Enhance ASR service descriptions and provider feedback in wizard.py#290
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AnkushMalaker merged 1 commit intodevfrom Feb 7, 2026
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Enhance ASR service descriptions and provider feedback in wizard.py#290AnkushMalaker merged 1 commit intodevfrom
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Feb 7, 2026
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- Updated the description for the 'asr-services' to remove the specific mention of 'Parakeet', making it more general.
- Improved the console output for auto-selected services to include the transcription provider label, enhancing user feedback during service selection.
- Updated the description for the 'asr-services' to remove the specific mention of 'Parakeet', making it more general. - Improved the console output for auto-selected services to include the transcription provider label, enhancing user feedback during service selection.
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Feb 9, 2026
* Enhance ASR service descriptions and provider feedback in wizard.py (#290) - Updated the description for the 'asr-services' to remove the specific mention of 'Parakeet', making it more general. - Improved the console output for auto-selected services to include the transcription provider label, enhancing user feedback during service selection. * Refactor Obsidian and Knowledge Graph integration in services and setup - Removed redundant Obsidian and Knowledge Graph configuration checks from services.py, streamlining the command execution process. - Updated wizard.py to enhance user experience by setting default options for speaker recognition during service selection. - Improved Neo4j password handling in setup processes, ensuring consistent configuration prompts and feedback. - Introduced a new cron scheduler for managing scheduled tasks, enhancing the backend's automation capabilities. - Added new entity annotation features, allowing for corrections and updates to knowledge graph entities directly through the API. * Enhance ASR services configuration and VibeVoice integration - Added new configuration options for VibeVoice ASR in defaults.yml, including batching parameters for audio processing. - Updated Docker Compose files to mount the config directory, ensuring access to ASR service configurations. - Enhanced the VibeVoice transcriber to load configuration settings from defaults.yml, allowing for dynamic adjustments via environment variables. - Introduced quantization options for model loading in the VibeVoice transcriber, improving performance and flexibility. - Refactored the speaker identification process to streamline audio handling and improve logging for better debugging. - Updated documentation to reflect new configuration capabilities and usage instructions for the VibeVoice ASR provider. * Enhance LangFuse integration and memory reprocessing capabilities - Introduced functions for checking LangFuse configuration in services.py, ensuring proper setup for observability. - Updated wizard.py to facilitate user input for LangFuse configuration, including options for local and external setups. - Implemented memory reprocessing logic in memory services to update existing memories based on speaker re-identification. - Enhanced speaker recognition client to support per-segment identification, improving accuracy during reprocessing. - Refactored various components to streamline handling of LangFuse parameters and improve overall service management. * Enhance service management and user input handling - Updated services.py to include LangFuse configuration checks during service startup, improving observability setup. - Refactored wizard.py to utilize a masked input for Neo4j password prompts, enhancing user experience and security. - Improved cron scheduler in advanced_omi_backend to manage active tasks and validate cron expressions, ensuring robust job execution. - Enhanced speaker recognition client documentation to clarify user_id limitations, preparing for future multi-user support. - Updated knowledge graph routes to enforce validation on entity updates, ensuring at least one field is provided for updates. * fix: Plugin System Refactor (#301) * Refactor connect-omi.py for improved device selection and user interaction - Replaced references to the chronicle Bluetooth library with friend_lite for device management. - Removed the list_devices function and implemented a new prompt_user_to_pick_device function to enhance user interaction when selecting OMI/Neo devices. - Updated the find_and_set_omi_mac function to utilize the new device selection method, improving the overall flow of device connection. - Added a new scan_devices.py script for quick scanning of neo/neosapien devices, enhancing usability. - Updated README.md to reflect new usage instructions and prerequisites for connecting to OMI devices over Bluetooth. - Enhanced start.sh to ensure proper environment variable setup