deep-swarm/camel/models/model_factory.py

# ========= 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. =========
from typing import Dict, Optional, Type, Union

from camel.models.anthropic_model import AnthropicModel
from camel.models.azure_openai_model import AzureOpenAIModel
from camel.models.base_model import BaseModelBackend
from camel.models.cohere_model import CohereModel
from camel.models.deepseek_model import DeepSeekModel
from camel.models.gemini_model import GeminiModel
from camel.models.groq_model import GroqModel
from camel.models.litellm_model import LiteLLMModel
from camel.models.mistral_model import MistralModel
from camel.models.nvidia_model import NvidiaModel
from camel.models.ollama_model import OllamaModel
from camel.models.openai_compatible_model import OpenAICompatibleModel
from camel.models.openai_model import OpenAIModel
from camel.models.qwen_model import QwenModel
from camel.models.reka_model import RekaModel
from camel.models.samba_model import SambaModel
from camel.models.stub_model import StubModel
from camel.models.togetherai_model import TogetherAIModel
from camel.models.vllm_model import VLLMModel
from camel.models.yi_model import YiModel
from camel.models.zhipuai_model import ZhipuAIModel
from camel.types import ModelPlatformType, ModelType, UnifiedModelType
from camel.utils import BaseTokenCounter


class ModelFactory:
    r"""Factory of backend models.

    Raises:
        ValueError: in case the provided model type is unknown.
    """

    @staticmethod
    def create(
        model_platform: ModelPlatformType,
        model_type: Union[ModelType, str],
        model_config_dict: Optional[Dict] = None,
        token_counter: Optional[BaseTokenCounter] = None,
        api_key: Optional[str] = None,
        url: Optional[str] = None,
    ) -> BaseModelBackend:
        r"""Creates an instance of `BaseModelBackend` of the specified type.

        Args:
            model_platform (ModelPlatformType): Platform from which the model
                originates.
            model_type (Union[ModelType, str]): Model for which a
                backend is created. Can be a `str` for open source platforms.
            model_config_dict (Optional[Dict]): A dictionary that will be fed
                into the backend constructor. (default: :obj:`None`)
            token_counter (Optional[BaseTokenCounter], optional): Token
                counter to use for the model. If not provided,
                :obj:`OpenAITokenCounter(ModelType.GPT_4O_MINI)`
                will be used if the model platform didn't provide official
                token counter. (default: :obj:`None`)
            api_key (Optional[str], optional): The API key for authenticating
                with the model service. (default: :obj:`None`)
            url (Optional[str], optional): The url to the model service.
                (default: :obj:`None`)

        Returns:
            BaseModelBackend: The initialized backend.

        Raises:
            ValueError: If there is no backend for the model.
        """
        model_class: Optional[Type[BaseModelBackend]] = None
        model_type = UnifiedModelType(model_type)

        if model_platform.is_ollama:
            model_class = OllamaModel
        elif model_platform.is_vllm:
            model_class = VLLMModel
        elif model_platform.is_openai_compatible_model:
            model_class = OpenAICompatibleModel
        elif model_platform.is_samba:
            model_class = SambaModel
        elif model_platform.is_together:
            model_class = TogetherAIModel
        elif model_platform.is_litellm:
            model_class = LiteLLMModel
        elif model_platform.is_nvidia:
            model_class = NvidiaModel

        elif model_platform.is_openai and model_type.is_openai:
            model_class = OpenAIModel
        elif model_platform.is_azure and model_type.is_azure_openai:
            model_class = AzureOpenAIModel
        elif model_platform.is_anthropic and model_type.is_anthropic:
            model_class = AnthropicModel
        elif model_platform.is_groq and model_type.is_groq:
            model_class = GroqModel
        elif model_platform.is_zhipuai and model_type.is_zhipuai:
            model_class = ZhipuAIModel
        elif model_platform.is_gemini and model_type.is_gemini:
            model_class = GeminiModel
        elif model_platform.is_mistral and model_type.is_mistral:
            model_class = MistralModel
        elif model_platform.is_reka and model_type.is_reka:
            model_class = RekaModel
        elif model_platform.is_cohere and model_type.is_cohere:
            model_class = CohereModel
        elif model_platform.is_yi and model_type.is_yi:
            model_class = YiModel
        elif model_platform.is_qwen and model_type.is_qwen:
            model_class = QwenModel
        elif model_platform.is_deepseek:
            model_class = DeepSeekModel
        elif model_type == ModelType.STUB:
            model_class = StubModel

        if model_class is None:
            raise ValueError(
                f"Unknown pair of model platform `{model_platform}` "
                f"and model type `{model_type}`."
            )
        return model_class(
            model_type=model_type,
            model_config_dict=model_config_dict,
            api_key=api_key,
            url=url,
            token_counter=token_counter,
        )