refactor: Remove observed total latency from metrics calculations

feat: Add new report and turn metrics functions in test_analyze_traces

refactor: Remove LLM to TTS handoff latency from metrics and UI

feat: Enhance metrics collection and turn tracing for assistant responses

feat: Enhance metrics collection and tracing for assistant text

feat: Enhance metrics collection and assistant item correlation

feat: Enhance turn tracing and metrics collection

codex fixex

feat: Add unit tests for analyze_traces module

feat: Introduce MCP connection timeout handling and enhance configuration

feat: Enhance voice activity detection and turn tracing features

feat: Implement NVIDIA TTS stream patch for improved synthesis handling

feat: Add Deepgram STT provider support and enhance configuration options

feat: Add NVIDIA TTS provider support and enhance configuration options

feat: Implement dynamic TTS footer component and enhance footer HTML generation

feat: Add support for Deepgram TTS provider and related configurations

refactor: Revise assistant instructions and configuration summary formatting

feat: Introduce MCP startup greeting timeout and PocketTTS connection timeout settings

feat: Enhance LiveKit worker configuration and documentation

refactor: Consolidate LLM runtime configuration using LLMSettings

feat: Update Ollama configuration for cloud and local usage

feat: Add support for extra MCP server URLs and enhance assistant instructions

feat: Enhance assistant instructions and footer display for LLM providers

feat: Update LLM and PocketTTS connection options in session management

feat: Add Langfuse tracing support and UI enhancements

feat: Update LLM runtime configuration and tests for thinking behavior

feat: Enhance turn pipeline summary with partial updates and tool activity tracking

feat: Introduce turn pipeline summary and enhance tool execution metrics

feat: Update Ollama configuration and validation for cloud usage

feat: Enhance metrics collection with event timestamps for assistant interactions

feat: Enhance assistant behavior and tool feedback mechanisms

feat: Add post-tool response timeout and enhance error handling in channel metrics

feat: Enhance metrics collection and tracing with speech_id support

refactor: Restructure agent components and remove unused files

[200~feat: Enhance tool tracing and feedback mechanisms

feat: Add soundfile dependency and implement pre-tool feedback mechanism

feat: Implement LLM warm-up functionality and update connection settings

feat: Implement startup greeting monitoring and enhance greeting handling

feat: Enhance telemetry with tool call tracing and metrics collection

feat: Add LLM runtime and STT factory implementations

Add MCP runtime support and update configuration: Introduce MCP_ENABLED setting in settings.py and .env.example, enhance README with MCP runtime details, and implement MCP runtime decision logic in agent.py. Update agent instructions and ensure fallback to legacy runtime when MCP is unavailable.

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.

Refactor PocketTTS and test cases: Remove unused sample rate parameters in _tensor_to_pcm_bytes

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.

Add error handling for session bootstrap failures: Implement a client-safe error response payload in session_bootstrap.py and update Streamlit routes to use this new error handling.

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 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.

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.