for macOS users. * Add friend-lite-sdk: Initial implementation of Python SDK for OMI/Friend Lite BLE devices - Introduced the friend-lite-sdk, a Python SDK for OMI/Friend Lite BLE devices, enabling audio streaming, button events, and transcription functionalities. - Added LICENSE and NOTICE files to clarify licensing and attribution. - Created pyproject.toml for package management, specifying dependencies and project metadata. - Developed core modules including bluetooth connection handling, button event parsing, audio decoding, and transcription capabilities. - Implemented example usage in README.md to guide users on installation and basic functionality. - Enhanced connect-omi.py to utilize the new SDK for improved device management and event handling. - Updated requirements.txt to reference the new SDK for local development. This commit lays the foundation for further enhancements and integrations with OMI devices. * Enhance client state and plugin architecture for button event handling - Introduced a new `markers` list in `ClientState` to collect button event data during sessions. - Added `add_marker` method to facilitate the addition of markers to the current session. - Implemented `on_button_event` method in the `BasePlugin` class to handle device button events, providing context data for button state and timestamps. - Updated `PluginRouter` to route button events to the appropriate plugin handler. - Enhanced conversation job handling to attach markers from Redis sessions, improving the tracking of button events during conversations. * Move plugins locatino - Introduced the Email Summarizer plugin that automatically sends email summaries upon conversation completion. - Implemented SMTP email service for sending formatted HTML and plain text emails. - Added configuration options for SMTP settings and email content in `config.yml`. - Created setup script for easy configuration of SMTP credentials and plugin orchestration. - Enhanced documentation with usage instructions and troubleshooting tips for the plugin. - Updated existing plugin architecture to support new event handling for email summaries. * Enhance Docker Compose and Plugin Management - Added external plugins directory to Docker Compose files for better plugin management. - Updated environment variables for MongoDB and Redis services to ensure consistent behavior. - Introduced new dependencies in `uv.lock` for improved functionality. - Refactored audio processing to support various audio formats and enhance error handling. - Implemented new plugin event types and services for better integration and communication between plugins. - Enhanced conversation and session management to support new closing mechanisms and event logging. * Update audio processing and event logging - Increased the maximum event log size in PluginRouter from 200 to 1000 for improved event tracking. - Refactored audio stream producer to dynamically read audio format from Redis session metadata, enhancing flexibility in audio handling. - Updated transcription job processing to utilize session-specific audio format settings, ensuring accurate audio processing. - Enhanced audio file writing utility to accept PCM parameters, allowing for better control over audio data handling. * Add markers list to ClientState and update timeout trigger comment - Introduced a new `markers` list in `ClientState` to track button event data during conversations. - Updated comment in `open_conversation_job` to clarify the behavior of the `timeout_triggered` variable, ensuring better understanding of session management. * Refactor audio file logging and error handling - Updated audio processing logs to consistently use the `filename` variable instead of `file.filename` for clarity. - Enhanced error logging to utilize the `filename` variable, improving traceability of issues during audio processing. - Adjusted title generation logic to handle cases where the filename is "unknown," ensuring a default title is used. - Minor refactor in conversation closing logs to use `user.user_id` for better consistency in user identification. * Enhance conversation retrieval with pagination and orphan handling - Updated `get_conversations` function to support pagination through `limit` and `offset` parameters, improving performance for large datasets. - Consolidated query logic to fetch both normal and orphan conversations in a single database call, reducing round-trips and enhancing efficiency. - Modified the response structure to include total count, limit, and offset in the returned data for better client-side handling. - Adjusted database indexing to optimize queries for paginated results, ensuring faster access to conversation data. * Refactor connection logging in transcribe function - Moved connection logging for the Wyoming server to a more structured format within the `transcribe_wyoming` function. - Ensured that connection attempts and successes are logged consistently for better traceability during audio transcription processes.
