fix caching (#658)

harrison/document-split
Harrison Chase 1 year ago committed by GitHub
parent d0fdc6da11
commit 54d7f1c933
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GPG Key ID: 4AEE18F83AFDEB23

@ -60,7 +60,7 @@ class SQLAlchemyCache(BaseCache):
"""Initialize by creating all tables."""
self.engine = engine
self.cache_schema = cache_schema
Base.metadata.create_all(self.engine)
self.cache_schema.metadata.create_all(self.engine)
def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
"""Look up based on prompt and llm_string."""

@ -1,6 +1,9 @@
"""Test base LLM functionality."""
from sqlalchemy import Column, Integer, Sequence, String, create_engine
from sqlalchemy.ext.declarative import declarative_base
import langchain
from langchain.cache import InMemoryCache
from langchain.cache import InMemoryCache, SQLAlchemyCache
from langchain.schema import Generation, LLMResult
from tests.unit_tests.llms.fake_llm import FakeLLM
@ -28,3 +31,41 @@ def test_caching() -> None:
llm_output=None,
)
assert output == expected_output
def test_custom_caching() -> None:
"""Test custom_caching behavior."""
Base = declarative_base()
class FulltextLLMCache(Base): # type: ignore
"""Postgres table for fulltext-indexed LLM Cache."""
__tablename__ = "llm_cache_fulltext"
id = Column(Integer, Sequence("cache_id"), primary_key=True)
prompt = Column(String, nullable=False)
llm = Column(String, nullable=False)
idx = Column(Integer)
response = Column(String)
engine = create_engine("sqlite://")
langchain.llm_cache = SQLAlchemyCache(engine, FulltextLLMCache)
llm = FakeLLM()
params = llm._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(
expected_generations,
llm_output=None,
)
assert output == expected_output

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