- Added support for processing image content in the agent, providing placeholder text when image parsing fails.
- Implemented a fallback mechanism to utilize vision tools for image analysis, improving the handling of image content.
- Updated tests to validate the new image handling behavior, ensuring correct responses when vision support is unavailable.
- Enhanced system prompts to guide users on using the new `image_read` tool for image analysis, improving user experience.
- Integrated logging for connector resolution failures, providing clearer diagnostics during fallback scenarios.
- Simplified connector ID extraction in various components, ensuring accurate handling of model identifiers.
- Updated model configuration to support new parameters and capabilities, improving overall provider management.
- Enhanced OpenAPI settings to reflect changes in model options and connector behavior, ensuring better alignment with upstream API requirements.
- Updated the system configuration to include new role-level defaults for Light, Vision, and Audio connectors.
- Refactored the resolveSystemConnector function to prioritize per-agent overrides, improving connector resolution logic.
- Enhanced LLMConnector integration across various components to streamline settings retrieval and capabilities management.
- Improved error handling and logging for connector-related operations, ensuring better diagnostics and user feedback.
- 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.
- Clean up the code for sending the initial ChunkToolCall, improving readability and maintaining alignment with OpenAI's format for tool name resolution.
- Ensure that the chunk count is incremented after sending the tool call data, enhancing the message handling process in the streamWithRetry function.
- Implement functionality to send an initial ChunkToolCall with the event's ID and function name, aligning with OpenAI's format for tool name resolution.
- Enhance message tracking by incrementing the chunk count after sending the tool call data, improving the overall message handling process in the streamWithRetry function.
- Include `ANTHROPIC_API_KEY` in both `pr-test.yml` and `unit-test.yml` workflows to support Anthropic API integration.
- Refactor tool call processing in `anthropic.go` to ensure deterministic order by sorting tool call indices before processing, enhancing reliability in tool call execution.
- Add handling for Anthropic connector types in the sandbox, allowing direct connections without a proxy.
- Enhance capability retrieval to support both OpenAI and Anthropic formats, ensuring a unified interface.
- Update the executor and command logic to differentiate between OpenAI and Anthropic configurations, streamlining environment setup.
- Modify the provider selection logic to accommodate Anthropic capabilities, improving flexibility in LLM provider management.
- Refactor API detection to include Anthropic, ensuring accurate identification of connector types.
