Professional AI Voice Agent for Automated Lead Qualification and Meeting Scheduling
Setter.AI is an intelligent calling system that automatically contacts business leads, qualifies them through natural conversations, and schedules meetings with your sales team. Powered by OpenAI's GPT-4 and Twilio's voice infrastructure.
- ๐ค AI Voice Agent: Professional female voice (Maayaa) for natural conversations
- ๐ Automated Calling: Intelligent lead qualification through phone calls
- ๐ฏ Lead Management: Integration with GoHighLevel (GHL) CRM
- ๐ Meeting Scheduling: Automatic calendar coordination
- ๐ Analytics Dashboard: Real-time call monitoring and reporting
- ๐ Secure: Environment-based configuration with API key protection
Setter.AI
โโโ ๐ค AI Logic (OpenAI GPT-4)
โโโ ๐ Voice System (Twilio)
โโโ ๐ CRM Integration (GoHighLevel)
โโโ ๐ Web Dashboard (Flask)
โโโ ๐๏ธ Data Storage (SQLite)
- Python 3.8+
- GoHighLevel API Key & Location ID
- OpenAI API Key (GPT-4 access)
- Twilio Account (Account SID, Auth Token, Phone Number)
git clone <your-repo-url>
cd setter.ai-v1pip install -r requirements.txtCreate a .env file in the project root:
# Copy environment template
cp .env.example .env
# Edit with your API keys
nano .envRequired Environment Variables:
# GHL (GoHighLevel) Configuration
GHL_API_KEY=your_ghl_api_key_here
GHL_LOCATION_ID=your_location_id_here
# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key_here
# Twilio Configuration
TWILIO_ACCOUNT_SID=your_twilio_account_sid_here
TWILIO_AUTH_TOKEN=your_twilio_auth_token_here
TWILIO_PHONE_NUMBER=+1234567890
# Webhook Configuration
WEBHOOK_BASE_URL=https://your-ngrok-url.ngrok.io# Start the main application
python src/main.pyOpen your browser and navigate to:
http://localhost:5000
# Verify all API keys are loaded
python -c "
import sys; sys.path.append('src')
from setter_ai.utils.config import load_config
config = load_config()
print('โ
Configuration loaded successfully!')
"# Test GHL Integration
cd tests && python test_ghl_leads.py
# Test Twilio Calling
cd tests && python test_twilio_call.py
# Test Voice Conversation
cd tests && python test_voice_conversation.py# Test web interface
cd tests && python test_dashboard.pysetter.ai-v1/
โโโ src/ # Source code
โ โโโ setter_ai/ # Main application package
โ โ โโโ core/ # AI logic and business rules
โ โ โโโ integrations/ # External service integrations
โ โ โโโ utils/ # Utilities and helpers
โ โ โโโ web/ # Web interface and API
โ โโโ main.py # Application entry point
โโโ tests/ # Test suite
โโโ data/ # Database and data files
โโโ logs/ # Application logs
โโโ requirements.txt # Python dependencies
โโโ .env.example # Environment template
โโโ README.md # This file
All configuration is managed through environment variables. The system automatically loads from .env files and validates required API keys at startup.
Modify the .env file to customize:
- Business Hours:
BUSINESS_HOURS_START,BUSINESS_HOURS_END - Voice Settings:
VOICE_TYPE,SPEECH_RATE,VOICE_PITCH - AI Behavior:
AI_MODEL,AI_TEMPERATURE,AI_MAX_TOKENS - Call Settings:
MAX_CALL_DURATION,RETRY_ATTEMPTS
- Leads are automatically imported from GoHighLevel
- System checks for new leads every 10 minutes
- Only leads within 24 hours are processed
- AI agent calls leads during business hours
- Natural conversation flow for qualification
- Automatic meeting scheduling for interested prospects
- Real-time call status and analytics
- Lead qualification results
- Meeting scheduling confirmations
- API Keys: Stored in
.envfiles (never committed to git) - Environment Isolation: Separate configs for development/production
- Input Validation: All external inputs are sanitized
- HTTPS: Webhook endpoints require secure connections
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the Apache License, Version 2.0 - see the LICENSE file for details.
- Multi-language support
- Advanced analytics dashboard
- Integration with additional CRMs
- Machine learning optimization
- Mobile application
- API rate limiting and optimization
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