- Added new reasoning levels: `none`, `minimal`, and `unsupported` to Codex model configurations.
- Introduced metadata sanitization and normalization for reasoning levels in API response.
- Extended unit tests to cover reasoning levels validation and metadata sanitation logic.
- Introduced OpenAI-compatible image model support in the API, enabling integration through image generation and editing endpoints.
- Added registry type for OpenAIImageModelType to classify and validate compatibility.
- Implemented request handling for OpenAI-compatible image models, including JSON and multipart formats.
- Enhanced executor methods to support OpenAI-compatible image streaming and non-streaming requests.
- Included tests to validate model registration, streaming behavior, and multipart payload formatting.
- Relocated Codex client model JSON and related logic from `openai` package to `registry` for better modularity.
- Updated references to use `registry.GetCodexClientModelsJSON()` in loading logic.
- Extended test cases to cover additional field removals (`upgrade`, `availability_nux`).
- Introduced Codex client models framework in `openai` package.
- Added JSON-based model definitions (`codex_client_models.json`) for Codex, including metadata, reasoning levels, and configuration options.
- Implemented handlers to load, clone, and build Codex client models with support for visibility overrides and metadata application.
- Enabled sorting and prioritization of models based on configuration or runtime criteria.
- Added utility functions for managing and validating model attributes.
Luis Pater