Bay Club Ignite Class Booking Assistant

A comprehensive Python system for booking Ignite classes at Bay Club San Francisco, featuring an AI-powered Streamlit chat interface.

Features

Class Booking/Checking Tools

• book_any_class(): Books any class type at Bay Club San Francisco (Ignite, Pilates, Riide, etc.)
  • Supports variable date input (YYYY-MM-DD format)
  • Supports variable time input (7:00, 6:30, etc.)
  • Supports variable AM/PM selection
  • Supports any class name (Ignite, Pilates, Riide, Cardio Hip Hop, etc.)
• check_all_classes(): Checks available classes for a specific date (all types: Ignite, Pilates, Riide, etc.)
  • Returns available times and class information
  • Can check any date (past, present, or future)
  • Returns detailed status information
• Smart day selection (works for any day - Ignite classes run daily)
• Context manager for proper resource cleanup

LLM Chat Assistant (Streamlit)

• Conversational AI interface using Gradient LLM
• Direct tool integration: Chat messages can trigger booking and checking functions
• Natural language processing: Understands phrases like "Check classes for today" or "Book a 7:00 AM class tomorrow"
• Intent parsing: Automatically detects when users want to check availability or book classes
• Memory and state management for booking history
• Real-time class availability and booking through chat interface
• Interactive weekly schedule viewing
• Credential management and booking history tracking

Class Availability Checker

• Check class availability for specific dates and times
• Weekly schedule generation
• Real-time availability status (available/waitlist)

Setup

1. Clone the repository and navigate to the directory:

cd langchain-gradient-bayclub

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Python dependencies:

pip install -r requirements.txt

4. Install Playwright browsers:

playwright install

5. Set up your credentials by creating a .env file:

python config.py  # Creates sample .env file
# Then edit .env with your actual credentials

Or set environment variables directly:

export BAY_CLUB_USERNAME="your-username"
export BAY_CLUB_PASSWORD="your-password"
export DIGITALOCEAN_INFERENCE_KEY="your-api-key"

🎯 Usage

Option 1: AI Chat Assistant (Recommended)

Launch the Streamlit chat interface:

python run_app.py

Or directly:

streamlit run streamlit_app.py

Then open your browser to http://localhost:8501 and chat with the AI assistant!

Example conversations:

• "Check classes for today" → Automatically calls check_all_classes()
• "What classes are available tomorrow?" → Automatically calls check_all_classes()
• "Book me a 7:00 AM Ignite class for Wednesday" → Automatically calls book_any_class()
• "Book a Pilates class for 2025-10-22 at 6:30 AM" → Automatically calls book_any_class()
• "Show me available times for today" → Automatically calls check_all_classes()

Natural Language Features:

• Understands relative dates: "today", "tomorrow", "next week"
• Extracts times from text: "7:00", "6:30", "8:00"
• Detects AM/PM: "7:00 AM", "6:30 PM"
• Parses specific dates: "2025-10-22", "October 22nd"

Option 2: Command Line Tools

Basic booking and checking (updated functionality):

# Run the main demo (checks classes for today and tomorrow)
python main.py

# Run example usage (shows function signatures and examples)
python example_usage.py

Option 3: Programmatic Usage

from main import book_any_class, check_all_classes
from config import Config

# Get credentials
username = Config.BAY_CLUB_USERNAME
password = Config.BAY_CLUB_PASSWORD

# Check classes for a specific date
result = check_all_classes(username, password, "2025-10-22", headless=True)
print(f"Available times: {result['available_times']}")

# Book a class for a specific date and time
success = book_any_class(username, password, "IGNITE", "2025-10-22", "7:00", "AM", headless=True)
if success:
    print("✅ Successfully booked class!")

📅 Date and Time Logic

The system now supports flexible date and time selection:

Date Input

• Format: YYYY-MM-DD (e.g., "2025-10-22")
• Default: If no date provided, uses current day
• Flexible: Can book for any date (past, present, or future)

Time Input

• Format: HH:MM (e.g., "7:00", "6:30", "8:00")
• Default: "7:00" if not specified
• Meridiem: "AM" or "PM" (default: "AM")

Function Parameters

• book_any_class(username, password, class_name, date=None, time="7:00", meridiem="AM", headless=False)
• check_all_classes(username, password, date=None, headless=False)

🛠️ File Structure

langchain-gradient-bayclub/
├── streamlit_app.py          # AI chat interface
├── flexible_booking.py       # Advanced booking system
├── class_checker.py          # Availability checker
├── bayclub_booking.py        # Core booking class
├── main.py                   # Simple booking script
├── run_app.py               # App launcher
├── requirements.txt         # Dependencies
└── README.md               # This file

🔧 Configuration

Environment Variables

Create a .env file in the project root with:

# Bay Club Credentials
BAY_CLUB_USERNAME=your_username_here
BAY_CLUB_PASSWORD=your_password_here

# Gradient API Key
DIGITALOCEAN_INFERENCE_KEY=your_gradient_api_key_here

Or set them as environment variables:

• BAY_CLUB_USERNAME: Your Bay Club username
• BAY_CLUB_PASSWORD: Your Bay Club password
• DIGITALOCEAN_INFERENCE_KEY: Your Gradient API key (required for chat assistant)

Quick Setup

Run python config.py to create a sample .env file, then edit it with your actual credentials.

🎨 Streamlit App Features

• Chat Interface: Natural language conversation with AI
• Credential Management: Secure storage of Bay Club login
• Booking History: Track all your bookings
• Quick Actions: One-click common tasks
• Real-time Availability: Live class availability checking
• Memory: Remembers conversation context and preferences

🚨 Error Handling

• If a class is full, the system automatically adds you to the waitlist
• Comprehensive logging shows what's happening at each step
• Automatic screenshot capture for debugging
• Graceful error handling with user-friendly messages

📋 Requirements

• Python 3.7+
• Playwright
• Streamlit
• LangChain Gradient
• Bay Club account credentials
• Gradient API key

📄 License

MIT License - see the header in the source files for details.