Source code for camel.models.stub_model

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# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
import time
from typing import Any, Dict, List, Optional, Union

from openai import Stream

from camel.messages import OpenAIMessage
from camel.models import BaseModelBackend
from camel.types import (
    ChatCompletion,
    ChatCompletionChunk,
    ChatCompletionMessage,
    Choice,
    CompletionUsage,
    ModelType,
)
from camel.utils import BaseTokenCounter


[docs] class StubTokenCounter(BaseTokenCounter):
[docs] def count_tokens_from_messages(self, messages: List[OpenAIMessage]) -> int: r"""Token counting for STUB models, directly returning a constant. Args: messages (List[OpenAIMessage]): Message list with the chat history in OpenAI API format. Returns: int: A constant to act as the number of the tokens in the messages. """ return 10
[docs] class StubModel(BaseModelBackend): r"""A dummy model used for unit tests.""" model_type = ModelType.STUB def __init__( self, model_type: ModelType, model_config_dict: Dict[str, Any], api_key: Optional[str] = None, url: Optional[str] = None, token_counter: Optional[BaseTokenCounter] = None, ) -> None: r"""All arguments are unused for the dummy model.""" super().__init__( model_type, model_config_dict, api_key, url, token_counter ) @property def token_counter(self) -> BaseTokenCounter: r"""Initialize the token counter for the model backend. Returns: BaseTokenCounter: The token counter following the model's tokenization style. """ if not self._token_counter: self._token_counter = StubTokenCounter() return self._token_counter
[docs] def run( self, messages: List[OpenAIMessage] ) -> Union[ChatCompletion, Stream[ChatCompletionChunk]]: r"""Run fake inference by returning a fixed string. All arguments are unused for the dummy model. Returns: Dict[str, Any]: Response in the OpenAI API format. """ ARBITRARY_STRING = "Lorem Ipsum" response: ChatCompletion = ChatCompletion( id="stub_model_id", model="stub", object="chat.completion", created=int(time.time()), choices=[ Choice( finish_reason="stop", index=0, message=ChatCompletionMessage( content=ARBITRARY_STRING, role="assistant", ), logprobs=None, ) ], usage=CompletionUsage( completion_tokens=10, prompt_tokens=10, total_tokens=20, ), ) return response
[docs] def check_model_config(self): r"""Directly pass the check on arguments to STUB model.""" pass