google/generativeai/embedding.py [199:212]:
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                embedding_request,
                **request_options,
            )
            embedding_dict = type(embedding_response).to_dict(embedding_response)
            result["embedding"].extend(e["values"] for e in embedding_dict["embeddings"])
        return result
    else:
        embedding_request = protos.EmbedContentRequest(
            model=model,
            content=content_types.to_content(content),
            task_type=task_type,
            title=title,
            output_dimensionality=output_dimensionality,
        )
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google/generativeai/embedding.py [292:305]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
                embedding_request,
                **request_options,
            )
            embedding_dict = type(embedding_response).to_dict(embedding_response)
            result["embedding"].extend(e["values"] for e in embedding_dict["embeddings"])
        return result
    else:
        embedding_request = protos.EmbedContentRequest(
            model=model,
            content=content_types.to_content(content),
            task_type=task_type,
            title=title,
            output_dimensionality=output_dimensionality,
        )
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