mirror of
https://github.com/hwchase17/langchain
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f92006de3c
0.2rc migrations - [x] Move memory - [x] Move remaining retrievers - [x] graph_qa chains - [x] some dependency from evaluation code potentially on math utils - [x] Move openapi chain from `langchain.chains.api.openapi` to `langchain_community.chains.openapi` - [x] Migrate `langchain.chains.ernie_functions` to `langchain_community.chains.ernie_functions` - [x] migrate `langchain/chains/llm_requests.py` to `langchain_community.chains.llm_requests` - [x] Moving `langchain_community.cross_enoders.base:BaseCrossEncoder` -> `langchain_community.retrievers.document_compressors.cross_encoder:BaseCrossEncoder` (namespace not ideal, but it needs to be moved to `langchain` to avoid circular deps) - [x] unit tests langchain -- add pytest.mark.community to some unit tests that will stay in langchain - [x] unit tests community -- move unit tests that depend on community to community - [x] mv integration tests that depend on community to community - [x] mypy checks Other todo - [x] Make deprecation warnings not noisy (need to use warn deprecated and check that things are implemented properly) - [x] Update deprecation messages with timeline for code removal (likely we actually won't be removing things until 0.4 release) -- will give people more time to transition their code. - [ ] Add information to deprecation warning to show users how to migrate their code base using langchain-cli - [ ] Remove any unnecessary requirements in langchain (e.g., is SQLALchemy required?) --------- Co-authored-by: Erick Friis <erick@langchain.dev>
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
import os
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from typing import Any, Callable, Union
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import pytest
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from langchain.globals import get_llm_cache, set_llm_cache
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from langchain_core.outputs import Generation
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from langchain_community.cache import GPTCache
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from tests.unit_tests.llms.fake_llm import FakeLLM
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try:
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from gptcache import Cache # noqa: F401
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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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gptcache_installed = True
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except ImportError:
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gptcache_installed = False
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def init_gptcache_map(cache_obj: Any) -> None:
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i = getattr(init_gptcache_map, "_i", 0)
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cache_path = f"data_map_{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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init_gptcache_map._i = i + 1 # type: ignore
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def init_gptcache_map_with_llm(cache_obj: Any, llm: str) -> None:
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cache_path = f"data_map_{llm}.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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@pytest.mark.skipif(not gptcache_installed, reason="gptcache not installed")
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@pytest.mark.parametrize(
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"init_func", [None, init_gptcache_map, init_gptcache_map_with_llm]
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)
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def test_gptcache_caching(
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init_func: Union[Callable[[Any, str], None], Callable[[Any], None], None],
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) -> None:
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"""Test gptcache default caching behavior."""
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set_llm_cache(GPTCache(init_func))
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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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get_llm_cache().update("foo", llm_string, [Generation(text="fizz")])
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_ = llm.generate(["foo", "bar", "foo"])
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cache_output = get_llm_cache().lookup("foo", llm_string)
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assert cache_output == [Generation(text="fizz")]
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get_llm_cache().clear()
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assert get_llm_cache().lookup("bar", llm_string) is None
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