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}"