Support explicit proxy disabling and ambient proxy fallback without leaking env state into config.
Improve first-run detection, endpoint-specific error messaging, diff exclusions, and runtime helper boundaries covered by unit tests.
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.
