mirror of
https://github.com/hwchase17/langchain
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105 lines
3.1 KiB
Python
105 lines
3.1 KiB
Python
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"""Fake ChatModel for testing purposes."""
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import asyncio
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import time
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from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Union
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from langchain_core.callbacks import (
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AsyncCallbackManagerForLLMRun,
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CallbackManagerForLLMRun,
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)
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from langchain_core.language_models.chat_models import BaseChatModel, SimpleChatModel
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from langchain_core.messages import AIMessageChunk, BaseMessage
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from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
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class FakeMessagesListChatModel(BaseChatModel):
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"""Fake ChatModel for testing purposes."""
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responses: List[BaseMessage]
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sleep: Optional[float] = None
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i: int = 0
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def _generate(
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self,
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messages: List[BaseMessage],
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stop: Optional[List[str]] = None,
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run_manager: Optional[CallbackManagerForLLMRun] = None,
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**kwargs: Any,
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) -> ChatResult:
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response = self.responses[self.i]
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if self.i < len(self.responses) - 1:
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self.i += 1
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else:
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self.i = 0
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generation = ChatGeneration(message=response)
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return ChatResult(generations=[generation])
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@property
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def _llm_type(self) -> str:
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return "fake-messages-list-chat-model"
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class FakeListChatModel(SimpleChatModel):
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"""Fake ChatModel for testing purposes."""
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responses: List
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sleep: Optional[float] = None
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i: int = 0
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@property
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def _llm_type(self) -> str:
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return "fake-list-chat-model"
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def _call(
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self,
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messages: List[BaseMessage],
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stop: Optional[List[str]] = None,
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run_manager: Optional[CallbackManagerForLLMRun] = None,
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**kwargs: Any,
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) -> str:
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"""First try to lookup in queries, else return 'foo' or 'bar'."""
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response = self.responses[self.i]
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if self.i < len(self.responses) - 1:
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self.i += 1
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else:
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self.i = 0
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return response
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def _stream(
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self,
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messages: List[BaseMessage],
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stop: Union[List[str], None] = None,
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run_manager: Union[CallbackManagerForLLMRun, None] = None,
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**kwargs: Any,
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) -> Iterator[ChatGenerationChunk]:
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response = self.responses[self.i]
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if self.i < len(self.responses) - 1:
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self.i += 1
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else:
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self.i = 0
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for c in response:
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if self.sleep is not None:
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time.sleep(self.sleep)
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yield ChatGenerationChunk(message=AIMessageChunk(content=c))
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async def _astream(
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self,
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messages: List[BaseMessage],
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stop: Union[List[str], None] = None,
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run_manager: Union[AsyncCallbackManagerForLLMRun, None] = None,
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**kwargs: Any,
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) -> AsyncIterator[ChatGenerationChunk]:
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response = self.responses[self.i]
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if self.i < len(self.responses) - 1:
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self.i += 1
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else:
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self.i = 0
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for c in response:
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if self.sleep is not None:
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await asyncio.sleep(self.sleep)
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yield ChatGenerationChunk(message=AIMessageChunk(content=c))
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@property
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def _identifying_params(self) -> Dict[str, Any]:
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return {"responses": self.responses}
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