Integrate Langchain usage patch and update UI metrics: Apply Langchain usage patch in agent.py, adjust pipeline stage layout in index.html, and enhance metric descriptions in main.js for improved clarity and functionality.
Enhance metrics handling and add EOU support: Update ChannelPublisher and TurnTracer to include end-of-utterance (EOU) metrics, refactor latency calculations, and improve metric attribute handling. Modify UI tooltips for clarity and adjust test cases to validate new metrics structure.
Add LLM connection settings and enhance error handling: Introduce new parameters for LLM connection timeout, retry attempts, and stall timeout in .env.example and settings.py. Update agent.py to log errors and session closures, and implement a watchdog for LLM stall detection in MetricsCollector.
Update PocketTTS configuration and logging: Change sample rate handling to enforce native 24kHz, adjust idle process count in .env.example, and enhance audio diagnostics in main.js for better tracking of remote audio track events.
Refactor metrics handling in MetricsCollector and UI: Consolidate latency calculations, enhance live metrics updates for agent roles, and improve test coverage for EOU latencies without LLM or TTS. Streamline code for clarity and accuracy in metric reporting.
Remove session metadata handling from agent and UI: Eliminate the on_data_received function in agent.py and the session metadata publishing logic in main.js to streamline session management and improve code clarity.
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.
Refactor MetricsCollector and UI for improved latency tracking: Simplify metric calculations by consolidating functions, enhance tooltip descriptions for clarity, and adjust CSS for better layout and responsiveness in index.html.
Add agent state change handling and improve metrics collection: Introduce AgentStateChangedEvent to track agent state transitions. Update MetricsCollector to record timestamps for first assistant audio when entering the speaking state. Enhance test coverage for new functionality in agent state management.
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.
Enhance VAD configuration and add fallback participant ID support: Update VAD_MIN_SPEECH_DURATION and VAD_MIN_SILENCE_DURATION for faster response times. Introduce fallback participant ID logic in MetricsCollector to handle cases where participant metadata is absent, ensuring accurate trace reporting.
Add fallback session ID support in MetricsCollector: Introduce a mechanism to generate a console-prefixed fallback session ID when metadata is absent. Update session handling logic to utilize the fallback ID and enhance test coverage for fallback scenarios.
Refactor MetricsCollector to improve latency metrics tracking: Update logic for calculating STT span duration and add support for conversation latency metrics. Enhance test coverage to validate new metrics in tracing spans.
Update Langfuse tracing configuration and enhance metrics collection: Increase trace finalize timeout in .env.example and settings.py. Add support for speech created events in MetricsCollector to capture assistant text. Refactor metrics handling to include additional latency metrics and improve test coverage for speech handling scenarios.
Enhance Langfuse tracing functionality: Add new configuration options for trace timeouts and maximum pending tasks in .env.example and settings.py. Update MetricsCollector to handle assistant text finalization and improve trace task management. Refactor agent logic to ensure accurate trace status reporting and enhance test coverage for tracing behavior.
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.
Enhance Pocket TTS configuration and update documentation: Add new Pocket TTS settings to .env.example, including voice and sample rate options. Update README to reflect new features and improvements in Pocket TTS, including streaming synthesis capabilities and error handling. Refactor Pocket TTS class to streamline voice loading and improve error management during initialization.
Refactor .gitignore and enhance Pocket TTS and Moonshine STT: Simplify .gitignore by removing unnecessary entries and adding environment-specific files. Update Pocket TTS to use a configurable sample rate and replace UUID with shortuuid for request IDs. Modify Moonshine STT to use NotGivenOr for language parameter and update stream class inheritance for better clarity.
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.
implement LLM provider selection and configuration: Update environment settings to support HuggingFace alongside NVIDIA, refactor LLM initialization logic in the agent, and enhance settings management for improved flexibility in model selection.
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 Python version requirement to 3.10, modify dependencies in pyproject.toml and uv.lock for compatibility, and enhance Moonshine STT plugin with improved model handling and streaming capabilities.
Enhance LLMFactory to support local model initialization for HuggingFace and Kokoro TTS, update dependencies in pyproject.toml and uv.lock for improved functionality.
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.
