code: """Test caching for LLMs and ChatModels."""
  from typing import Dict, Generator, List, Union
  
  import pytest
  from _pytest.fixtures import FixtureRequest
  from sqlalchemy import create_engine
  from sqlalchemy.orm import Session
  
  import langchain
  from langchain.cache import (
      InMemoryCache,
      SQLAlchemyCache,
  )
  from langchain.chat_models import FakeListChatModel
  from langchain.chat_models.base import BaseChatModel, dumps
  from langchain.llms import FakeListLLM
  from langchain.llms.base import BaseLLM
  from langchain.schema import (
      AIMessage,
      BaseMessage,
      ChatGeneration,
      Generation,
      HumanMessage,
  )
  
  
  def get_sqlite_cache() -> SQLAlchemyCache:
      return SQLAlchemyCache(engine=create_engine("sqlite://"))
  
  
  CACHE_OPTIONS = [
      InMemoryCache,
      get_sqlite_cache,
  ]
  
  
  @pytest.fixture(autouse=True, params=CACHE_OPTIONS)
  def set_cache_and_teardown(request: FixtureRequest) -> Generator[None, None, None]:
      # Will be run before each test
      cache_instance = request.param
      langchain.llm_cache = cache_instance()
      if langchain.llm_cache:
          langchain.llm_cache.clear()
      else:
          raise ValueError("Cache not set. This should never happen.")
  
      yield
  
      # Will be run after each test
      if langchain.llm_cache:
          langchain.llm_cache.clear()
      else:
          raise ValueError("Cache not set. This should never happen.")
  
  
  def test_llm_caching() -> None:
      prompt = "How are you?"
      response = "Test response"
      cached_response = "Cached test response"
      llm = FakeListLLM(responses=[response])
      if langchain.llm_cache:
          langchain.llm_cache.update(
              prompt=prompt,
              llm_string=create_llm_string(llm),
              return_val=[Generation(text=cached_response)],
          )
          assert llm(prompt) == cached_response
      else:
          raise ValueError(
              "The cache not set. This should never happen, as the pytest fixture "
              "`set_cache_and_teardown` always sets the cache."
          )
  
  
  def test_old_sqlite_llm_caching() -> None:
      if isinstance(langchain.llm_cache, SQLAlchemyCache):
          prompt = "How are you?"
          response = "Test response"
          cached_response = "Cached test response"
          llm = FakeListLLM(responses=[response])
          items = [
              langchain.llm_cache.cache_schema(
                  prompt=prompt,
                  llm=create_llm_string(llm),
                  response=cached_response,
                  idx=0,
              )
          ]
          with Session(langchain.llm_cache.engine) as session, session.begin():
              for item in items:
                  session.merge(item)
          assert llm(prompt) == cached_response
  
  
  def test_chat_model_caching() -> None:
      prompt: List[BaseMessage] = [HumanMessage(content="How are you?")]
      response = "Test response"
      cached_response = "Cached test response"
      cached_message = AIMessage(content=cached_response)
      llm = FakeListChatModel(responses=[response])
      if langchain.llm_cache:
          langchain.llm_cache.update(
              prompt=dumps(prompt),
              llm_string=llm._get_llm_string(),
              return_val=[ChatGeneration(message=cached_message)],
          )
          result = llm(prompt)
          assert isinstance(result, AIMessage)
          assert result.content == cached_response
      else:
          raise ValueError(
              "The cache not set. This should never happen, as the pytest fixture "
              "`set_cache_and_teardown` always sets the cache."
          )
  
  
  def test_chat_model_caching_params() -> None:
      prompt: List[BaseMessage] = [HumanMessage(content="How are you?")]
      response = "Test response"
      cached_response = "Cached test response"
      cached_message = AIMessage(content=cached_response)
      llm = FakeListChatModel(responses=[response])
      if langchain.llm_cache:
          langchain.llm_cache.update(
              prompt=dumps(prompt),
              llm_string=llm._get_llm_string(functions=[]),
              return_val=[ChatGeneration(message=cached_message)],
          )
          result = llm(prompt, functions=[])
          assert isinstance(result, AIMessage)
          assert result.content == cached_response
          result_no_params = llm(prompt)
          assert isinstance(result_no_params, AIMessage)
          assert result_no_params.content == response
  
      else:
          raise ValueError(
              "The cache not set. This should never happen, as the pytest fixture "
              "`set_cache_and_teardown` always sets the cache."
          )
  
  
  def create_llm_string(llm: Union[BaseLLM, BaseChatModel]) -> str:
      _dict: Dict = llm.dict()
      _dict["stop"] = None
      return str(sorted([(k, v) for k, v in _dict.items()]))
  
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