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#

# Source code for langchain.embeddings.cohere

    """Wrapper around Cohere embedding models."""
    from typing import Any, Dict, List, Optional

    from pydantic import BaseModel, Extra, root_validator

    from langchain.embeddings.base import Embeddings
    from langchain.utils import get_from_dict_or_env

    class CohereEmbeddings(BaseModel, Embeddings):
        """Wrapper around Cohere embedding 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.embeddings import CohereEmbeddings
                cohere = CohereEmbeddings(model="medium", cohere_api_key="my-api-key")
        """

        client: Any  #: :meta private:
        model: str = "large"
        """Model name to use."""

        truncate: Optional[str] = None
        """Truncate embeddings that are too long from start or end ("NONE"|"START"|"END")"""

        cohere_api_key: Optional[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

        def embed_documents(self, texts: List[str]) -> List[List[float]]:
            """Call out to Cohere's embedding endpoint.

            Args:
                texts: The list of texts to embed.

            Returns:
                List of embeddings, one for each text.
            """
            embeddings = self.client.embed(
                model=self.model, texts=texts, truncate=self.truncate
            ).embeddings
            return [list(map(float, e)) for e in embeddings]

        def embed_query(self, text: str) -> List[float]:
            """Call out to Cohere's embedding endpoint.

            Args:
                text: The text to embed.

            Returns:
                Embeddings for the text.
            """
            embedding = self.client.embed(
                model=self.model, texts=[text], truncate=self.truncate
            ).embeddings[0]
            return list(map(float, embedding))