This update introduces a centralized error handling mechanism for various AI engines, improving the consistency and clarity of error messages. The new `normalizeEngineError` function standardizes error responses, allowing for better user feedback and recovery suggestions. Additionally, specific error classes for insufficient credits, rate limits, and service availability have been implemented, along with user-friendly formatting for error messages. This refactor aims to enhance the overall user experience when interacting with the AI services.
Add comprehensive setup command with provider selection, API key
configuration, and model selection. Include error recovery for
model-not-found scenarios with suggested alternatives and automatic
retry functionality. Update Anthropic model list with latest versions
and add provider metadata for better user experience.
Introduces AIMLAPI as a supported AI provider, including model list, config validation, and engine implementation. Updates README and engine selection logic to integrate AIMLAPI for chat completions.
Refactor AimlApiEngine response handling
Removed dependency on removeContentTags and simplified message content extraction. Minor header formatting fix for HTTP-Referer. This streamlines the response handling and reduces unnecessary processing.
The changes:
1. Expanded the skip condition to include additional AI providers (DEEPSEEK, GROQ, MISTRAL, MLX, OPENROUTER) beyond just TEST
2. Maintained existing TEST provider skip behavior
3. Added explicit comment explaining the skip logic
The why:
Prevents migration execution for unsupported AI providers to avoid potential runtime errors or data inconsistencies, ensuring migrations only run for properly handled configurations.
- Add prettier job to GitHub Actions workflow to enforce code formatting
- Add format:check script to package.json for checking formatting
- Include failure message when prettier check fails in CI
Add OpenRouterEngine class and integrate it into the configuration
system. OpenRouter provides access to 300+ AI models through a
unified API, expanding model availability for commit message
generation beyond existing providers.
When user wants one line commits the system prompt and the user/assistant one-shot example were contradicting each other, confusing the LLM. This fix modifies the assistant output so that prompt and one-shot are consistent.
