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* feat(vertex_ai): label Vertex requests with the caller's key, team, org, and project Adds the opt-in litellm.vertex_request_label_fields setting, the Vertex twin of bedrock_request_metadata_fields. When set, Gemini, embeddings, Imagen and Gemini image generation, rerank, and Claude on Vertex (chat and /v1/messages) send the listed proxy identity fields and spend_logs_metadata as request labels, identity first, with the user_api_key_ prefix reserved so a caller cannot forge or evict them. Identity text is rewritten to fit Google's label rules. Gemini image generation now forwards labels at all. * feat(vertex_ai): send the opt-in identity labels on multimodal embeddings, the Google GenAI route, and batches With litellm_settings.vertex_request_label_fields on, the multimodal embedding predict body, the native generateContent and streamGenerateContent body, and the BatchPredictionJob now carry the key's identity labels the same way chat does Caller labels on GenAI are resolved after the extra_body merge, so neither a top-level labels field nor extra_body.labels can write the reserved prefix. Batch labels come only from the proxy's litellm_metadata, never the caller's OpenAI batch metadata. With the setting off every route sends the same body as before * fix(vertex_ai): keep identity labels when a Gemini caller sends extra_body labels * fix(vertex_ai): label Interactions, image edits, Mistral, and the /vertex_ai pass-through, and gate Gemini image labels on the setting * fix(vertex_ai): move body labels into the labels header on Vertex rawPredict pass-through calls * fix(vertex_ai): send Mistral extra_body labels in the labels header instead of the body Labels a caller nests in extra_body now merge over top-level labels before the X-Vertex-AI-Labels header is built, the way the Gemini body merges them, and leave the outbound body. The token-fetch stubs in the Mistral and multimodal embedding tests are scoped to their instance so later tests see the real method * fix(vertex_ai): limit pass-through labels to POST and to publishers that take the labels header rawPredict to custom endpoints and publishers other than Anthropic and Mistral, and PATCH or PUT bodies, now reach Vertex as the caller sent them. The pass-through drops a caller's labels header where it writes body labels, a single field written as text turns the setting on for that field, and an undecodable Claude labels header falls back to the caller's labels * fix(vertex): label Veo video, Gemini transcription, and pass-through predictLongRunning requests * fix(vertex): read the pass-through publisher from the end of the upstream path A project id named publishers shifted the first-match lookup, so a forged X-Vertex-AI-Labels header reached Claude or Mistral untouched * fix(vertex): drop a caller labels header on body-labelled Vertex routes while identity labels are on * test(vertex): script the v1beta1 GenAI target in the labels header integration test * test(vertex): type the transcription test's access token override --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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| .. | ||
| __init__.py | ||
| test_batch_line_items.py | ||
| test_batch_utils.py | ||
| test_main.py | ||
| test_responses_batch_cost.py | ||