langchain/libs/community/tests/unit_tests/llms/test_databricks.py
Corey Zumar 3a068b26f3
community[patch]: Databricks - fix scope of dangerous deserialization error in Databricks LLM connector (#20368)
fix scope of dangerous deserialization error in Databricks LLM connector

---------

Signed-off-by: dbczumar <corey.zumar@databricks.com>
2024-04-12 17:27:26 -04:00

116 lines
3.7 KiB
Python

"""test Databricks LLM"""
from pathlib import Path
from typing import Any, Dict
import pytest
from pytest import MonkeyPatch
from langchain_community.llms.databricks import (
Databricks,
_load_pickled_fn_from_hex_string,
)
from langchain_community.llms.loading import load_llm
from tests.integration_tests.llms.utils import assert_llm_equality
class MockDatabricksServingEndpointClient:
def __init__(
self,
host: str,
api_token: str,
endpoint_name: str,
databricks_uri: str,
task: str,
):
self.host = host
self.api_token = api_token
self.endpoint_name = endpoint_name
self.databricks_uri = databricks_uri
self.task = task
def transform_input(**request: Any) -> Dict[str, Any]:
request["messages"] = [{"role": "user", "content": request["prompt"]}]
del request["prompt"]
return request
@pytest.mark.requires("cloudpickle")
def test_serde_transform_input_fn(monkeypatch: MonkeyPatch) -> None:
import cloudpickle
monkeypatch.setattr(
"langchain_community.llms.databricks._DatabricksServingEndpointClient",
MockDatabricksServingEndpointClient,
)
monkeypatch.setenv("DATABRICKS_HOST", "my-default-host")
monkeypatch.setenv("DATABRICKS_TOKEN", "my-default-token")
llm = Databricks(
endpoint_name="some_end_point_name", # Value should not matter for this test
transform_input_fn=transform_input,
allow_dangerous_deserialization=True,
)
params = llm._default_params
pickled_string = cloudpickle.dumps(transform_input).hex()
assert params["transform_input_fn"] == pickled_string
request = {"prompt": "What is the meaning of life?"}
fn = _load_pickled_fn_from_hex_string(
data=params["transform_input_fn"],
allow_dangerous_deserialization=True,
)
assert fn(**request) == transform_input(**request)
def test_saving_loading_llm(monkeypatch: MonkeyPatch, tmp_path: Path) -> None:
monkeypatch.setattr(
"langchain_community.llms.databricks._DatabricksServingEndpointClient",
MockDatabricksServingEndpointClient,
)
monkeypatch.setenv("DATABRICKS_HOST", "my-default-host")
monkeypatch.setenv("DATABRICKS_TOKEN", "my-default-token")
llm = Databricks(
endpoint_name="chat",
temperature=0.1,
)
llm.save(file_path=tmp_path / "databricks.yaml")
loaded_llm = load_llm(tmp_path / "databricks.yaml")
assert_llm_equality(llm, loaded_llm)
@pytest.mark.requires("cloudpickle")
def test_saving_loading_llm_dangerous_serde_check(
monkeypatch: MonkeyPatch, tmp_path: Path
) -> None:
monkeypatch.setattr(
"langchain_community.llms.databricks._DatabricksServingEndpointClient",
MockDatabricksServingEndpointClient,
)
monkeypatch.setenv("DATABRICKS_HOST", "my-default-host")
monkeypatch.setenv("DATABRICKS_TOKEN", "my-default-token")
llm1 = Databricks(
endpoint_name="chat",
temperature=0.1,
transform_input_fn=lambda x, y, **kwargs: {},
)
llm1.save(file_path=tmp_path / "databricks1.yaml")
with pytest.raises(ValueError, match="This code relies on the pickle module."):
load_llm(tmp_path / "databricks1.yaml")
load_llm(tmp_path / "databricks1.yaml", allow_dangerous_deserialization=True)
llm2 = Databricks(
endpoint_name="chat", temperature=0.1, transform_output_fn=lambda x: "test"
)
llm2.save(file_path=tmp_path / "databricks2.yaml")
with pytest.raises(ValueError, match="This code relies on the pickle module."):
load_llm(tmp_path / "databricks2.yaml")
load_llm(tmp_path / "databricks2.yaml", allow_dangerous_deserialization=True)