code: def completions_response():
      return {
          "completion": "Here is a basic overview of how a car works:\n\n1. The engine. "
          "The engine is the power source that makes the car move.",
          "stop_reason": "max_tokens",
          "model": "claude-instant-1.1",
          "truncated": False,
          "stop": None,
          "log_id": "dee173f87ddf1357da639dee3c38d833",
          "exception": None,
          "headers": {"Content-Type": "application/json"},
      }
  
file_path: mlflow/tests/gateway/providers/test_anthropic.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_AI_GATEWAY_ANTHROPIC_MAXIMUM_MAX_TOKENS, MLFLOW_GATEWAY_ROUTE_TIMEOUT_SECONDS
  from mlflow.gateway.providers.anthropic import AnthropicProvider
  from mlflow.gateway.schemas import chat, completions, embeddings
  from tests.gateway.tools import MockAsyncResponse
label_desc: Use image node_id 1 for calling a global function with example usage: completions_response() and returns: dict