Source code for langchain_community.chat_models.databricks

import logging
from urllib.parse import urlparse

from langchain_community.chat_models.mlflow import ChatMlflow

logger = logging.getLogger(__name__)

[docs]class ChatDatabricks(ChatMlflow): """`Databricks` chat models API. To use, you should have the ``mlflow`` python package installed. For more information, see Example: .. code-block:: python from langchain_community.chat_models import ChatDatabricks chat_model = ChatDatabricks( target_uri="databricks", endpoint="databricks-llama-2-70b-chat", temperature=0.1, ) # single input invocation print(chat_model.invoke("What is MLflow?").content) # single input invocation with streaming response for chunk in"What is MLflow?"): print(chunk.content, end="|") """ target_uri: str = "databricks" """The target URI to use. Defaults to ``databricks``.""" @property def _llm_type(self) -> str: """Return type of chat model.""" return "databricks-chat" @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." )