Skip to main content
`Ctrl`+`K`

#

# Source code for langchain.llms.cohere

    """Wrapper around Cohere APIs."""
    import logging
    from typing import Any, Dict, List, Optional

    from pydantic import Extra, root_validator

    from langchain.llms.base import LLM
    from langchain.llms.utils import enforce_stop_tokens
    from langchain.utils import get_from_dict_or_env

    logger = logging.getLogger(__name__)

    class Cohere(LLM):
        """Wrapper around Cohere large language models.

        To use, you should have the ``cohere`` python package installed, and the
        environment variable ``COHERE_API_KEY`` set with your API key, or pass
        it as a named parameter to the constructor.

        Example:
            .. code-block:: python

                from langchain.llms import Cohere
                cohere = Cohere(model="gptd-instruct-tft", cohere_api_key="my-api-key")
        """

        client: Any  #: :meta private:
        model: Optional[str] = None
        """Model name to use."""

        max_tokens: int = 256
        """Denotes the number of tokens to predict per generation."""

        temperature: float = 0.75
        """A non-negative float that tunes the degree of randomness in generation."""

        k: int = 0
        """Number of most likely tokens to consider at each step."""

        p: int = 1
        """Total probability mass of tokens to consider at each step."""

        frequency_penalty: float = 0.0
        """Penalizes repeated tokens according to frequency. Between 0 and 1."""

        presence_penalty: float = 0.0
        """Penalizes repeated tokens. Between 0 and 1."""

        truncate: Optional[str] = None
        """Specify how the client handles inputs longer than the maximum token
        length: Truncate from START, END or NONE"""

        cohere_api_key: Optional[str] = None

        stop: Optional[List[str]] = None

        class Config:
            """Configuration for this pydantic object."""

            extra = Extra.forbid

        @root_validator()
        def validate_environment(cls, values: Dict) -> Dict:
            """Validate that api key and python package exists in environment."""
            cohere_api_key = get_from_dict_or_env(
                values, "cohere_api_key", "COHERE_API_KEY"
            )
            try:
                import cohere

                values["client"] = cohere.Client(cohere_api_key)
            except ImportError:
                raise ValueError(
                    "Could not import cohere python package. "
                    "Please install it with `pip install cohere`."
                )
            return values

        @property
        def _default_params(self) -> Dict[str, Any]:
            """Get the default parameters for calling Cohere API."""
            return {
                "max_tokens": self.max_tokens,
                "temperature": self.temperature,
                "k": self.k,
                "p": self.p,
                "frequency_penalty": self.frequency_penalty,
                "presence_penalty": self.presence_penalty,
                "truncate": self.truncate,
            }

        @property
        def _identifying_params(self) -> Dict[str, Any]:
            """Get the identifying parameters."""
            return {**{"model": self.model}, **self._default_params}

        @property
        def _llm_type(self) -> str:
            """Return type of llm."""
            return "cohere"

        def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
            """Call out to Cohere's generate endpoint.

            Args:
                prompt: The prompt to pass into the model.
                stop: Optional list of stop words to use when generating.

            Returns:
                The string generated by the model.

            Example:
                .. code-block:: python

                    response = cohere("Tell me a joke.")
            """
            params = self._default_params
            if self.stop is not None and stop is not None:
                raise ValueError("`stop` found in both the input and default params.")
            elif self.stop is not None:
                params["stop_sequences"] = self.stop
            else:
                params["stop_sequences"] = stop

            response = self.client.generate(model=self.model, prompt=prompt, **params)
            text = response.generations[0].text
            # If stop tokens are provided, Cohere's endpoint returns them.
            # In order to make this consistent with other endpoints, we strip them.
            if stop is not None or self.stop is not None:
                text = enforce_stop_tokens(text, params["stop_sequences"])
            return text