemini CLI's capabilities and has evolved into a functional tool for personal training analysis.

Screenshot

Features

• Strava Integration: Securely connect your Strava account to fetch your last six months of activity data.
• AI-Powered Analysis: Utilizes a generative AI model to act as a personal running coach, providing:
  • A summary of your recent training period.
  • Concrete, actionable suggestions for improvement.
  • A trend analysis chart visualizing your average pace and total distance over the last six months.
• Special Considerations Input: Provide additional context (e.g., injuries, upcoming events) to the AI for more tailored and safe training suggestions.
• Multi-language Support: The user interface is available in English, Norwegian, and Spanish.
• Light & Dark Mode: Switch between light and dark themes for your viewing preference.

How It Works

The application consists of a simple frontend and a Node.js backend.

• Frontend: A static web page built with HTML, CSS, and vanilla JavaScript. It handles user interaction, displays data, and renders a trend chart using Chart.js.
• Backend: An Express.js server that manages:
  • Strava OAuth authentication.
  • Fetching activities from the Strava API.
  • Interacting with a generative AI model to analyze the activity data.
  • Serving language translations.

Setup and Installation

To run this project locally, you will need to have Node.js installed.

1. Clone the repository:

   git clone https://github.com/torfinnnome/iform.git
   cd iform

2. Install backend dependencies:

   cd backend
   npm install

3. Configure environment variables:

   Create a .env file in the backend directory and add the following, replacing the placeholder values with your actual credentials:

   STRAVA_CLIENT_ID=your_strava_client_id
   STRAVA_CLIENT_SECRET=your_strava_client_secret
   GOOGLE_API_KEY=your_google_api_key
   REDIRECT_URI=http://localhost:3000/api/strava/callback
   GEMINI_MODEL=gemini-2.0-flash
   SESSION_SECRET=your_very_secret_session_key
   

   Generating a secure SESSION_SECRET: For production environments, it is crucial to use a strong, randomly generated string for SESSION_SECRET. You can generate one using openssl:

   openssl rand -base64 32

   Replace your_very_secret_session_key with the output of this command.

4. Start the server:

   node server.js

5. Open the application:

   Open your web browser and navigate to http://localhost:3000.

Future Development

Future plans for iform include:

• Interactive Chat: A chat interface to interact directly with the AI personal trainer for more dynamic and personalized coaching.
• Expanded Data Sources: Integration with other training data sources beyond Strava.
• AI Model Flexibility: The ability to choose from different AI service providers for analysis.

Contributing

This is a personal project, but feedback and contributions are welcome. Please feel free to open an issue or submit a pull request.