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106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
from abc import ABC, abstractmethod
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from typing import List, Optional
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from pydantic import BaseModel, Extra, Field, validator
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import langchain
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from langchain.callbacks import get_callback_manager
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from langchain.callbacks.base import BaseCallbackManager
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from langchain.schema import (
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AIMessage,
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BaseLanguageModel,
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BaseMessage,
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ChatGeneration,
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ChatResult,
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LLMResult,
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PromptValue,
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)
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def _get_verbosity() -> bool:
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return langchain.verbose
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class BaseChatModel(BaseLanguageModel, BaseModel, ABC):
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verbose: bool = Field(default_factory=_get_verbosity)
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"""Whether to print out response text."""
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callback_manager: BaseCallbackManager = Field(default_factory=get_callback_manager)
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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arbitrary_types_allowed = True
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@validator("callback_manager", pre=True, always=True)
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def set_callback_manager(
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cls, callback_manager: Optional[BaseCallbackManager]
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) -> BaseCallbackManager:
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"""If callback manager is None, set it.
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This allows users to pass in None as callback manager, which is a nice UX.
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"""
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return callback_manager or get_callback_manager()
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def generate(
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self, messages: List[List[BaseMessage]], stop: Optional[List[str]] = None
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) -> LLMResult:
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"""Top Level call"""
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results = []
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for m in messages:
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results.append(self._generate(m, stop=stop))
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return LLMResult(generations=[res.generations for res in results])
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async def agenerate(
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self, messages: List[List[BaseMessage]], stop: Optional[List[str]] = None
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) -> LLMResult:
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results = []
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for m in messages:
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results.append(self._generate(m, stop=stop))
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return LLMResult(generations=[res.generations for res in results])
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def generate_prompt(
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self, prompts: List[PromptValue], stop: Optional[List[str]] = None
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) -> LLMResult:
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prompt_messages = [p.to_messages() for p in prompts]
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return self.generate(prompt_messages, stop=stop)
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async def agenerate_prompt(
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self, prompts: List[PromptValue], stop: Optional[List[str]] = None
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) -> LLMResult:
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prompt_messages = [p.to_messages() for p in prompts]
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return await self.agenerate(prompt_messages, stop=stop)
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@abstractmethod
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def _generate(
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self, messages: List[BaseMessage], stop: Optional[List[str]] = None
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) -> ChatResult:
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"""Top Level call"""
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@abstractmethod
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async def _agenerate(
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self, messages: List[BaseMessage], stop: Optional[List[str]] = None
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) -> ChatResult:
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"""Top Level call"""
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def __call__(
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self, messages: List[BaseMessage], stop: Optional[List[str]] = None
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) -> BaseMessage:
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return self._generate(messages, stop=stop).generations[0].message
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class SimpleChatModel(BaseChatModel):
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def _generate(
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self, messages: List[BaseMessage], stop: Optional[List[str]] = None
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) -> ChatResult:
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output_str = self._call(messages, stop=stop)
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message = AIMessage(text=output_str)
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generation = ChatGeneration(message=message)
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return ChatResult(generations=[generation])
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@abstractmethod
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def _call(
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self, messages: List[BaseMessage], stop: Optional[List[str]] = None
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) -> str:
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"""Simpler interface."""
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