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refactor: reuse _build_part_for_input in embed_content transform

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Chesars 2026-03-21 23:23:41 -03:00
parent 806dd31158
commit 9c4c34177e
1 changed files with 1 additions and 23 deletions
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24
litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py
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@ -238,29 +238,7 @@ def transform_openai_input_gemini_embed_content(
for element in input_list:
if not isinstance(element, str):
raise ValueError(f"Unsupported input type: {type(element)}")
if element.startswith("data:") and ";base64," in element:
mime_type, base64_data = _parse_data_url(element)
blob: BlobType = {"mime_type": mime_type, "data": base64_data}
parts.append(PartType(inline_data=blob))
elif _is_gcs_url(element):
mime_type = _infer_mime_type_from_gcs_url(element)
file_data: FileDataType = {
"mime_type": mime_type,
"file_uri": element,
}
parts.append(PartType(file_data=file_data))
elif _is_file_reference(element):
if element not in resolved_files:
raise ValueError(f"File reference {element} not resolved")
file_info = resolved_files[element]
file_data_ref: FileDataType = {
"mime_type": file_info["mime_type"],
"file_uri": file_info["uri"],
}
parts.append(PartType(file_data=file_data_ref))
else:
parts.append(PartType(text=element))
parts.append(_build_part_for_input(element, resolved_files=resolved_files))
request_body: dict = {
"content": ContentType(parts=parts),