We’ve introduced finish_reason normalization to simplify the interpretation of responses:
Normalized Finish Reasons: Models now return standardized finish_reason values, aligned with OpenAI-style conventions.
Native Finish Reason: To retain model-specific details, the native_finish_reason is also returned.
Debugging and Understanding: Gain insight into a model’s decision-making process.
Cross-Model Consistency: Streamline development with unified finish reasons across reasoning-capable models.
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