AI Therapist
Project Overview
AI Therapist is a real-time conversational assistant that enables natural speech-to-speech interactions for mental health support. Using WebRTC technology and OpenAI's Realtime API, the application creates a seamless, voice-based interface that feels like talking to a supportive human therapist.
The system is designed to provide accessible mental health resources through natural conversation, creating a low-barrier entry point for those seeking emotional support or guidance. While not a replacement for professional therapy, it serves as a supplementary tool for mental wellness.
Challenges & Solutions
Real-time Audio Processing
Implementing bidirectional audio streaming with minimal latency while maintaining high quality was a significant technical challenge.
Solution: I developed a WebRTC client using Python's aiortc library that establishes secure, low-latency connections with OpenAI's Realtime API. The implementation includes optimized audio configuration (48kHz sampling rate, mono channel) and efficient buffer management to minimize latency while preserving audio quality.
Secure Authentication
Ensuring secure access to the API while maintaining user privacy required careful implementation.
Solution: I implemented an ephemeral token-based authentication system that securely manages API credentials and user sessions. The system uses environment variables for API key storage and establishes encrypted connections for all data transmission.
Conversation Context Management
Maintaining coherent, contextually-aware conversations across a therapy session presented unique challenges.
Solution: I designed a data channel system that manages conversation state, tracks emotional context, and ensures continuity throughout the interaction. This approach allows the AI to remember previous statements and respond appropriately to evolving emotional needs.
Features & Functionality
- Real-time Voice Interaction: Natural speech-to-speech conversation with minimal latency
- Secure Communication: End-to-end encryption for all user interactions
- Contextual Awareness: Maintains conversation history for coherent, meaningful exchanges
- Multi-modal Support: Handles both text and speech inputs/outputs
- Emotional Intelligence: Responds appropriately to emotional cues in conversation
- User Authentication: Secure login system with session management
- Conversation History: Option to save and review past conversations
Key Learnings
Developing the AI Therapist project provided valuable insights into several advanced technical domains:
- Implementing WebRTC for real-time audio communication
- Working with OpenAI's Realtime API for speech processing
- Building secure authentication systems for sensitive applications
- Optimizing audio processing for conversational AI
- Designing user interfaces for voice-first applications
- Creating systems that handle emotionally sensitive content appropriately
This project also deepened my understanding of the intersection between technology and mental health, highlighting both the opportunities and ethical considerations in this space.