Source code for langchain_community.utilities.wolfram_alpha

"""Util that calls WolframAlpha."""

from typing import Any, Dict, Optional

from langchain_core.utils import get_from_dict_or_env
from pydantic import BaseModel, ConfigDict, model_validator


[docs] class WolframAlphaAPIWrapper(BaseModel): """Wrapper for Wolfram Alpha. Docs for using: 1. Go to wolfram alpha and sign up for a developer account 2. Create an app and get your APP ID 3. Save your APP ID into WOLFRAM_ALPHA_APPID env variable 4. pip install wolframalpha """ wolfram_client: Any = None #: :meta private: wolfram_alpha_appid: Optional[str] = None model_config = ConfigDict( extra="forbid", ) @model_validator(mode="before") @classmethod def validate_environment(cls, values: Dict) -> Any: """Validate that api key and python package exists in environment.""" wolfram_alpha_appid = get_from_dict_or_env( values, "wolfram_alpha_appid", "WOLFRAM_ALPHA_APPID" ) values["wolfram_alpha_appid"] = wolfram_alpha_appid try: import wolframalpha except ImportError: raise ImportError( "wolframalpha is not installed. " "Please install it with `pip install wolframalpha`" ) client = wolframalpha.Client(wolfram_alpha_appid) values["wolfram_client"] = client return values
[docs] def run(self, query: str) -> str: """Run query through WolframAlpha and parse result.""" res = self.wolfram_client.query(query) try: assumption = next(res.pods).text answer = next(res.results).text except StopIteration: return "Wolfram Alpha wasn't able to answer it" if answer is None or answer == "": # We don't want to return the assumption alone if answer is empty return "No good Wolfram Alpha Result was found" else: return f"Assumption: {assumption} \nAnswer: {answer}"