forked from Archives/langchain
You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
import os
|
|
|
|
import pytest
|
|
|
|
import langchain
|
|
from langchain.cache import GPTCache
|
|
from langchain.schema import Generation, LLMResult
|
|
from tests.unit_tests.llms.fake_llm import FakeLLM
|
|
|
|
try:
|
|
import gptcache # noqa: F401
|
|
|
|
gptcache_installed = True
|
|
except ImportError:
|
|
gptcache_installed = False
|
|
|
|
|
|
@pytest.mark.skipif(not gptcache_installed, reason="gptcache not installed")
|
|
def test_gptcache_map_caching() -> None:
|
|
"""Test gptcache caching behavior."""
|
|
|
|
from gptcache import Cache
|
|
from gptcache.manager.factory import get_data_manager
|
|
from gptcache.processor.pre import get_prompt
|
|
|
|
i = 0
|
|
file_prefix = "data_map"
|
|
|
|
def init_gptcache_map(cache_obj: Cache) -> None:
|
|
nonlocal i
|
|
cache_path = f"{file_prefix}_{i}.txt"
|
|
if os.path.isfile(cache_path):
|
|
os.remove(cache_path)
|
|
cache_obj.init(
|
|
pre_embedding_func=get_prompt,
|
|
data_manager=get_data_manager(data_path=cache_path),
|
|
)
|
|
i += 1
|
|
|
|
langchain.llm_cache = GPTCache(init_gptcache_map)
|
|
|
|
llm = FakeLLM()
|
|
params = llm.dict()
|
|
params["stop"] = None
|
|
llm_string = str(sorted([(k, v) for k, v in params.items()]))
|
|
langchain.llm_cache.update("foo", llm_string, [Generation(text="fizz")])
|
|
output = llm.generate(["foo", "bar", "foo"])
|
|
expected_cache_output = [Generation(text="foo")]
|
|
cache_output = langchain.llm_cache.lookup("bar", llm_string)
|
|
assert cache_output == expected_cache_output
|
|
langchain.llm_cache = None
|
|
expected_generations = [
|
|
[Generation(text="fizz")],
|
|
[Generation(text="foo")],
|
|
[Generation(text="fizz")],
|
|
]
|
|
expected_output = LLMResult(
|
|
generations=expected_generations,
|
|
llm_output=None,
|
|
)
|
|
assert output == expected_output
|