fix(ai): DeepInfra completion tokens calculation for gemini models

[sylviezhang37]

Background

We noticed in ai-gateway logs that Deepinfra's gemini models' output tokens are negative.

Summary

Deepinfra's issue with how they convert gemini response to openai-compat, this is a raw output from them where completion tokens < reasoning tokens. For openai-compat, completion tokens should include reasoning tokens.

  "prompt_tokens": 19,
  "completion_tokens": 84,
  "total_tokens": 1184,
  "prompt_tokens_details": null,
  "completion_tokens_details": {
    "reasoning_tokens": 1081
  }

They use vllm, and the issue should be here where they don't treat complete_token_details.

Added a conditional logic to override their calculation issues for the models we are seeing issues for but keeping the other models unchanged.

Manual Verification

• Verified with streaming and non-streaming tests on both gemini models with Deepinfra
• Verified with additional unit tests

Checklist

• Tests have been added / updated (for bug fixes / features)
• Documentation has been added / updated (for bug fixes / features)
• A patch changeset for relevant packages has been added (for bug fixes / features - run pnpm changeset in the project root)
• I have reviewed this pull request (self-review)

Future Work

A PR is open on vllm related to reasoning tokens calculation, but it is making progress very slowly, I subscribed to it. If reasoning tokens are incorporated by vllm, I can revert the code changes here.

[sylviezhang37]

Closing this and passing this issue to ai sdk team