langchain_community.embeddings.databricks

from __future__ import annotations

from typing import Iterator, List
from urllib.parse import urlparse

from langchain_community.embeddings.mlflow import MlflowEmbeddings


def _chunk(texts: List[str], size: int) -> Iterator[List[str]]:
    for i in range(0, len(texts), size):
        yield texts[i : i + size]


[docs]class DatabricksEmbeddings(MlflowEmbeddings):
    """Databricks嵌入。

    要使用，您应该安装``mlflow`` python包。
    更多信息，请参见https://mlflow.org/docs/latest/llms/deployments。

    示例:
        .. code-block:: python

            from langchain_community.embeddings import DatabricksEmbeddings

            embeddings = DatabricksEmbeddings(
                target_uri="databricks",
                endpoint="embeddings",
            )
"""

    target_uri: str = "databricks"
    """要使用的目标URI。默认为“databricks”。"""

    @property
    def _mlflow_extras(self) -> str:
        return ""

    def _validate_uri(self) -> None:
        if self.target_uri == "databricks":
            return

        if urlparse(self.target_uri).scheme != "databricks":
            raise ValueError(
                "Invalid target URI. The target URI must be a valid databricks URI."
            )
Source code for langchain_community.embeddings.databricks
