mirror of
https://github.com/hwchase17/langchain.git
synced 2025-11-23 17:06:54 +00:00
a0c2281540
```python
"""python scripts/update_mypy_ruff.py"""
import glob
import tomllib
from pathlib import Path
import toml
import subprocess
import re
ROOT_DIR = Path(__file__).parents[1]
def main():
for path in glob.glob(str(ROOT_DIR / "libs/**/pyproject.toml"), recursive=True):
print(path)
with open(path, "rb") as f:
pyproject = tomllib.load(f)
try:
pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = (
"^1.10"
)
pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = (
"^0.5"
)
except KeyError:
continue
with open(path, "w") as f:
toml.dump(pyproject, f)
cwd = "/".join(path.split("/")[:-1])
completed = subprocess.run(
"poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
logs = completed.stdout.split("\n")
to_ignore = {}
for l in logs:
if re.match("^(.*)\:(\d+)\: error:.*\[(.*)\]", l):
path, line_no, error_type = re.match(
"^(.*)\:(\d+)\: error:.*\[(.*)\]", l
).groups()
if (path, line_no) in to_ignore:
to_ignore[(path, line_no)].append(error_type)
else:
to_ignore[(path, line_no)] = [error_type]
print(len(to_ignore))
for (error_path, line_no), error_types in to_ignore.items():
all_errors = ", ".join(error_types)
full_path = f"{cwd}/{error_path}"
try:
with open(full_path, "r") as f:
file_lines = f.readlines()
except FileNotFoundError:
continue
file_lines[int(line_no) - 1] = (
file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n"
)
with open(full_path, "w") as f:
f.write("".join(file_lines))
subprocess.run(
"poetry run ruff format .; poetry run ruff --select I --fix .",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
if __name__ == "__main__":
main()
```
117 lines
3.7 KiB
Python
117 lines
3.7 KiB
Python
"""test Databricks LLM"""
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from pathlib import Path
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from typing import Any, Dict
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import pytest
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from pytest import MonkeyPatch
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from langchain_community.llms.databricks import (
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Databricks,
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_load_pickled_fn_from_hex_string,
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)
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from langchain_community.llms.loading import load_llm
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from tests.integration_tests.llms.utils import assert_llm_equality
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class MockDatabricksServingEndpointClient:
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def __init__(
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self,
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host: str,
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api_token: str,
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endpoint_name: str,
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databricks_uri: str,
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task: str,
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):
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self.host = host
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self.api_token = api_token
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self.endpoint_name = endpoint_name
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self.databricks_uri = databricks_uri
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self.task = task
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def transform_input(**request: Any) -> Dict[str, Any]:
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request["messages"] = [{"role": "user", "content": request["prompt"]}]
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del request["prompt"]
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return request
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@pytest.mark.requires("cloudpickle")
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def test_serde_transform_input_fn(monkeypatch: MonkeyPatch) -> None:
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import cloudpickle
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monkeypatch.setattr(
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"langchain_community.llms.databricks._DatabricksServingEndpointClient",
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MockDatabricksServingEndpointClient,
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)
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monkeypatch.setenv("DATABRICKS_HOST", "my-default-host")
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monkeypatch.setenv("DATABRICKS_TOKEN", "my-default-token")
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llm = Databricks(
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endpoint_name="some_end_point_name", # Value should not matter for this test
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transform_input_fn=transform_input,
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allow_dangerous_deserialization=True,
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)
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params = llm._default_params
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pickled_string = cloudpickle.dumps(transform_input).hex()
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assert params["transform_input_fn"] == pickled_string
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request = {"prompt": "What is the meaning of life?"}
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fn = _load_pickled_fn_from_hex_string(
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data=params["transform_input_fn"],
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allow_dangerous_deserialization=True,
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)
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assert fn(**request) == transform_input(**request)
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def test_saving_loading_llm(monkeypatch: MonkeyPatch, tmp_path: Path) -> None:
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monkeypatch.setattr(
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"langchain_community.llms.databricks._DatabricksServingEndpointClient",
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MockDatabricksServingEndpointClient,
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)
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monkeypatch.setenv("DATABRICKS_HOST", "my-default-host")
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monkeypatch.setenv("DATABRICKS_TOKEN", "my-default-token")
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llm = Databricks(
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endpoint_name="chat",
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temperature=0.1,
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)
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llm.save(file_path=tmp_path / "databricks.yaml")
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loaded_llm = load_llm(tmp_path / "databricks.yaml")
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assert_llm_equality(llm, loaded_llm)
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@pytest.mark.requires("cloudpickle")
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def test_saving_loading_llm_dangerous_serde_check(
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monkeypatch: MonkeyPatch, tmp_path: Path
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) -> None:
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monkeypatch.setattr(
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"langchain_community.llms.databricks._DatabricksServingEndpointClient",
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MockDatabricksServingEndpointClient,
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)
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monkeypatch.setenv("DATABRICKS_HOST", "my-default-host")
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monkeypatch.setenv("DATABRICKS_TOKEN", "my-default-token")
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llm1 = Databricks(
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endpoint_name="chat",
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temperature=0.1,
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transform_input_fn=lambda x, y, **kwargs: {},
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)
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llm1.save(file_path=tmp_path / "databricks1.yaml")
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with pytest.raises(ValueError, match="This code relies on the pickle module."):
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load_llm(tmp_path / "databricks1.yaml")
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load_llm(tmp_path / "databricks1.yaml", allow_dangerous_deserialization=True)
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llm2 = Databricks(
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endpoint_name="chat", temperature=0.1, transform_output_fn=lambda x: "test"
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)
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llm2.save(file_path=tmp_path / "databricks2.yaml")
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with pytest.raises(ValueError, match="This code relies on the pickle module."):
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load_llm(tmp_path / "databricks2.yaml")
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load_llm(tmp_path / "databricks2.yaml", allow_dangerous_deserialization=True)
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