AnthropicLlm usage_metadata is missing thinking token count

[sebastienc]

AnthropicLlm only maps basic input/output token counts into usage_metadata. When extended thinking is enabled, thinking block tokens are included in output_tokens but never broken out separately.

Current behaviour

message_to_generate_content_response and the streaming final response both produce:

usage_metadata=types.GenerateContentResponseUsageMetadata(
    prompt_token_count=message.usage.input_tokens,
    candidates_token_count=message.usage.output_tokens,
    total_token_count=(input_tokens + output_tokens),
)

Cache token counts (cache_creation_input_tokens, cache_read_input_tokens) are also missing but are tracked separately in #5395.

Expected behaviour

When extended thinking is enabled, populate usage_metadata.thoughts_token_count with the token count of thinking blocks. This is derivable from the thinking block content (supplemental API call to tokenizer) or from a future dedicated API field (ref: anthropic-python-sdk ).

Reference

This is particularly relevant now that extended thinking is supported via PR #5392.

[llalitkumarrr]

Hello @sebastienc ,

Thank you for bringing this to our attention. If you have a solution in mind for this issue, would you be willing to contribute a fix?

[sebastienc]

I see three options.

1. Do nothing since it's not pre-computed by the anthropic sdk right now. We could wait and see.
2. Use the thinking blocks to locally calculate the number of tokens with a formula we could decide on. Less precision but we could have a value.
3. Call the token count API with the content of the thinking blocks and use that result.

Which one would you prefer?

I'd be happy to implement.