Source code for langchain_community.llms.gooseai

import logging
from typing import Any, Dict, List, Mapping, Optional

from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
from langchain_core.pydantic_v1 import Extra, Field, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env

logger = logging.getLogger(__name__)


class GooseAI(LLM):
    """GooseAI大型语言模型。

要使用，您应该已安装``openai`` python包，并且设置了环境变量``GOOSEAI_API_KEY``为您的API密钥。

可以传递给openai.create调用的任何有效参数，即使在此类中没有明确保存。

示例：
    .. code-block:: python

        from langchain_community.llms import GooseAI
        gooseai = GooseAI(model_name="gpt-neo-20b")"""

    client: Any

    model_name: str = "gpt-neo-20b"
    """要使用的模型名称"""

    temperature: float = 0.7
    """使用哪种采样温度"""

    max_tokens: int = 256
    """生成完成时要生成的最大令牌数。
    -1 返回尽可能多的令牌，考虑到提示和模型的最大上下文大小。"""

    top_p: float = 1
    """每一步需要考虑的标记的总概率质量。"""

    min_tokens: int = 1
    """生成完成所需的最小令牌数量。"""

    frequency_penalty: float = 0
    """根据频率惩罚重复的标记。"""

    presence_penalty: float = 0
    """惩罚重复的标记。"""

    n: int = 1
    """每个提示生成多少个完成。"""

    model_kwargs: Dict[str, Any] = Field(default_factory=dict)
    """保存任何在`create`调用中有效但未明确指定的模型参数。"""

    logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict)
    """调整生成特定令牌的概率。"""

    gooseai_api_key: Optional[SecretStr] = None

    class Config:
        """这是用于pydantic配置的设置。"""

        extra = Extra.ignore

    @root_validator(pre=True)
    def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
        """从传入的额外参数构建额外的kwargs。"""
        all_required_field_names = {field.alias for field in cls.__fields__.values()}

        extra = values.get("model_kwargs", {})
        for field_name in list(values):
            if field_name not in all_required_field_names:
                if field_name in extra:
                    raise ValueError(f"Found {field_name} supplied twice.")
                logger.warning(
                    f"""WARNING! {field_name} is not default parameter.
                    {field_name} was transferred to model_kwargs.
                    Please confirm that {field_name} is what you intended."""
                )
                extra[field_name] = values.pop(field_name)
        values["model_kwargs"] = extra
        return values

    @root_validator()
    def validate_environment(cls, values: Dict) -> Dict:
        """验证环境中是否存在API密钥和Python包。"""
        gooseai_api_key = convert_to_secret_str(
            get_from_dict_or_env(values, "gooseai_api_key", "GOOSEAI_API_KEY")
        )
        values["gooseai_api_key"] = gooseai_api_key
        try:
            import openai

            openai.api_key = gooseai_api_key.get_secret_value()
            openai.api_base = "https://api.goose.ai/v1"
            values["client"] = openai.Completion
        except ImportError:
            raise ImportError(
                "Could not import openai python package. "
                "Please install it with `pip install openai`."
            )
        return values

    @property
    def _default_params(self) -> Dict[str, Any]:
        """获取调用GooseAI API的默认参数。"""
        normal_params = {
            "temperature": self.temperature,
            "max_tokens": self.max_tokens,
            "top_p": self.top_p,
            "min_tokens": self.min_tokens,
            "frequency_penalty": self.frequency_penalty,
            "presence_penalty": self.presence_penalty,
            "n": self.n,
            "logit_bias": self.logit_bias,
        }
        return {**normal_params, **self.model_kwargs}

    @property
    def _identifying_params(self) -> Mapping[str, Any]:
        """获取识别参数。"""
        return {**{"model_name": self.model_name}, **self._default_params}

    @property
    def _llm_type(self) -> str:
        """llm的返回类型。"""
        return "gooseai"

    def _call(
        self,
        prompt: str,
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> str:
        """调用GooseAI API。"""
        params = self._default_params
        if stop is not None:
            if "stop" in params:
                raise ValueError("`stop` found in both the input and default params.")
            params["stop"] = stop

        params = {**params, **kwargs}

        response = self.client.create(engine=self.model_name, prompt=prompt, **params)
        text = response.choices[0].text
        return text