mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-20 14:31:44 +00:00
226802f0c4
This change adds args_schema (pydantic BaseModel) to SearxSearchRun for
correct schema formatting on LLM function calls
Issue: currently using SearxSearchRun with OpenAI function calling
returns the following error "TypeError: SearxSearchRun._run() got an
unexpected keyword argument '__arg1' ".
This happens because the schema sent to the LLM is "input:
'{"__arg1":"foobar"}'" while the method should be called with the
"query" parameter.
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
85 lines
2.4 KiB
Python
85 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__()
|