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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. ========= | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# ========= Copyright 2023-2024 @ 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 | |
class StubTokenCounter(BaseTokenCounter): | |
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 | |
class StubModel(BaseModelBackend): | |
r"""A dummy model used for unit tests.""" | |
model_type = ModelType.STUB | |
def __init__( | |
self, | |
model_type: Union[ModelType, str], | |
model_config_dict: Optional[Dict[str, Any]] = None, | |
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 | |
) | |
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 | |
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 | |
def check_model_config(self): | |
r"""Directly pass the check on arguments to STUB model.""" | |
pass | |