code: def embeddings_batch_response():
      return {
          "id": "bc57846a-3e56-4327-8acc-588ca1a37b8a",
          "texts": ["hello world"],
          "embeddings": [
              [
                  3.25,
                  0.7685547,
                  2.65625,
                  -0.30126953,
                  -2.3554688,
                  1.2597656,
              ],
              [
                  7.25,
                  0.7685547,
                  4.65625,
                  -0.30126953,
                  -2.3554688,
                  8.2597656,
              ],
          ],
          "meta": [
              {
                  "api_version": [
                      {
                          "version": "1",
                      }
                  ]
              },
          ],
          "headers": {"Content-Type": "application/json"},
      }
  
file_path: mlflow/tests/gateway/providers/test_cohere.py
imports: from unittest import mock
  import pytest
  from aiohttp import ClientTimeout
  from fastapi import HTTPException
  from fastapi.encoders import jsonable_encoder
  from pydantic import ValidationError
  from mlflow.gateway.config import RouteConfig
  from mlflow.gateway.constants import MLFLOW_GATEWAY_ROUTE_TIMEOUT_SECONDS
  from mlflow.gateway.providers.cohere import CohereProvider
  from mlflow.gateway.schemas import completions, embeddings
  from tests.gateway.tools import MockAsyncResponse
label_desc: Use image node_id 5 for calling a global function with example usage: embeddings_batch_response() and returns: dict