Source code for langchain_community.llms.fake

import asyncio
import time
from typing import Any, AsyncIterator, Iterator, List, Mapping, Optional

from langchain_core.callbacks import (
    AsyncCallbackManagerForLLMRun,
    CallbackManagerForLLMRun,
)
from langchain_core.language_models import LanguageModelInput
from langchain_core.language_models.llms import LLM
from langchain_core.runnables import RunnableConfig


[docs]class FakeListLLM(LLM): """Fake LLM for testing purposes.""" responses: List[str] sleep: Optional[float] = None i: int = 0 @property def _llm_type(self) -> str: """Return type of llm.""" return "fake-list" def _call( self, prompt: str, stop: Optional[List[str]] = None, run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> str: """Return next response""" response = self.responses[self.i] if self.i < len(self.responses) - 1: self.i += 1 else: self.i = 0 return response async def _acall( self, prompt: str, stop: Optional[List[str]] = None, run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any, ) -> str: """Return next response""" response = self.responses[self.i] if self.i < len(self.responses) - 1: self.i += 1 else: self.i = 0 return response @property def _identifying_params(self) -> Mapping[str, Any]: return {"responses": self.responses}
[docs]class FakeStreamingListLLM(FakeListLLM): """Fake streaming list LLM for testing purposes."""
[docs] def stream( self, input: LanguageModelInput, config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any, ) -> Iterator[str]: result = self.invoke(input, config) for c in result: if self.sleep is not None: time.sleep(self.sleep) yield c
[docs] async def astream( self, input: LanguageModelInput, config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any, ) -> AsyncIterator[str]: result = await self.ainvoke(input, config) for c in result: if self.sleep is not None: await asyncio.sleep(self.sleep) yield c