- Renamed and refactored functions and variables to transition from connector settings to model capabilities, enhancing clarity and consistency.
- Updated the loading mechanism to read model capabilities from `models.yml` instead of `connectors.yml`.
- Adjusted the assistant's global settings to utilize model capabilities, ensuring proper integration with the new configuration structure.
- Enhanced the reasoning adapter to support temperature adjustment based on model capabilities, improving flexibility in handling reasoning parameters.
- Added DeepSeek API keys and model configurations to the GitHub workflows for both unit and PR tests.
- Introduced a new `ReasoningEffort` parameter in the `CompletionOptions` struct to manage reasoning levels for models like o1 and GPT-5.
- Updated the `ReasoningAdapter` to handle the new `ReasoningEffort` parameter, ensuring it is stripped if not supported by the model.
- Enhanced the OpenAI provider to preprocess options through adapters, improving the handling of reasoning content and ensuring compatibility with DeepSeek R1 reasoning format.
- Removed legacy and audio providers, consolidating functionality into a new architecture that separates API format handling from capability management.
- Updated the OpenAI provider to support capability adapters for tool calls, vision, audio, and reasoning, enhancing modularity and extensibility.
- Introduced a new method for detecting API formats and streamlined the provider selection process.
- Enhanced documentation to reflect the new architecture and clarify provider capabilities and usage.
- 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.
- Added context cancellation handling in the OpenAI provider's Stream and Post methods, allowing for graceful termination of operations when the context is cancelled.
- Implemented a new test, TestOpenAIStreamContextCancellation, to validate that streaming respects context cancellation, ensuring proper error handling and event emission during cancellation scenarios.
- Refactored context usage in existing methods to improve consistency and reliability in handling context across streaming operations.
- Removed unnecessary blank lines in the TestOpenAIStreamLifecycleEvents function to improve code readability.
- Adjusted log formatting for group_end event to ensure consistent output during test execution.
- Added support for stream lifecycle events including stream_start, stream_end, group_start, and group_end.
- Introduced new data structures for handling lifecycle event data, enhancing communication of stream boundaries and metadata.
- Updated the OpenAI provider to track and emit these events during streaming operations, improving UI/UX capabilities.
- Added tests to validate the correct emission and order of lifecycle events during streaming.
- Introduced TestOpenAIJSONMode and TestOpenAIJSONModePost to validate JSON response formatting for streaming and non-streaming requests.
- Added TestOpenAIJSONSchema and TestOpenAIJSONSchemaPost to ensure compliance with strict JSON schema validation.
- Enhanced request body construction in the OpenAI provider to support JSON schema details in response formats.
- Added message preprocessing in the base provider to filter unsupported content types (vision and audio) based on model capabilities.
- Introduced new methods in the OpenAI provider for handling streaming and non-streaming requests with retry logic and tool call validation.
- Enhanced request body building to support various options and improved error handling for API interactions.
- Implemented validation for tool call arguments against JSON schemas, ensuring compliance with expected formats.
- Upgraded Go version to 1.25 and updated several dependencies, including `testify` to v1.11.1 and added new indirect dependencies for JSON schema validation.
- Refactored the assistant's context management to utilize a new `context.Uses` structure, improving the handling of vision, audio, search, and fetch configurations.
- Enhanced the assistant's request building process to support new response formats, including JSON schema validation, ensuring better integration with various tools and services.
- Added global uses configuration to the assistant, allowing for centralized management of vision, audio, search, and fetch settings.
- Updated the Assistant struct and related methods to support the new Uses configuration, improving flexibility in assistant operations.
- Refactored the Stream method to utilize the new CompletionResponse type, enhancing response handling.
- Introduced new methods for building requests and managing capabilities, streamlining the assistant's interaction with various connectors.
- Updated the Stream method to return a structured response, including create, done, and completion hooks.
- Introduced new methods for managing message history and building LLM requests, enhancing modularity.
- Refactored the Script type to utilize a new hook structure, improving code organization.
- Removed the obsolete hooks file to streamline the codebase.
- Enhanced context types with additional fields for better integration with LLM models.
- Updated Stream and Run methods in the Assistant to use pointer receivers for context, enhancing performance and clarity.
- Introduced stack management in context handling, including initialization and cleanup of stack references.
- Enhanced the Release method in Context to ensure proper cleanup of resources, including stacks and writer references.
- Added new stack status constants and validation to improve traceability and error handling in agent operations.
- Removed the obsolete JavaScript API file to streamline the codebase.
