Bodybuilding AI Coach API

A serverless API for an AI-powered bodybuilding coach that provides personalized workout plans, progress tracking, and real-time feedback.

Features

• Personalized workout plan generation
• Progress tracking and metrics
• AI coach chat interface
• User profile management
• Plan versioning and history
• Real-time workout feedback

Project Structure

bodybuilding_serverless_api/
├── src/
│   ├── models/         # Data models
│   ├── services/       # Business logic
│   │   ├── chat/      # AI chat functionality
│   │   └── core/      # Core services
│   └── aws/           # AWS service wrappers
├── schema/            # JSON schemas
├── tests/             # Test suite
└── config files       # Configuration files

Documentation

Detailed documentation is available in the docs directory:

• Bodybuilding API Documentation - Complete API structure and components
• Implementation Plan - Project implementation phases
• DynamoDB Tables Comparison - Database schema changes
• Handler Comparison - API handler transformations

Setup

1. Install dependencies:

npm install -g serverless
pip install -r requirements.txt

2. Configure AWS credentials:

serverless config credentials --provider aws --key YOUR_KEY --secret YOUR_SECRET

3. Deploy:

serverless deploy --stage dev

Development

• Use serverless offline for local development
• Run tests with pytest
• Format code with black

API Endpoints

Plans

• POST /plans/create - Create new workout plan
• POST /plans/save - Save plan changes
• GET /plans/list - List user's plans
• GET /plans/versions/{planId} - Get plan versions

Users

• POST /users/create - Create user profile
• PUT /users/{userId} - Update user profile

Progress

• POST /progress/{userId} - Update progress
• GET /progress/{userId} - Get progress history

Chat

• POST /plans/chat - Chat with AI coach
• GET /plans/{planId}/chat-history - Get chat history

Environment Variables

Required environment variables:

• STAGE - Deployment stage (dev/prod)
• COGNITO - Cognito secret name
• Various table names (see serverless.yml)

Contributing

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

License

MIT License