Refactor session bootstrap handling and Streamlit app startup: Update start.sh to launch the app using uvicorn, enhance session bootstrap logic in session_bootstrap.py with retry mechanisms for transient errors, and modify streamlit_app.py to conditionally use a new route for session initialization. Add tests for retry behavior and error handling in session bootstrap payload generation.
Refactor Streamlit app and UI for session management: Replace token generation with session bootstrap URL, update client rendering logic, and enhance error handling for session initialization. Improve metrics logging in agent and metrics collector for better tracking of session metadata.
efactor MetricsCollector and UI to enhance latency tracking and simplify display: Update latency calculations to include STT finalization and LLM generation wait metrics. Remove unused session and trace ID elements from the UI for a cleaner interface. Improve test coverage for new latency metrics and ensure accurate reporting in conversation turns.
Add Langfuse tracing support and enhance agent dispatch logic: Introduce optional Langfuse tracing configuration in .env.example and settings.py. Update agent and metrics collector to handle Langfuse traces per user turn. Refactor agent dispatch logic to ensure proper agent management and session metadata handling in the Streamlit app. Enhance UI to display session and trace information.
Implement speech-to-text provider selection and configuration: Update environment settings to support both Moonshine and NVIDIA STT providers, refactor STT initialization logic in the agent, and enhance footer generation in the Streamlit app for improved user experience. Update dependencies and settings management for better flexibility in model selection.
Refactor Streamlit app layout and enhance UI styling: Update page configuration for a wider layout, improve header visibility, and apply new CSS styles for better user experience. Adjust audio visualization in JavaScript for improved responsiveness and aesthetics.
Enhance metrics tracking and visualization: Integrate live and average metrics display in the UI, update JavaScript for metrics handling, and improve audio synthesis logging in Pocket TTS. Adjust Streamlit app for better component height and scrolling.
Enhance LiveKit integration: Add audio input and VAD configurations, update settings, and improve Streamlit app for better agent dispatch and error handling.
Update environment configuration for LiveKit integration, modify Dockerfile for Python version compatibility, and enhance settings management with LiveKit parameters.
implement main entry point for Open Voice Agent with CLI support for running FastAPI, Streamlit, or both. Enhance Streamlit UI for audio processing and integrate WebSocket communication. Update dependencies in pyproject.toml and remove requirements.txt.
