mirror of
https://github.com/hwchase17/langchain.git
synced 2025-09-28 23:07:11 +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()
```
86 lines
2.4 KiB
Python
86 lines
2.4 KiB
Python
"""Tool for the SearxNG search API."""
|
|
|
|
from typing import Optional, Type
|
|
|
|
from langchain_core.callbacks import (
|
|
AsyncCallbackManagerForToolRun,
|
|
CallbackManagerForToolRun,
|
|
)
|
|
from langchain_core.pydantic_v1 import BaseModel, Extra, Field
|
|
from langchain_core.tools import BaseTool
|
|
|
|
from langchain_community.utilities.searx_search import SearxSearchWrapper
|
|
|
|
|
|
class SearxSearchQueryInput(BaseModel):
|
|
"""Input for the SearxSearch tool."""
|
|
|
|
query: str = Field(description="query to look up on searx")
|
|
|
|
|
|
class SearxSearchRun(BaseTool):
|
|
"""Tool that queries a Searx instance."""
|
|
|
|
name: str = "searx_search"
|
|
description: str = (
|
|
"A meta search engine."
|
|
"Useful for when you need to answer questions about current events."
|
|
"Input should be a search query."
|
|
)
|
|
wrapper: SearxSearchWrapper
|
|
kwargs: dict = Field(default_factory=dict)
|
|
args_schema: Type[BaseModel] = SearxSearchQueryInput
|
|
|
|
def _run(
|
|
self,
|
|
query: str,
|
|
run_manager: Optional[CallbackManagerForToolRun] = None,
|
|
) -> str:
|
|
"""Use the tool."""
|
|
return self.wrapper.run(query, **self.kwargs)
|
|
|
|
async def _arun(
|
|
self,
|
|
query: str,
|
|
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
|
|
) -> str:
|
|
"""Use the tool asynchronously."""
|
|
return await self.wrapper.arun(query, **self.kwargs)
|
|
|
|
|
|
class SearxSearchResults(BaseTool):
|
|
"""Tool that queries a Searx instance and gets back json."""
|
|
|
|
name: str = "searx_search_results"
|
|
description: str = (
|
|
"A meta search engine."
|
|
"Useful for when you need to answer questions about current events."
|
|
"Input should be a search query. Output is a JSON array of the query results"
|
|
)
|
|
wrapper: SearxSearchWrapper
|
|
num_results: int = 4
|
|
kwargs: dict = Field(default_factory=dict)
|
|
|
|
class Config:
|
|
"""Pydantic config."""
|
|
|
|
extra = Extra.allow
|
|
|
|
def _run(
|
|
self,
|
|
query: str,
|
|
run_manager: Optional[CallbackManagerForToolRun] = None,
|
|
) -> str:
|
|
"""Use the tool."""
|
|
return str(self.wrapper.results(query, self.num_results, **self.kwargs))
|
|
|
|
async def _arun(
|
|
self,
|
|
query: str,
|
|
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
|
|
) -> str:
|
|
"""Use the tool asynchronously."""
|
|
return (
|
|
await self.wrapper.aresults(query, self.num_results, **self.kwargs)
|
|
).__str__()
|