langchain/vectorstores/typesense.py/Typesense/from_client_params
class Typesense:    def from_client_params(
        cls,
        embedding: Embeddings,
        *,
        host: str = "localhost",
        port: Union[str, int] = "8108",
        protocol: str = "http",
        typesense_api_key: Optional[str] = None,
        connection_timeout_seconds: int = 2,
        **kwargs: Any,
    ) -> Typesense:
        """Initialize Typesense directly from client parameters.

        Example:
            .. code-block:: python

                from langchain.embedding.openai import OpenAIEmbeddings
                from langchain.vectorstores import Typesense

                # Pass in typesense_api_key as kwarg or set env var "TYPESENSE_API_KEY".
                vectorstore = Typesense(
                    OpenAIEmbeddings(),
                    host="localhost",
                    port="8108",
                    protocol="http",
                    typesense_collection_name="langchain-memory",
                )
        """
        try:
            from typesense import Client
        except ImportError:
            raise ValueError(
                "Could not import typesense python package. "
                "Please install it with `pip install typesense`."
            )

        node = {
            "host": host,
            "port": str(port),
            "protocol": protocol,
        }
        typesense_api_key = typesense_api_key or get_from_env(
            "typesense_api_key", "TYPESENSE_API_KEY"
        )
        client_config = {
            "nodes": [node],
            "api_key": typesense_api_key,
            "connection_timeout_seconds": connection_timeout_seconds,
        }
        return cls(Client(client_config), embedding, **kwargs)