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8516a03a02
This PR upgrades langchain-community to pydantic 2.
* Most of this PR was auto-generated using code mods with gritql
(https://github.com/eyurtsev/migrate-pydantic/tree/main)
* Subsequently, some code was fixed manually due to accommodate
differences between pydantic 1 and 2
Breaking Changes:
- Use TEXTEMBED_API_KEY and TEXTEMBEB_API_URL for env variables for text
embed integrations:
cbea780492
Other changes:
- Added pydantic_settings as a required dependency for community. This
may be removed if we have enough time to convert the dependency into an
optional one.
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
"""Util that calls WolframAlpha."""
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from typing import Any, Dict, Optional
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from langchain_core.utils import get_from_dict_or_env
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from pydantic import BaseModel, ConfigDict, model_validator
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class WolframAlphaAPIWrapper(BaseModel):
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"""Wrapper for Wolfram Alpha.
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Docs for using:
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1. Go to wolfram alpha and sign up for a developer account
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2. Create an app and get your APP ID
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3. Save your APP ID into WOLFRAM_ALPHA_APPID env variable
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4. pip install wolframalpha
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"""
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wolfram_client: Any #: :meta private:
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wolfram_alpha_appid: Optional[str] = None
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model_config = ConfigDict(
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extra="forbid",
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)
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@model_validator(mode="before")
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@classmethod
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def validate_environment(cls, values: Dict) -> Any:
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"""Validate that api key and python package exists in environment."""
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wolfram_alpha_appid = get_from_dict_or_env(
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values, "wolfram_alpha_appid", "WOLFRAM_ALPHA_APPID"
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)
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values["wolfram_alpha_appid"] = wolfram_alpha_appid
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try:
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import wolframalpha
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except ImportError:
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raise ImportError(
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"wolframalpha is not installed. "
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"Please install it with `pip install wolframalpha`"
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)
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client = wolframalpha.Client(wolfram_alpha_appid)
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values["wolfram_client"] = client
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return values
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def run(self, query: str) -> str:
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"""Run query through WolframAlpha and parse result."""
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res = self.wolfram_client.query(query)
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try:
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assumption = next(res.pods).text
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answer = next(res.results).text
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except StopIteration:
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return "Wolfram Alpha wasn't able to answer it"
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if answer is None or answer == "":
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# We don't want to return the assumption alone if answer is empty
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return "No good Wolfram Alpha Result was found"
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else:
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return f"Assumption: {assumption} \nAnswer: {answer}"
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