AnkushMalaker
added a commit
that referenced
this pull request
Feb 15, 2026
* Enhance ASR service descriptions and provider feedback in wizard.py - Updated the description for the 'asr-services' to remove the specific mention of 'Parakeet', making it more general. - Improved the console output for auto-selected services to include the transcription provider label, enhancing user feedback during service selection. * Implement LangFuse integration for observability and prompt management - Added LangFuse configuration options in the .env.template for observability and prompt management. - Introduced setup_langfuse method in ChronicleSetup to handle LangFuse initialization and configuration prompts. - Enhanced prompt management by integrating a centralized PromptRegistry for dynamic prompt retrieval and registration. - Updated various services to utilize prompts from the PromptRegistry, improving flexibility and maintainability. - Refactored OpenAI client initialization to support optional LangFuse tracing, enhancing observability during API interactions. - Added new prompt defaults for memory management and conversation handling, ensuring consistent behavior across the application. * Enhance LangFuse integration and service management - Added LangFuse service configuration in services.py and wizard.py, including paths, commands, and descriptions. - Implemented auto-selection for LangFuse during service setup, improving user experience. - Enhanced service startup process to display prompt management tips for LangFuse, guiding users on editing AI prompts. - Updated run_service_setup to handle LangFuse-specific parameters, including admin credentials and API keys, ensuring seamless integration with backend services. * Feat/better reprocess memory (#300) * Enhance ASR service descriptions and provider feedback in wizard.py (#290) - Updated the description for the 'asr-services' to remove the specific mention of 'Parakeet', making it more general. - Improved the console output for auto-selected services to include the transcription provider label, enhancing user feedback during service selection. * Refactor Obsidian and Knowledge Graph integration in services and setup - Removed redundant Obsidian and Knowledge Graph configuration checks from services.py, streamlining the command execution process. - Updated wizard.py to enhance user experience by setting default options for speaker recognition during service selection. - Improved Neo4j password handling in setup processes, ensuring consistent configuration prompts and feedback. - Introduced a new cron scheduler for managing scheduled tasks, enhancing the backend's automation capabilities. - Added new entity annotation features, allowing for corrections and updates to knowledge graph entities directly through the API. * Enhance ASR services configuration and VibeVoice integration - Added new configuration options for VibeVoice ASR in defaults.yml, including batching parameters for audio processing. - Updated Docker Compose files to mount the config directory, ensuring access to ASR service configurations. - Enhanced the VibeVoice transcriber to load configuration settings from defaults.yml, allowing for dynamic adjustments via environment variables. - Introduced quantization options for model loading in the VibeVoice transcriber, improving performance and flexibility. - Refactored the speaker identification process to streamline audio handling and improve logging for better debugging. - Updated documentation to reflect new configuration capabilities and usage instructions for the VibeVoice ASR provider. * Enhance LangFuse integration and memory reprocessing capabilities - Introduced functions for checking LangFuse configuration in services.py, ensuring proper setup for observability. - Updated wizard.py to facilitate user input for LangFuse configuration, including options for local and external setups. - Implemented memory reprocessing logic in memory services to update existing memories based on speaker re-identification. - Enhanced speaker recognition client to support per-segment identification, improving accuracy during reprocessing. - Refactored various components to streamline handling of LangFuse parameters and improve overall service management. * Enhance service management and user input handling - Updated services.py to include LangFuse configuration checks during service startup, improving observability setup. - Refactored wizard.py to utilize a masked input for Neo4j password prompts, enhancing user experience and security. - Improved cron scheduler in advanced_omi_backend to manage active tasks and validate cron expressions, ensuring robust job execution. - Enhanced speaker recognition client documentation to clarify user_id limitations, preparing for future multi-user support. - Updated knowledge graph routes to enforce validation on entity updates, ensuring at least one field is provided for updates. * fix: Plugin System Refactor (#301) * Refactor connect-omi.py for improved device selection and user interaction - Replaced references to the chronicle Bluetooth library with friend_lite for device management. - Removed the list_devices function and implemented a new prompt_user_to_pick_device function to enhance user interaction when selecting OMI/Neo devices. - Updated the find_and_set_omi_mac function to utilize the new device selection method, improving the overall