Set cluster_id and cluster_driver_port and do not set endpoint_name.
The expected server schema (using JSON schema) is:
inputs:
{"type": "object",
 "properties": {
    "prompt": {"type": "string"},
    "stop": {"type": "array", "items": {"type": "string"}}},
 "required": ["prompt"]}`
outputs: {"type": "string"}
If the endpoint model signature is different or you want to set extra params,
you can use transform_input_fn and transform_output_fn to apply necessary
transformations before and after the query.
Validators
raise_deprecation » all fields
set_cluster_driver_port » cluster_driver_port
set_cluster_id » cluster_id
set_model_kwargs » model_kwargs
set_verbose » verbose
field api_token: str [Optional]#
Databricks personal access token.
If not provided, the default value is determined by
the DATABRICKS_TOKEN environment variable if present, or
an automatically generated temporary token if running inside a Databricks
notebook attached to an interactive cluster in “single user” or
“no isolation shared” mode.
field cluster_driver_port: Optional[str] = None#
The port number used by the HTTP server running on the cluster driver node.
The server should listen on the driver IP address or simply 0.0.0.0 to connect.
We recommend the server using a port number between [3000, 8000].
field cluster_id: Optional[str] = None#
ID of the cluster if connecting to a cluster driver proxy app.
If neither endpoint_name nor cluster_id is not provided and the code runs
inside a Databricks notebook attached to an interactive cluster in “single user”
or “no isolation shared” mode, the current cluster ID is used as default.
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html