fix(usage): Normalize None token detail objects on Usage initialization #2141
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It seems the tests are failing |
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Extends openai#2034 to handle providers that return None for entire input_tokens_details and output_tokens_details objects (not just the fields within them). This affects non-streaming responses. Related to openai#1179 (which fixed the streaming case). Some providers like llama-stack return null for these optional fields in their JSON responses. The OpenAI SDK maps these to None in Python. Previously, passing None to the Usage constructor would fail Pydantic validation before __post_init__ could normalize them. This PR uses Pydantic's BeforeValidator to normalize None values at the field level, before Pydantic's type validation runs. The validators also convert Chat Completions API types (PromptTokensDetails, CompletionTokensDetails) to Responses API types (InputTokensDetails, OutputTokensDetails).
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sorry about that @seratch |
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Extends #2034 to handle providers that return None for entire input_tokens_details and output_tokens_details objects (not just the fields within them). This affects non-streaming responses.
Related to #1179 (which fixed the streaming case).
Some providers like llama-stack return null for these optional fields in their JSON responses. The OpenAI SDK maps these to None in Python. Previously, passing None to the Usage constructor would fail Pydantic validation before
__post_init__could normalize them.This PR uses Pydantic's BeforeValidator to normalize None values at the field level, before Pydantic's type validation runs.