- Added support for "execute" message type to track tool execution observations within the sandbox environment.
- Implemented handling for execute messages in the stream processing, allowing for real-time updates on tool execution status.
- Enhanced the stream parser to manage the lifecycle of execute messages, including merging input and output data.
- Updated the stream handler to accommodate new message types, improving overall message processing capabilities.
- Refactored related tests to ensure coverage for the new execute message functionality, enhancing reliability.
- Remove the `LoadModelCapabilities` test and associated model capabilities initialization from the agent, streamlining the loading process.
- Update the LLM provider implementations to utilize a unified `Capabilities` structure, replacing references to `openai.Capabilities` with `llm.Capabilities`.
- Enhance capability retrieval methods to simplify the extraction of connector capabilities, ensuring compatibility across different LLM providers.
- Clean up unused functions and variables related to model capabilities, improving code maintainability.
- Added support for converting extended types (file, data) to standard LLM types (text, image_url, input_audio) in the Stream method.
- Introduced a new agentCallerWrapper to facilitate agent calls from the content package.
- Implemented ThreadID management for nested agent calls to improve concurrent stream identification.
- Enhanced message handling to include metadata for message_start and message_end events, allowing for better tracking of message states.
- Removed deprecated vision capability checks from the Assistant initialization process, streamlining the codebase.
- Added new content types (file, data) to the context types for improved message content handling.
- Updated the model capabilities throughout the agent to utilize the new gouOpenAI.Capabilities struct instead of the previous ModelCapabilities.
- Adjusted related methods and types to ensure compatibility with the new capabilities structure, enhancing clarity and maintainability.
- Improved context handling and message processing by directly integrating OpenAI capabilities, streamlining the overall architecture.
- Replaced group-related event types with message-specific types, enhancing clarity in event management.
- Updated stream handling functions to utilize new message start and end events, improving the granularity of message tracking.
- Refactored context management to integrate a context-scoped ID generator for unique message identifiers.
- Removed deprecated group handling methods and streamlined message processing logic.
- Updated tests and documentation to reflect changes in message handling and ensure proper functionality.
- Updated message structures to replace 'StreamStartData' and 'StreamEndData' with 'EventStreamStartData' and 'EventStreamEndData' for better clarity and consistency.
- Introduced 'EventMessageStartData' and 'EventMessageEndData' to represent individual message lifecycle events, enhancing the granularity of message tracking.
- Refactored the 'streamState' and 'groupTracker' to utilize the new message structures, improving the organization and handling of streaming events.
- Enhanced the context management by integrating an ID generator for unique message identifiers, facilitating better tracking of message sequences.
- Updated documentation and tests to reflect the new message structures and ensure proper functionality across the system.
- Introduced SendGroupStart and SendGroupEnd methods for better control over message grouping, allowing for automatic ID generation and event handling.
- Updated streamState structure to track group IDs, message sequences, and chunk counts, improving message organization during streaming.
- Refactored message handling to eliminate the 'done' field, signaling message completion through group_end events instead.
- Revised JSAPI documentation to reflect new methods and usage patterns, enhancing clarity for developers.
- Improved test cases to validate new group handling features and ensure proper functionality.
- Introduced a new message type `user_input` to handle user input specifically for frontend display.
- Defined `UserInputProps` structure to standardize the properties of user input messages, including content, role, and name.
- Implemented `NewUserInputMessage` function to facilitate the creation of user input messages.
- Updated built-in type checks to include the new user input type, ensuring compatibility across the system.
- Refactored the Stream method to retrieve connector capabilities early, allowing output adapters to utilize them effectively.
- Introduced a new Info method in the Assistant to provide structured assistant information, enhancing context accessibility.
- Updated StreamStartData to include additional fields such as ChatID and Assistant info for better event tracking.
- Improved error handling in the Stream method to ensure robust management of connector retrieval failures.
- Enhanced internationalization support for stream event messages, providing localized output for different clients.
- Added support for lifecycle event messages, including a new event type for tracking stream states (e.g., stream_start, stream_end).
- Introduced a NewEventMessage function to create event messages with structured properties.
- Updated the output package to include event messages in the built-in types, ensuring compatibility with CUI clients while remaining silent for OpenAI clients.
- Enhanced the DefaultStreamHandler to utilize event messages for better lifecycle tracking during streaming operations.
- Improved error handling and logging in the OpenAI provider to capture and report streaming errors effectively.
- Implemented a state management system for handling different streaming chunk types, including stream start, group start, text, thinking, tool calls, metadata, errors, and stream end.
- Introduced a new Send method in the context to facilitate message sending to the client.
- Enhanced the output package with message sending capabilities, including support for message groups and flushing.
- Improved error handling and message ID generation for better streaming reliability and user feedback.
