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langchain/libs/community/langchain_community/chat_models/fake.py

105 lines
3.1 KiB
Python

"""Fake ChatModel for testing purposes."""
import asyncio
import time
from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Union
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain_core.language_models.chat_models import BaseChatModel, SimpleChatModel
from langchain_core.messages import AIMessageChunk, BaseMessage
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
class FakeMessagesListChatModel(BaseChatModel):
"""Fake ChatModel for testing purposes."""
responses: List[BaseMessage]
sleep: Optional[float] = None
i: int = 0
def _generate(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> ChatResult:
response = self.responses[self.i]
if self.i < len(self.responses) - 1:
self.i += 1
else:
self.i = 0
generation = ChatGeneration(message=response)
return ChatResult(generations=[generation])
@property
def _llm_type(self) -> str:
return "fake-messages-list-chat-model"
class FakeListChatModel(SimpleChatModel):
"""Fake ChatModel for testing purposes."""
responses: List
sleep: Optional[float] = None
i: int = 0
@property
def _llm_type(self) -> str:
return "fake-list-chat-model"
def _call(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
"""First try to lookup in queries, else return 'foo' or 'bar'."""
response = self.responses[self.i]
if self.i < len(self.responses) - 1:
self.i += 1
else:
self.i = 0
return response
def _stream(
self,
messages: List[BaseMessage],
stop: Union[List[str], None] = None,
run_manager: Union[CallbackManagerForLLMRun, None] = None,
**kwargs: Any,
) -> Iterator[ChatGenerationChunk]:
response = self.responses[self.i]
if self.i < len(self.responses) - 1:
self.i += 1
else:
self.i = 0
for c in response:
if self.sleep is not None:
time.sleep(self.sleep)
yield ChatGenerationChunk(message=AIMessageChunk(content=c))
async def _astream(
self,
messages: List[BaseMessage],
stop: Union[List[str], None] = None,
run_manager: Union[AsyncCallbackManagerForLLMRun, None] = None,
**kwargs: Any,
) -> AsyncIterator[ChatGenerationChunk]:
response = self.responses[self.i]
if self.i < len(self.responses) - 1:
self.i += 1
else:
self.i = 0
for c in response:
if self.sleep is not None:
await asyncio.sleep(self.sleep)
yield ChatGenerationChunk(message=AIMessageChunk(content=c))
@property
def _identifying_params(self) -> Dict[str, Any]:
return {"responses": self.responses}