flow of device connection. - Added a new scan_devices.py script for quick scanning of neo/neosapien devices, enhancing usability. - Updated README.md to reflect new usage instructions and prerequisites for connecting to OMI devices over Bluetooth. - Enhanced start.sh to ensure proper environment variable setup for macOS users. * Add friend-lite-sdk: Initial implementation of Python SDK for OMI/Friend Lite BLE devices - Introduced the friend-lite-sdk, a Python SDK for OMI/Friend Lite BLE devices, enabling audio streaming, button events, and transcription functionalities. - Added LICENSE and NOTICE files to clarify licensing and attribution. - Created pyproject.toml for package management, specifying dependencies and project metadata. - Developed core modules including bluetooth connection handling, button event parsing, audio decoding, and transcription capabilities. - Implemented example usage in README.md to guide users on installation and basic functionality. - Enhanced connect-omi.py to utilize the new SDK for improved device management and event handling. - Updated requirements.txt to reference the new SDK for local development. This commit lays the foundation for further enhancements and integrations with OMI devices. * Enhance client state and plugin architecture for button event handling - Introduced a new `markers` list in `ClientState` to collect button event data during sessions. - Added `add_marker` method to facilitate the addition of markers to the current session. - Implemented `on_button_event` method in the `BasePlugin` class to handle device button events, providing context data for button state and timestamps. - Updated `PluginRouter` to route button events to the appropriate plugin handler. - Enhanced conversation job handling to attach markers from Redis sessions, improving the tracking of button events during conversations. * Move plugins locatino - Introduced the Email Summarizer plugin that automatically sends email summaries upon conversation completion. - Implemented SMTP email service for sending formatted HTML and plain text emails. - Added configuration options for SMTP settings and email content in `config.yml`. - Created setup script for easy configuration of SMTP credentials and plugin orchestration. - Enhanced documentation with usage instructions and troubleshooting tips for the plugin. - Updated existing plugin architecture to support new event handling for email summaries. * Enhance Docker Compose and Plugin Management - Added external plugins directory to Docker Compose files for better plugin management. - Updated environment variables for MongoDB and Redis services to ensure consistent behavior. - Introduced new dependencies in `uv.lock` for improved functionality. - Refactored audio processing to support various audio formats and enhance error handling. - Implemented new plugin event types and services for better integration and communication between plugins. - Enhanced conversation and session management to support new closing mechanisms and event logging. * Update audio processing and event logging - Increased the maximum event log size in PluginRouter from 200 to 1000 for improved event tracking. - Refactored audio stream producer to dynamically read audio format from Redis session metadata, enhancing flexibility in audio handling. - Updated transcription job processing to utilize session-specific audio format settings, ensuring accurate audio processing. - Enhanced audio file writing utility to accept PCM parameters, allowing for better control over audio data handling. * Add markers list to ClientState and update timeout trigger comment - Introduced a new `markers` list in `ClientState` to track button event data during conversations. - Updated comment in `open_conversation_job` to clarify the behavior of the `timeout_triggered` variable, ensuring better understanding of session management. * Refactor audio file logging and error handling - Updated audio processing logs to consistently use the `filename` variable instead of `file.filename` for clarity. - Enhanced error logging to utilize the `filename` variable, improving traceability of issues during audio processing. - Adjusted title generation logic to handle cases where the filename is "unknown," ensuring a default title is used. - Minor refactor in conversation closing logs to use `user.user_id` for better consistency in user identification. * Enhance conversation retrieval with pagination and orphan handling - Updated `get_conversations` function to support pagination through `limit` and `offset` parameters, improving performance for large datasets. - Consolidated query logic to fetch both normal and orphan conversations in a single database call, reducing round-trips and enhancing efficiency. - Modified the response structure to include total count, limit, and offset in the returned data for better client-side handling. - Adjusted database indexing to optimize queries for paginated results, ensuring faster access to conversation data. * Refactor connection logging in transcribe function - Moved connection logging for the Wyoming server to a more structured format within the `transcribe_wyoming` function. - Ensured that connection attempts and successes are logged consistently for better traceability during audio transcription processes. * Feat/neo sdk (#302) * Update friend-lite-sdk for Neo1 device support and enhance