What changed

Added a catalog-based validation path for MiniMax models in _resolve_model_selection(), mirroring the existing openai-codex pattern. MiniMax does not expose a /models API endpoint, so the previous code would fall through to a generic "Could not reach API" rejection even for valid model names.

Before: Any MiniMax model would be rejected with "Could not reach API" because the API probe to /v1/models always fails for MiniMax.

After: MiniMax models are validated against a static catalog (case-insensitive matching), with:

• Exact match detection for known models
• Auto-correct for close matches (edit distance via difflib.get_close_matches)
• Suggestion display for near-matches
• Graceful acceptance with warning for unrecognized models (since the catalog may be incomplete)

Note: Unlike openai-codex which rejects unknown models (accepted: False), MiniMax accepts unknown models with a warning (accepted: True) because the catalog may not cover all available models and the user's model may still work server-side.

How to test

1. Configure MiniMax as a provider with a valid API key
2. Set model to MiniMax-M2.7 — should be accepted without warning
3. Set model to minimax-m2.7 — should be accepted (case-insensitive)
4. Set model to MiniMax-Text-01 — should auto-correct with suggestion
5. Set model to MiniMax-Unknown — should be accepted with warning
6. Run the test suite:

   pytest tests/test_minimax_model_validation.py -v

Platforms tested

• Linux (Docker container, Python 3.11)

Closes #12611
Closes #12460
Closes #12399
Closes #12547