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.
97 lines
3.3 KiB
Python
97 lines
3.3 KiB
Python
"""Beta Feature: base interface for cache."""
|
|
from abc import ABC, abstractmethod
|
|
from typing import Dict, List, Optional, Tuple
|
|
|
|
from sqlalchemy import Column, Integer, String, create_engine, select
|
|
from sqlalchemy.engine.base import Engine
|
|
from sqlalchemy.ext.declarative import declarative_base
|
|
from sqlalchemy.orm import Session
|
|
|
|
from langchain.schema import Generation
|
|
|
|
RETURN_VAL_TYPE = List[Generation]
|
|
|
|
|
|
class BaseCache(ABC):
|
|
"""Base interface for cache."""
|
|
|
|
@abstractmethod
|
|
def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
|
|
"""Look up based on prompt and llm_string."""
|
|
|
|
@abstractmethod
|
|
def update(self, prompt: str, llm_string: str, return_val: RETURN_VAL_TYPE) -> None:
|
|
"""Update cache based on prompt and llm_string."""
|
|
|
|
|
|
class InMemoryCache(BaseCache):
|
|
"""Cache that stores things in memory."""
|
|
|
|
def __init__(self) -> None:
|
|
"""Initialize with empty cache."""
|
|
self._cache: Dict[Tuple[str, str], RETURN_VAL_TYPE] = {}
|
|
|
|
def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
|
|
"""Look up based on prompt and llm_string."""
|
|
return self._cache.get((prompt, llm_string), None)
|
|
|
|
def update(self, prompt: str, llm_string: str, return_val: RETURN_VAL_TYPE) -> None:
|
|
"""Update cache based on prompt and llm_string."""
|
|
self._cache[(prompt, llm_string)] = return_val
|
|
|
|
|
|
Base = declarative_base()
|
|
|
|
|
|
class FullLLMCache(Base): # type: ignore
|
|
"""SQLite table for full LLM Cache (all generations)."""
|
|
|
|
__tablename__ = "full_llm_cache"
|
|
prompt = Column(String, primary_key=True)
|
|
llm = Column(String, primary_key=True)
|
|
idx = Column(Integer, primary_key=True)
|
|
response = Column(String)
|
|
|
|
|
|
class SQLAlchemyCache(BaseCache):
|
|
"""Cache that uses SQAlchemy as a backend."""
|
|
|
|
def __init__(self, engine: Engine):
|
|
"""Initialize by creating all tables."""
|
|
self.engine = engine
|
|
Base.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."""
|
|
stmt = (
|
|
select(FullLLMCache.response)
|
|
.where(FullLLMCache.prompt == prompt)
|
|
.where(FullLLMCache.llm == llm_string)
|
|
.order_by(FullLLMCache.idx)
|
|
)
|
|
with Session(self.engine) as session:
|
|
generations = []
|
|
for row in session.execute(stmt):
|
|
generations.append(Generation(text=row[0]))
|
|
if len(generations) > 0:
|
|
return generations
|
|
return None
|
|
|
|
def update(self, prompt: str, llm_string: str, return_val: RETURN_VAL_TYPE) -> None:
|
|
"""Look up based on prompt and llm_string."""
|
|
for i, generation in enumerate(return_val):
|
|
item = FullLLMCache(
|
|
prompt=prompt, llm=llm_string, response=generation.text, idx=i
|
|
)
|
|
with Session(self.engine) as session, session.begin():
|
|
session.add(item)
|
|
|
|
|
|
class SQLiteCache(SQLAlchemyCache):
|
|
"""Cache that uses SQLite as a backend."""
|
|
|
|
def __init__(self, database_path: str = ".langchain.db"):
|
|
"""Initialize by creating the engine and all tables."""
|
|
engine = create_engine(f"sqlite:///{database_path}")
|
|
super().__init__(engine)
|