Salon Assistant

A voice-enabled salon booking assistant that helps customers schedule appointments and check service availability.

Prerequisites

• Python 3.8 or higher
• PostgreSQL 12 or higher
• psql command-line tool

Installation

1. Clone the repository:

git clone <repository-url>
cd salon

2. Create and activate a virtual environment:

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

3. Install Python dependencies:

pip install -r requirements.txt

Database Setup

1. Start PostgreSQL service:

# On macOS
brew services start postgresql

# On Ubuntu/Debian
sudo service postgresql start

# On Windows
# Start PostgreSQL service from Services application

2. Create the database:

psql -U postgres
CREATE DATABASE salon;
\q

3. Seed the database with initial data:

# From project root
python scripts/seed_database.py

Configuration

1. Create a .env file in the root directory or copy from .env.example:

# Database Settings
DATABASE_URL=postgresql://{username}:{password}@localhost:5432/salon

# Voice Service Settingsa
WHISPER_MODEL=tiny  # Options: tiny, base, small, medium, large
TTS_LANGUAGE=en
TTS_PROVIDER=gtts  # Options: gtts, google_cloud
STT_PROVIDER=whisper  # Options: whisper, google_cloud

# Optional Google Cloud Settings
GOOGLE_CLOUD_CREDENTIALS=path/to/credentials.json  # Only if using Google Cloud services

Running the Application

You'll need to run three components: the FastAPI server, the Rasa server, and the Rasa Action server.

1. Ensure PostgreSQL is running:

# Check PostgreSQL status
# On macOS
brew services list | grep postgresql

# On Ubuntu/Debian
sudo service postgresql status

# On Windows
# Check Services application

2. Start the FastAPI server:

# From the project root
uvicorn app.main:app --reload --port 8000

3. Start the Rasa server:

# From the rasa directory
rasa run --enable-api --cors "*" --port 5005 --model stable-model.tar.gz

4. Start the Rasa Action server (in a new terminal):

# From the rasa directory
rasa run actions --port 5055

Training a new model

After making changes to the rasa config files you will need to re-train

# From the rasa directory
rasa train

You can then start the model

# From the rasa directory
rasa run --enable-api --cors "*" --port 5005 --model route/to/model

Testing the Application

1. Run the test suite:

# From the project root
pytest

2. Access the voice interface:

• Open your browser and navigate to: http://localhost:8000/static/voice.html
• Click "Start Recording" and allow microphone access
• Speak your request (e.g., "I want to book a haircut")
• Click "Stop Recording" to process your request

Available Services

The assistant can help with:

• Booking appointments for:
  • Haircuts
  • Massages
  • Facials
  • Manicures
  • Pedicures
  • Hair coloring
  • Styling
• Checking service availability
• Canceling appointments

Development

Project Structure

salon/
├── app/
│   ├── api/            # API endpoints
│   ├── core/           # Core functionality
│   ├── db/             # Database models and migrations
│   ├── services/       # Business logic
│   └── utils/          # Utility functions
├── tests/              # Test files
├── scripts/            # Utility scripts
├── .env.example        # Example environment variables
├── requirements.txt    # Project dependencies
└── README.md          # This file

API Documentation

Once the server is running, visit:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

License

MIT License