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https://github.com/hwchase17/langchain
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54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
import logging
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from urllib.parse import urlparse
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from langchain_community.chat_models.mlflow import ChatMlflow
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logger = logging.getLogger(__name__)
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class ChatDatabricks(ChatMlflow):
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"""`Databricks` chat models API.
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To use, you should have the ``mlflow`` python package installed.
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For more information, see https://mlflow.org/docs/latest/llms/deployments.
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Example:
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.. code-block:: python
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from langchain_community.chat_models import ChatDatabricks
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chat_model = ChatDatabricks(
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target_uri="databricks",
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endpoint="databricks-llama-2-70b-chat",
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temperature=0.1,
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)
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# single input invocation
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print(chat_model.invoke("What is MLflow?").content)
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# single input invocation with streaming response
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for chunk in chat_model.stream("What is MLflow?"):
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print(chunk.content, end="|")
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"""
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target_uri: str = "databricks"
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"""The target URI to use. Defaults to ``databricks``."""
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@property
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def _llm_type(self) -> str:
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"""Return type of chat model."""
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return "databricks-chat"
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@property
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def _mlflow_extras(self) -> str:
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return ""
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def _validate_uri(self) -> None:
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if self.target_uri == "databricks":
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return
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if urlparse(self.target_uri).scheme != "databricks":
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raise ValueError(
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"Invalid target URI. The target URI must be a valid databricks URI."
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)
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