code: """Test Momento cache functionality.
  
  To run tests, set the environment variable MOMENTO_AUTH_TOKEN to a valid
  Momento auth token. This can be obtained by signing up for a free
  Momento account at https://gomomento.com/.
  """
  from __future__ import annotations
  
  import uuid
  from datetime import timedelta
  from typing import Iterator
  
  import pytest
  
  import langchain
  from langchain.cache import MomentoCache
  from langchain.schema import Generation, LLMResult
  from tests.unit_tests.llms.fake_llm import FakeLLM
  
  
  def random_string() -> str:
      return str(uuid.uuid4())
  
  
  @pytest.fixture(scope="module")
  def momento_cache() -> Iterator[MomentoCache]:
      from momento import CacheClient, Configurations, CredentialProvider
  
      cache_name = f"langchain-test-cache-{random_string()}"
      client = CacheClient(
          Configurations.Laptop.v1(),
          CredentialProvider.from_environment_variable("MOMENTO_AUTH_TOKEN"),
          default_ttl=timedelta(seconds=30),
      )
      try:
          llm_cache = MomentoCache(client, cache_name)
          langchain.llm_cache = llm_cache
          yield llm_cache
      finally:
          client.delete_cache(cache_name)
  
  
  def test_invalid_ttl() -> None:
      from momento import CacheClient, Configurations, CredentialProvider
  
      client = CacheClient(
          Configurations.Laptop.v1(),
          CredentialProvider.from_environment_variable("MOMENTO_AUTH_TOKEN"),
          default_ttl=timedelta(seconds=30),
      )
      with pytest.raises(ValueError):
          MomentoCache(client, cache_name=random_string(), ttl=timedelta(seconds=-1))
  
  
  def test_momento_cache_miss(momento_cache: MomentoCache) -> None:
      llm = FakeLLM()
      stub_llm_output = LLMResult(generations=[[Generation(text="foo")]])
      assert llm.generate([random_string()]) == stub_llm_output
  
  
  @pytest.mark.parametrize(
      "prompts,  generations",
      [
          # Single prompt, single generation
          ([random_string()], [[random_string()]]),
          # Single prompt, multiple generations
          ([random_string()], [[random_string(), random_string()]]),
          # Single prompt, multiple generations
          ([random_string()], [[random_string(), random_string(), random_string()]]),
          # Multiple prompts, multiple generations
          (
              [random_string(), random_string()],
              [[random_string()], [random_string(), random_string()]],
          ),
      ],
  )
  def test_momento_cache_hit(
      momento_cache: MomentoCache, prompts: list[str], generations: list[list[str]]
  ) -> None:
      llm = FakeLLM()
      params = llm.dict()
      params["stop"] = None
      llm_string = str(sorted([(k, v) for k, v in params.items()]))
  
      llm_generations = [
          [
              Generation(text=generation, generation_info=params)
              for generation in prompt_i_generations
          ]
          for prompt_i_generations in generations
      ]
      for prompt_i, llm_generations_i in zip(prompts, llm_generations):
          momento_cache.update(prompt_i, llm_string, llm_generations_i)
  
      assert llm.generate(prompts) == LLMResult(
          generations=llm_generations, llm_output={}
      )
  
apis: langchain.schema.Generation langchain.schema.LLMResult langchain.cache.MomentoCache
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