- Added support for managing user transcripts, including pending states and timestamps.
- Implemented methods to handle user transcript completion and deferred assistant messages.
- Updated event handling to ensure user transcripts are emitted before assistant responses.
- Enhanced tests to verify the correct order of transcript and assistant message emissions during user interactions.
- Introduced Qwen-Audio Realtime service for speech-to-speech processing in Pipecat.
- Updated interface catalog to include Qwen-Audio Realtime capabilities.
- Enhanced model resource testing to support new service.
- Added configuration options for audio sample rates and turn detection modes.
- Updated documentation to reflect integration details and usage instructions.
- Extend McpTransport to support "sse" in schemas.
- Refactor McpToolClient to handle both "streamable_http" and "sse" transports.
- Introduce McpServerDialog for managing MCP server configurations, including transport settings and tool synchronization.
- Replace McpServersSection with the new dialog component for improved server management.
- Add tests for MCP transport handling and server dialog functionality.
- Introduce WorkflowAgentStage to manage agent stage configurations and enhance interaction with the workflow engine.
- Implement WorkflowEdgeEvaluator for priority-aware edge evaluation, improving routing decisions based on conditions and user turns.
- Update WorkflowBrain to handle user turns and routing more effectively, ensuring agents cannot have only one default path.
- Enhance CallEndCoordinator to track speech events and manage call termination based on queued speech.
- Add new models and output handling for workflow interactions, improving clarity and maintainability.
- Update tests to validate the new routing logic and agent behavior under various scenarios.
- Update WorkflowBrain to handle greeting playback more effectively, ensuring that the initial greeting completes before transitioning to the first node.
- Introduce new methods for managing greeting states and conditions, enhancing the interaction flow for user turns.
- Refactor WorkflowLLMRouter to improve routing logic and ensure proper handling of conditional paths.
- Enhance tests to verify the correct behavior of greeting management and routing under various scenarios, including waiting for audio playback to finish.
- Update frontend components to reflect changes in edge handling and improve user experience in workflow configurations.
- Add begin_response and finish_after_current_speech methods to CallEndCoordinator for better management of speech events.
- Update PromptBrain to utilize new methods, ensuring proper handling of generated closing speech and tool-only calls.
- Enhance tests to verify the correct behavior of speech tracking and response handling in various scenarios, including waiting for audio to finish before ending calls.
- Introduce a new test suite for CallEndCoordinator to validate the interaction with speech frames.
- Introduce greeting context handling in BaseBrain and WorkflowBrain to manage assistant greetings effectively.
- Implement prepare_greeting_context method to add greeting messages to the local context while preserving playback order.
- Update pipeline event handling to ensure greeting timestamps are maintained until the client is ready.
- Enhance tests to verify the correct behavior of greeting context management in various scenarios.
- Remove unused imports and classes from pipeline.py to streamline the codebase.
- Consolidate dynamic variable handling and workflow management in AssistantPage, enhancing clarity and maintainability.
- Update WorkflowEditor to utilize a more modular approach, improving the overall architecture and reducing complexity.
- Enhance the import structure across components for better organization and readability.
- Implement on_client_ready in BaseBrain to handle client-visible state after the app message channel is ready.
- Extend WorkflowBrain with on_client_ready to replay state that may have been emitted before WebRTC data was ready.
- Update pipeline to call on_client_ready when a client connects.
- Enhance tests to verify the correct behavior of on_client_ready in WorkflowBrain.
- Update ConversationRecorder to include source and nodeId metadata in transcripts for better context tracking.
- Introduce optional variable handling in DynamicVariableStore, allowing for unset variables to be rendered as empty without raising errors.
- Refactor WorkflowBrain to apply turn configurations and manage interaction policies dynamically, improving agent responsiveness.
- Implement tests to ensure proper handling of updated session variables and workflow metadata in various scenarios.
- Introduce WorkflowLLMRouter for pre-response LLM routing, allowing agents to determine the appropriate function to call based on user input.
- Implement UserTurnRoutingProcessor to manage user turns before reaching the LLM, ensuring proper routing and handling of user messages.
- Refactor WorkflowBrain to integrate new routing logic and enhance agent stage configuration, including entry modes and resource management.
- Update service factory to support dynamic LLM resource configuration based on workflow settings.
- Add tests for new routing functionality and ensure proper handling of user messages in various scenarios.
- Introduce RuntimeModelResource and RuntimeKnowledgeBase classes to manage workflow resources.
- Update AssistantConfig to include workflow_model_resources and workflow_knowledge_bases for better integration.
- Refactor validation and processing logic in routes and services to accommodate workflow types.
- Implement dynamic variable support for workflow assistants and enhance graph normalization.
- Add ToolExecutor for reusable tool execution across different assistant types.
- Update various services to ensure compatibility with new workflow features and improve error handling.
- Add new HTTP endpoints for handling WebRTC offers and ICE candidates, enhancing the signaling process for voice interactions.
- Introduce dynamic variable decoding from request headers to support flexible offer payloads.
- Refactor existing WebSocket handling to accommodate new offer processing logic.
- Update frontend dependencies to include Pipecat client libraries for improved WebRTC transport management.
- Streamline voice preview functionality by integrating SmallWebRTCTransport for better media handling.
- Introduce dynamic variable definitions in AssistantConfig and Assistant models, allowing for flexible prompt customization.
