Customer Support Voice Agent 🎙️

A Streamlit-powered application that converts documentation into interactive voice responses using OpenAI's Text-to-Speech capabilities. This tool helps users get quick, voice-enabled answers to their documentation-related questions.

Features

• 🔍 Documentation crawling and indexing
• 🔊 Voice-powered responses using OpenAI's TTS
• 💡 Intelligent context-aware answers
• 📚 Vector-based document search
• 🎯 Multiple voice options
• 📥 Downloadable audio responses

Prerequisites

• Python 3.8+
• OpenAI API key
• Qdrant instance and API key
• Firecrawl API key

Installation

1. Clone the repository:

git clone https://github.com/ucalyptus/customer_support_voice_agent.git
cd customer_support_voice_agent

2. Install the required dependencies:

pip install -r requirements.txt

3. Create a .env file in the project root with your API keys:

QDRANT_URL=your_qdrant_url
QDRANT_API_KEY=your_qdrant_api_key
FIRECRAWL_API_KEY=your_firecrawl_api_key
OPENAI_API_KEY=your_openai_api_key

Usage

1. Start the Streamlit application:

streamlit run script.py

2. Configure the system using the sidebar:

   • Enter your API keys
   • Specify the documentation URL
   • Select your preferred voice

3. Ask questions about the documentation and receive both text and voice responses

Voice Options

The following voices are available:

• alloy
• ash
• ballad
• coral
• echo
• fable
• onyx
• nova
• sage
• shimmer
• verse

System Components

• Vector Database: Uses Qdrant for efficient document storage and retrieval
• Document Crawler: Utilizes Firecrawl for documentation scraping
• Embedding Model: FastEmbed for text embedding generation
• Processing Agents: GPT-4 powered agents for context processing and TTS optimization
• Voice Synthesis: OpenAI's TTS model for natural-sounding responses

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

Support

For support, please open an issue in the GitHub repository or contact the maintainers.