documentation - Updated the friend-lite-sdk to version 0.3.0, reflecting the transition to support OMI/Neo1 BLE wearable devices. - Refactored the Bluetooth connection handling to introduce a new `WearableConnection` class, enhancing the connection lifecycle management for wearable devices. - Added a new `Neo1Connection` class for controlling Neo1 devices, including methods for sleep and wake functionalities. - Updated UUID constants to include Neo1-specific characteristics, improving device interaction capabilities. - Revised the plugin development guide to reflect changes in device naming and connection processes. - Removed outdated local OMI Bluetooth scripts and documentation to streamline the project structure and focus on wearable client development. * Refactor backend audio streaming to use Opus codec and enhance menu app functionality - Updated backend_sender.py to stream raw Opus audio instead of PCM, improving bandwidth efficiency. - Modified stream_to_backend function to handle Opus audio data and adjusted audio chunk parameters accordingly. - Enhanced main.py with new CLI commands for device scanning and connection management, improving user experience. - Introduced menu_app.py for a macOS menu bar application, providing a user-friendly interface for device management and status display. - Added README.md to document usage instructions and configuration details for the local wearable client. - Updated requirements.txt to include new dependencies for the menu app and service management. - Implemented service.py for managing launchd service installation and configuration on macOS, enabling auto-start on login. * Refactor audio processing and queue management in local wearable client - Removed the audio queue in favor of a dedicated BLE data queue and backend queue for improved data handling. - Enhanced the `connect_and_stream` function to streamline audio decoding and writing to the local file sink. - Updated the handling of BLE data to ensure robust queue management and error logging. - Improved task management during device disconnection to ensure proper cleanup and error handling. - Updated requirements.txt to specify a minimum version for easy_audio_interfaces, ensuring compatibility.
AnkushMalaker
added a commit
that referenced
this pull request
Feb 15, 2026
* Enhance ASR service descriptions and provider feedback in wizard.py - Updated the description for the 'asr-services' to remove the specific mention of 'Parakeet', making it more general. - Improved the console output for auto-selected services to include the transcription provider label, enhancing user feedback during service selection. * Implement LangFuse integration for observability and prompt management - Added LangFuse configuration options in the .env.template for observability and prompt management. - Introduced setup_langfuse method in ChronicleSetup to handle LangFuse initialization and configuration prompts. - Enhanced prompt management by integrating a centralized PromptRegistry for dynamic prompt retrieval and registration. - Updated various services to utilize prompts from the PromptRegistry, improving flexibility and maintainability. - Refactored OpenAI client initialization to support optional LangFuse tracing, enhancing observability during API interactions. - Added new prompt defaults for memory management and conversation handling, ensuring consistent behavior across the application. * Enhance LangFuse integration and service management - Added LangFuse service configuration in services.py and wizard.py, including paths, commands, and descriptions. - Implemented auto-selection for LangFuse during service setup, improving user experience. - Enhanced service startup process to display prompt management tips for LangFuse, guiding users on editing AI prompts. - Updated run_service_setup to handle LangFuse-specific parameters, including admin credentials and API keys, ensuring seamless integration with backend services. * Feat/better reprocess memory (#300) * Enhance ASR service descriptions and provider feedback in wizard.py (#290) - Updated the description for the 'asr-services' to remove the specific mention of 'Parakeet', making it more general. - Improved the console output for auto-selected services to include the transcription provider label, enhancing user feedback during service selection. * Refactor Obsidian and Knowledge Graph integration in services and setup - Removed redundant Obsidian and Knowledge Graph configuration checks from services.py, streamlining the command execution process. - Updated wizard.py to enhance user experience by setting default options for speaker recognition during service selection. - Improved Neo4j password handling in setup processes, ensuring consistent configuration prompts and feedback. - Introduced a new cron scheduler for managing scheduled tasks, enhancing the backend's automation capabilities. - Added new entity annotation features, allowing for corrections and updates to knowledge graph entities directly through the API. * Enhance ASR services configuration and VibeVoice integration - Added new configuration options for VibeVoice ASR in defaults.yml, including batching parameters for audio processing. - Updated Docker Compose files to mount the config directory, ensuring access to ASR service configurations. - Enhanced the VibeVoice transcriber to load configuration settings from defaults.yml, allowing