- 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.
- Introduced mechanisms to handle agent-to-agent (A2A) calls, including automatic history skipping for forked calls and proper source tracking.
- Enhanced context management with the addition of ForkParentInfo to facilitate child stack creation without race conditions.
- Updated JSAPI methods to ensure correct handling of sub-agent calls, maintaining output isolation and preventing history pollution.
- Improved documentation to clarify the behavior of A2A calls and context management in concurrent scenarios.
- Added initialization for the Agent JSAPI factory to support ctx.agent.* methods, improving agent interaction capabilities.
- Introduced a new agent object in the JSAPI context for calling other agents, enhancing modularity.
- Implemented an OnMessage callback in the context options to handle messages sent via ctx.Send(), allowing for more flexible message processing.
- Updated the `ChatBuffer` to support streaming messages, allowing for content to be appended and finalized with `SendStream` and `End` methods.
- Modified the `AddAssistantMessage` method to include a message ID, improving message tracking and retrieval.
- Implemented new methods for appending content to streaming messages and completing them, ensuring accurate message storage and event handling.
- Revised tests to validate the new streaming functionality and ensure proper integration with existing message handling processes.
- Updated `CHAT_STORAGE_DESIGN.md` to reflect changes in message storage and indexing, including unique constraints for message IDs within requests.
- Introduced methods for initializing and managing a chat buffer, allowing for efficient storage of user inputs and assistant messages during chat sessions.
- Added functionality to track execution steps, including beginning and completing steps, with support for capturing space snapshots and handling errors.
- Enhanced the FlushBuffer method to save buffered messages and steps to the database, ensuring data integrity and recovery capabilities.
- Updated the Stream method to integrate buffer management, ensuring proper handling of chat sessions and message storage.
- Added comprehensive tests to validate buffer initialization, user input handling, and step tracking functionalities.
- Updated the Stream, BuildContent, and LLM execution methods to accept an Options parameter, allowing for more flexible context handling.
- Removed debug print statements to clean up the code and improve readability.
- Enhanced locale handling in the loadMap function to automatically inject assistant name and description into all locales, ensuring better localization support.
- Introduced output skipping functionality in context options to manage internal A2A calls more effectively.
- Improved output writer resolution logic to prioritize context settings, enhancing output management during agent calls.
- 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.
- Implemented logic to auto-generate ChunkID for messages when not provided, enhancing message tracking.
- Utilized IDGenerator if available; otherwise, fallback to message.GenerateNanoID for unique identification.
- Improved message handling consistency by ensuring ChunkID is always set for non-event messages.
- Added EndBlock method to explicitly mark the end of a message block, sending a block_end event.
- Updated message handling to include lifecycle events for message start and end, improving tracking and management of message durations.
- Enhanced message metadata structure to support chunk counting and message types, facilitating better message operations.
- Improved JSAPI documentation to include new lifecycle management features, clarifying usage for developers.
- Introduced recordMessageMetadata and getMessageMetadata methods to manage metadata for sent messages, enabling BlockID and ThreadID inheritance in delta operations.
- Implemented new methods (Append, Merge, Set) in the context to enhance message management capabilities, allowing for more flexible message updates.
- Updated the Send method to automatically manage BlockID and ThreadID for delta operations, improving message handling consistency.
- Enhanced JSAPI documentation to reflect new methods and usage patterns, improving developer experience and clarity.
