forked from Archives/langchain
62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
import os
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import pytest
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import langchain
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from langchain.cache import GPTCache
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from langchain.schema import Generation, LLMResult
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from tests.unit_tests.llms.fake_llm import FakeLLM
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try:
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import gptcache # noqa: F401
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gptcache_installed = True
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except ImportError:
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gptcache_installed = False
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@pytest.mark.skipif(not gptcache_installed, reason="gptcache not installed")
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def test_gptcache_map_caching() -> None:
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"""Test gptcache caching behavior."""
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from gptcache import Cache
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from gptcache.manager.factory import get_data_manager
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from gptcache.processor.pre import get_prompt
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i = 0
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file_prefix = "data_map"
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def init_gptcache_map(cache_obj: Cache) -> None:
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nonlocal i
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cache_path = f"{file_prefix}_{i}.txt"
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if os.path.isfile(cache_path):
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os.remove(cache_path)
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cache_obj.init(
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pre_embedding_func=get_prompt,
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data_manager=get_data_manager(data_path=cache_path),
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)
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i += 1
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langchain.llm_cache = GPTCache(init_gptcache_map)
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llm = FakeLLM()
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params = llm.dict()
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params["stop"] = None
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llm_string = str(sorted([(k, v) for k, v in params.items()]))
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langchain.llm_cache.update("foo", llm_string, [Generation(text="fizz")])
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output = llm.generate(["foo", "bar", "foo"])
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expected_cache_output = [Generation(text="foo")]
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cache_output = langchain.llm_cache.lookup("bar", llm_string)
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assert cache_output == expected_cache_output
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langchain.llm_cache = None
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expected_generations = [
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[Generation(text="fizz")],
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[Generation(text="foo")],
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[Generation(text="fizz")],
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]
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expected_output = LLMResult(
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generations=expected_generations,
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llm_output=None,
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)
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assert output == expected_output
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