for dynamic adjustments via environment variables. - Introduced quantization options for model loading in the VibeVoice transcriber, improving performance and flexibility. - Refactored the speaker identification process to streamline audio handling and improve logging for better debugging. - Updated documentation to reflect new configuration capabilities and usage instructions for the VibeVoice ASR provider. * Enhance LangFuse integration and memory reprocessing capabilities - Introduced functions for checking LangFuse configuration in services.py, ensuring proper setup for observability. - Updated wizard.py to facilitate user input for LangFuse configuration, including options for local and external setups. - Implemented memory reprocessing logic in memory services to update existing memories based on speaker re-identification. - Enhanced speaker recognition client to support per-segment identification, improving accuracy during reprocessing. - Refactored various components to streamline handling of LangFuse parameters and improve overall service management. * Enhance service management and user input handling - Updated services.py to include LangFuse configuration checks during service startup, improving observability setup. - Refactored wizard.py to utilize a masked input for Neo4j password prompts, enhancing user experience and security. - Improved cron scheduler in advanced_omi_backend to manage active tasks and validate cron expressions, ensuring robust job execution. - Enhanced speaker recognition client documentation to clarify user_id limitations, preparing for future multi-user support. - Updated knowledge graph routes to enforce validation on entity updates, ensuring at least one field is provided for updates. * fix: Plugin System Refactor (#301) * Refactor connect-omi.py for improved device selection and user interaction - Replaced references to the chronicle Bluetooth library with friend_lite for device management. - Removed the list_devices function and implemented a new prompt_user_to_pick_device function to enhance user interaction when selecting OMI/Neo devices. - Updated the find_and_set_omi_mac function to utilize the new device selection method, improving the overall flow of device connection. - Added a new scan_devices.py script for quick scanning of neo/neosapien devices, enhancing usability. - Updated README.md to reflect new usage instructions and prerequisites for connecting to OMI devices over Bluetooth. - Enhanced start.sh to ensure proper environment variable setup for macOS users. * Add friend-lite-sdk: Initial implementation of Python SDK for OMI/Friend Lite BLE devices - Introduced the friend-lite-sdk, a Python SDK for OMI/Friend Lite BLE devices, enabling audio streaming, button events, and transcription functionalities. - Added LICENSE and NOTICE files to clarify licensing and attribution. - Created pyproject.toml for package management, specifying dependencies and project metadata. - Developed core modules including bluetooth connection handling, button event parsing, audio decoding, and transcription capabilities. - Implemented example usage in README.md to guide users on installation and basic functionality. - Enhanced connect-omi.py to utilize the new SDK for improved device management and event handling. - Updated requirements.txt to reference the new SDK for local development. This commit lays the foundation for further enhancements and integrations with OMI devices. * Enhance client state and plugin architecture for button event handling - Introduced a new `markers` list in `ClientState` to collect button event data during sessions. - Added `add_marker` method to facilitate the addition of markers to the current session. - Implemented `on_button_event` method in the `BasePlugin` class to handle device button events, providing context data for button state and timestamps. - Updated `PluginRouter` to route button events to the appropriate plugin handler. - Enhanced conversation job handling to attach markers from Redis sessions, improving the tracking of button events during conversations. * Move plugins locatino - Introduced the Email Summarizer plugin that automatically sends email summaries upon conversation completion. - Implemented SMTP email service for sending formatted HTML and plain text emails. - Added configuration options for SMTP settings and email content in `config.yml`. - Created setup script for easy configuration of SMTP credentials and plugin orchestration. - Enhanced documentation with usage instructions and troubleshooting tips for the plugin. - Updated existing plugin architecture to support new event handling for email summaries. * Enhance Docker Compose and Plugin Management - Added external plugins directory to Docker Compose files for better plugin management. - Updated environment variables for MongoDB and Redis services to ensure consistent behavior. - Introduced new dependencies in `uv.lock` for improved functionality. - Refactored audio processing to support various audio formats and enhance error handling. - Implemented new plugin event types and services for better integration and communication between plugins. - Enhanced conversation and session management to support new closing mechanisms and event logging. * Update audio processing and event logging - Increased the maximum event log size in PluginRouter from 200 to 1000 for improved event