VoiceFlow AI

Enterprise-Grade AI Voice Agent Platform

Intelligent phone conversations powered by Claude, Whisper, and ElevenLabs

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Overview

VoiceFlow AI is a production-ready voice agent system for intelligent phone conversations with sub-2 second latency. Built on cutting-edge AI technologies, it delivers natural, context-aware interactions at scale.

Key Capabilities:

• Advanced AI - Claude-powered natural language understanding
• Real-time Processing - Streaming audio pipeline with <2s latency
• Telephony Integration - Seamless Twilio inbound/outbound calls
• Contextual Memory - Redis-backed conversation history
• Extensible Tools - LangChain integration for CRM, booking, ticketing
• Production Ready - Docker deployment, CI/CD, comprehensive testing

Use Cases: Customer support, appointment scheduling, billing inquiries, ticket management, lead qualification, outbound notifications

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Architecture

Technology Stack:

• Telephony: Twilio Voice API
• Application: FastAPI + Uvicorn
• STT: OpenAI Whisper
• LLM: Claude (Anthropic)
• TTS: ElevenLabs
• Memory: Redis
• Database: PostgreSQL
• Orchestration: LangChain

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Quick Start

Prerequisites

• Python 3.11+
• Docker & Docker Compose
• API Keys: Twilio, Anthropic, OpenAI, ElevenLabs

Installation

# Clone and install
git clone https://github.com/yourusername/voiceflow-ai.git
cd voiceflow-ai
pip install poetry && poetry install

# Configure environment
cp .env.example .env
# Edit .env with your API keys

# Start services
docker-compose -f docker/docker-compose.yml up -d

# Initialize database
poetry run python scripts/init_db.py

# Run application
poetry run python -m voiceflow.main

Development Setup

# Expose local server with ngrok
ngrok http 8000

# Update .env with ngrok URL
NGROK_URL=https://your-subdomain.ngrok.io

# Configure Twilio webhook
# Set "A call comes in" to: https://your-subdomain.ngrok.io/webhook/voice/incoming

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Configuration

Create .env file:

# Twilio
TWILIO_ACCOUNT_SID=ACxxxxxxxxxxxxx
TWILIO_AUTH_TOKEN=your_token
TWILIO_PHONE_NUMBER=+1234567890

# AI Services
ANTHROPIC_API_KEY=sk-ant-xxxxx
OPENAI_API_KEY=sk-xxxxx
ELEVENLABS_API_KEY=your_key
ELEVENLABS_VOICE_ID=voice_id

# Database
REDIS_URL=redis://localhost:6379/0
DATABASE_URL=postgresql://voiceflow:dev123@localhost:5432/voiceflow

# Development
NGROK_URL=https://your-subdomain.ngrok.io

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API Reference

Webhooks

Incoming Call Handler

POST /webhook/voice/incoming

Media Stream WebSocket

WS /webhook/ws/media-stream/{call_sid}

Call Management

Initiate Outbound Call

curl -X POST http://localhost:8000/api/calls/outbound \
  -H "Content-Type: application/json" \
  -d '{"to_number": "+1234567890", "initial_message": "Hello!"}'

Get Call Details

GET /api/calls/{call_sid}

Health Checks

curl http://localhost:8000/health/
curl http://localhost:8000/health/detailed

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Project Structure

voiceflow-ai/
├── src/voiceflow/          # Main application
│   ├── api/                # API endpoints & webhooks
│   ├── services/           # STT, TTS, Agent, Conversation
│   ├── memory/             # Redis memory management
│   ├── tools/              # LangChain tools (CRM, booking, ticketing)
│   ├── models/             # Data models
│   └── utils/              # Audio, logging, validators
├── tests/                  # Unit & integration tests
├── scripts/                # Helper scripts
├── docker/                 # Docker configuration
└── docs/                   # Documentation

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Testing

# Run all tests
poetry run pytest

# With coverage
poetry run pytest --cov=voiceflow tests/

# Code quality
poetry run black src/
poetry run ruff check src/
poetry run mypy src/

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Docker Deployment

Development:

docker-compose -f docker/docker-compose.yml up -d

Production:

docker build -t voiceflow-ai:latest -f docker/Dockerfile .
docker run -d --name voiceflow-ai -p 8000:8000 --env-file .env voiceflow-ai:latest

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Performance

Metric	Target	Typical
Response Latency	<2s	1.5s
STT Accuracy	>95%	97%
Call Success Rate	>90%	94%
Concurrent Calls	100+	100+
Uptime	99.9%	99.95%

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Documentation

Comprehensive guides available in the docs/ directory:

• Architecture Guide - System design, components, and technology stack
• Deployment Guide - Production deployment (Docker, AWS ECS, monitoring)
• Integration Guide - CRM, booking, payment, and custom integrations
• API Reference - Complete API documentation with examples
• Implementation Plan - Development roadmap and timeline
• Directory Structure - File organization guide
• Coding Standards - Code quality guidelines

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Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to branch (git push origin feature/amazing-feature)
5. Open Pull Request

Requirements: Follow coding rules, write tests, format with black

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License

MIT License - see LICENSE file

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Acknowledgments

Built with: FastAPI • Twilio • Anthropic Claude • OpenAI Whisper • ElevenLabs • LangChain • Redis

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Support

• Issues: GitHub Issues
• Docs: docs/
• Email: support@voiceflow-ai.com

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Roadmap

• Core voice agent functionality
• Intent detection and routing
• Memory and context management
• Tool integration framework
• Multi-language support
• Advanced sentiment analysis
• Real-time analytics dashboard
• Custom voice training
• WhatsApp/SMS integration

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VoiceFlow AI - Making every call count 🎙️