- Implement validation for dynamic variable names and types in the schema.
- Update backend services and routes to handle dynamic variables in assistant configurations and runtime processing.
- Enhance frontend components to support dynamic variable definitions, including a new editor for managing variables.
- Add tests to ensure proper functionality and validation of dynamic variables in various scenarios.
- Introduce new fields for knowledge retrieval configuration in AssistantConfig and Assistant models, including mode, top_n, and score_threshold.
- Implement KnowledgeRetrievalConfig schema with validation for top_n.
- Update backend services and routes to handle knowledge retrieval settings.
- Enhance frontend components to support knowledge retrieval configuration, including a new dialog for advanced settings.
- Add tests for knowledge retrieval configuration validation and description generation.
- Add new models for `KnowledgeDocument` and `KnowledgeChunk` to manage document ingestion and chunking.
- Implement S3-compatible storage integration for knowledge documents, allowing for file uploads and retrieval.
- Introduce API endpoints for managing knowledge bases and documents, including creation, deletion, and searching.
- Update frontend components to support knowledge base configuration and document management, improving user interaction.
- Enhance backend services for knowledge processing and retrieval, ensuring robust handling of document statuses and errors.
- Introduce a new `turnConfig` field in `AssistantConfig` and `Assistant` models to manage user interaction settings.
- Implement `TurnConfig`, `BargeInConfig`, `VadConfig`, and `TurnDetectionConfig` schemas to define turn management strategies.
- Update the backend to handle turn configuration in the database and during assistant operations.
- Enhance frontend components with a `TurnConfigEditor` for configuring turn settings, including VAD and barge-in strategies.
- Modify existing pages to integrate turn configuration, improving user experience and interaction capabilities.
- Introduce new fields `dify_api_url` and `dify_api_key` in `AssistantConfig` for Dify API integration.
- Update `requirements.txt` to include `dify-client-python` for Dify SDK support.
- Modify `config_resolver` to handle Dify connection information.
- Add a new `globalNode` type in workflow specifications to provide unified settings across workflows.
- Enhance node specifications with additional constraints and default values for better configuration management.
- Update frontend components to support the new `globalNode` type and its properties, improving workflow editor functionality.
- Implement a new API endpoint for duplicating tools in the backend.
- Add a duplicate_tool function in ComponentsToolsPage to handle tool duplication requests.
- Update the UI to include a dropdown menu option for duplicating tools, improving user experience.
- Refactor the remove function to accept a resource object instead of an ID for better clarity and maintainability.
- Implement a new API endpoint for deleting conversations in the backend.
- Enhance the HistoryPage component to include a dropdown menu for conversation actions, allowing users to delete conversations.
- Update the pagination logic to handle conversation removal and improve user experience during deletion.
- Adjust the loading state and error handling for the delete operation, ensuring smooth interaction.
- Introduce new database models for conversation sessions, messages, and artifacts to support conversation history tracking.
- Implement API routes for listing conversations and retrieving detailed conversation data, enhancing user interaction with historical records.
- Add a conversation recorder service to persist conversation messages in real-time without disrupting ongoing calls.
- Update the frontend to display conversation history, including filtering and sorting options, improving user experience.
- Enhance the pipeline to integrate conversation history recording seamlessly during interactions.
- Introduce a new `RuntimeTool` model to encapsulate tool data for runtime sessions, including attributes like `id`, `name`, `function_name`, `type`, and `description`.
- Update the `AssistantConfig` model to include a list of reusable tools, allowing for better management of tools within assistant configurations.
- Modify the `config_resolver` service to fetch and resolve tools associated with assistants, ensuring they are available during runtime.
- Refactor tool-related CRUD operations in the `tools` route to support the new runtime execution model, enhancing the overall tool management system.
- Update documentation and comments to reflect changes in tool execution and configuration handling, improving clarity for future development.
- Introduce a new `sync_default_tools` function in `session.py` to ensure essential reusable tools are created without overwriting existing edits.
- Update the `lifespan` context manager in `app.py` to call `sync_default_tools`, enhancing the initialization process for the application.
- This change improves the management of default tools within the system, ensuring they are available for use while preserving user modifications.
- Introduce a new `Tool` model and `AssistantToolBinding` for managing reusable tools within the application.
- Implement CRUD operations for tools in the new `tools` route, allowing for the creation, retrieval, updating, and deletion of tools.
- Update the `Assistant` model to include a list of tool IDs, enabling assistants to utilize these tools.
- Enhance the backend routes to synchronize tool bindings with assistants, ensuring proper management of tool associations.
- Add frontend components for tool management, including a tool picker in the assistant configuration, improving user experience in tool selection.
- Create a mobile call page to facilitate video calls, integrating camera and microphone selection for enhanced communication capabilities.
- Update API definitions to include tool-related types and operations, ensuring consistency across the application.
- Add a migration script to create the necessary database tables for tools and bindings, supporting the new functionality.
- Introduce a new `auth` module with login, logout, and user verification endpoints for a single admin user.
- Update backend routes to require admin authentication for sensitive operations, enhancing security.
- Modify frontend components to include an authentication provider and gate, ensuring only authorized users can access the application.
- Implement a login page for admin access, improving user experience and security management.
- Update API request handling to redirect unauthorized users to the login page, ensuring proper access control.