tracking. - Refactored audio stream producer to dynamically read audio format from Redis session metadata, enhancing flexibility in audio handling. - Updated transcription job processing to utilize session-specific audio format settings, ensuring accurate audio processing. - Enhanced audio file writing utility to accept PCM parameters, allowing for better control over audio data handling. * Add markers list to ClientState and update timeout trigger comment - Introduced a new `markers` list in `ClientState` to track button event data during conversations. - Updated comment in `open_conversation_job` to clarify the behavior of the `timeout_triggered` variable, ensuring better understanding of session management. * Refactor audio file logging and error handling - Updated audio processing logs to consistently use the `filename` variable instead of `file.filename` for clarity. - Enhanced error logging to utilize the `filename` variable, improving traceability of issues during audio processing. - Adjusted title generation logic to handle cases where the filename is "unknown," ensuring a default title is used. - Minor refactor in conversation closing logs to use `user.user_id` for better consistency in user identification. * Enhance conversation retrieval with pagination and orphan handling - Updated `get_conversations` function to support pagination through `limit` and `offset` parameters, improving performance for large datasets. - Consolidated query logic to fetch both normal and orphan conversations in a single database call, reducing round-trips and enhancing efficiency. - Modified the response structure to include total count, limit, and offset in the returned data for better client-side handling. - Adjusted database indexing to optimize queries for paginated results, ensuring faster access to conversation data. * Refactor connection logging in transcribe function - Moved connection logging for the Wyoming server to a more structured format within the `transcribe_wyoming` function. - Ensured that connection attempts and successes are logged consistently for better traceability during audio transcription processes. * Refactor configuration management and enhance plugin architecture - Replaced PyYAML with ruamel.yaml for improved YAML handling, preserving quotes and enhancing configuration loading. - Updated ConfigManager to utilize ruamel.yaml for loading and saving configuration files, ensuring better error handling and validation. - Enhanced service startup messages to display access URLs for backend services, improving user experience. - Introduced new plugin health tracking in PluginRouter, allowing for better monitoring of plugin initialization and error states. - Refactored audio stream client and conversation management to streamline audio processing and improve error handling. - Updated Docker and requirements configurations to include ruamel.yaml, ensuring compatibility across environments. * refactor clean up script * cleanup partial mycelia integration * Refactor configuration management and remove Mycelia integration - Updated ConfigManager to remove references to the Mycelia memory provider, simplifying the memory provider options to only include "chronicle" and "openmemory_mcp". - Cleaned up Makefile by removing Mycelia-related targets and help descriptions, streamlining the build process. - Enhanced cleanup script documentation for clarity on usage and options. - Introduced LLM operation configurations to improve model management and prompt optimization capabilities. * Refactor Docker and cleanup scripts to remove 'uv' command usage - Updated cleanup.sh to directly execute the Python script without 'uv' command. - Modified Docker Compose files to remove 'uv run' from service commands, simplifying execution. - Enhanced start.sh to reflect changes in command usage and improve clarity in usage instructions. - Introduced a new transcription job timeout configuration in the backend, allowing for dynamic timeout settings. - Added insert annotation functionality in the API, enabling users to insert new segments in conversations. - Implemented memory retrieval for conversations, enhancing the ability to fetch related memories. - Improved error handling and logging across various modules for better traceability and debugging. * Add backend worker health check and job clearing functionality - Introduced a new function `get_backend_worker_health` to retrieve health metrics from the backend's /health endpoint, including worker count and queue status. - Updated `show_quick_status` to display worker health information, alerting users to potential issues with registered workers. - Added a new API endpoint `/jobs` to allow admin users to clear finished and failed jobs from all queues, enhancing job management capabilities. - Updated the frontend Queue component to include a button for clearing jobs, improving user interaction and management of job statuses. * Update plugin event descriptions and refactor event handling - Reduced redundancy by embedding descriptions directly within the PluginEvent enum, enhancing clarity and maintainability. - Removed the EVENT_DESCRIPTIONS dictionary, streamlining the event handling process in the plugin assistant. - Updated references in the plugin assistant to utilize the new description attributes, ensuring consistent event metadata usage.
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