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* fix(vertex): preserve Gemini Embedding 2 usageMetadata for cost tracking * style(vertex): apply ruff format to batch_embed_content_transformation * fix(vertex): bill files/ image refs in Gemini embedContent at per-image rate Resolved files/... references whose mime type is an image were not detected by _is_image_element, so image_count stayed 0 and generic_cost_per_token fell back to the text token rate instead of input_cost_per_image. Thread the resolved_files mapping into the usage builder so resolved image references are counted and billed per image. Also modernize the _flatten_input return annotation to satisfy the ruff UP006 strict gate. * fix(vertex): bill Gemini embedding audio per-second and stop video+audio double-billing Audio-only embedContent responses set audio_tokens, but generic_cost_per_token only charges audio via input_cost_per_audio_token. gemini-embedding-2 prices audio via input_cost_per_audio_per_second, so spend stayed at $0. Plumb a new audio_length_seconds field through PromptTokensDetailsWrapper, parse it in _parse_prompt_tokens_details, and bill it from _calculate_input_cost. The vertex embedding transformation derives audio_length_seconds from audio_tokens using the documented 32 tokens/sec Gemini rate. The 1-token text floor that protects video billing only fired when no other modality was billable, but audio presence flipped that flag, leaving text_tokens at zero for video+audio responses. generic_cost_per_token then rewrote text_tokens to prompt_tokens minus audio_tokens (the video token count), charging video tokens as text on top of the per-second video cost. The rewrite trigger is text_tokens == 0 and image_count == 0; align the floor with that trigger and ignore audio_tokens. --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> |
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| .. | ||
| __init__.py | ||
| test_batch_embed_content_transformation.py | ||