diff --git a/docs/ecosystem/wolfram_alpha.md b/docs/ecosystem/wolfram_alpha.md new file mode 100644 index 00000000..2c6f844c --- /dev/null +++ b/docs/ecosystem/wolfram_alpha.md @@ -0,0 +1,34 @@ +# Wolfram Alpha Wrapper + +This page covers how to use the Wolfram Alpha API within LangChain. +It is broken into two parts: installation and setup, and then references to specific Wolfram Alpha wrappers. + +## Installation and Setup +- Install requirements with `pip install wolframalpha` +- Go to wolfram alpha and sign up for a developer account [here](https://developer.wolframalpha.com/) +- Create an app and get your APP ID +- Set your APP ID as an environment variable `WOLFRAM_ALPHA_APPID` + + +## Wrappers + +### Utility + +There exists a WolframAlphaAPIWrapper utility which wraps this API. To import this utility: + +```python +from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper +``` + +For a more detailed walkthrough of this wrapper, see [this notebook](../modules/utils/examples/wolfram_alpha.ipynb). + +### Tool + +You can also easily load this wrapper as a Tool (to use with an Agent). +You can do this with: +```python +from langchain.agents import load_tools +tools = load_tools(["wolfram-alpha"]) +``` + +For more information on this, see [this page](../modules/agents/tools.md) diff --git a/docs/modules/agents/tools.md b/docs/modules/agents/tools.md index 8f35a1fc..212528a1 100644 --- a/docs/modules/agents/tools.md +++ b/docs/modules/agents/tools.md @@ -43,6 +43,12 @@ Below is a list of all supported tools and relevant information: - Notes: Calls the Serp API and then parses results. - Requires LLM: No +**wolfram-alpha** +- Tool Name: Wolfram Alpha +- Tool Description: A wolfram alpha search engine. Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Input should be a search query. +- Notes: Calls the Wolfram Alpha API and then parses results. +- Requires LLM: No + **requests** - Tool Name: Requests - Tool Description: A portal to the internet. Use this when you need to get specific content from a site. Input should be a specific url, and the output will be all the text on that page. diff --git a/docs/modules/utils/examples/wolfram_alpha.ipynb b/docs/modules/utils/examples/wolfram_alpha.ipynb new file mode 100644 index 00000000..5e86c683 --- /dev/null +++ b/docs/modules/utils/examples/wolfram_alpha.ipynb @@ -0,0 +1,124 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "245a954a", + "metadata": {}, + "source": [ + "# Wolfram Alpha\n", + "\n", + "This notebook goes over how to use the wolfram alpha component.\n", + "\n", + "First, you need to set up your Wolfram Alpha developer account and get your APP ID:\n", + "\n", + "1. Go to wolfram alpha and sign up for a developer account [here](https://developer.wolframalpha.com/)\n", + "2. Create an app and get your APP ID\n", + "3. pip install wolframalpha\n", + "\n", + "Then we will need to set some environment variables:\n", + "1. Save your APP ID into WOLFRAM_ALPHA_APPID env variable" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "961b3689", + "metadata": { + "vscode": { + "languageId": "shellscript" + } + }, + "outputs": [], + "source": [ + "pip install wolframalpha" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "34bb5968", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "os.environ[\"WOLFRAM_ALPHA_APPID\"] = \"\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "ac4910f8", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "84b8f773", + "metadata": {}, + "outputs": [], + "source": [ + "wolfram = WolframAlphaAPIWrapper()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "068991a6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'x = 2/5'" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wolfram.run(\"What is 2x+5 = -3x + 7?\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "028f4cba", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "vscode": { + "interpreter": { + "hash": "53f3bc57609c7a84333bb558594977aa5b4026b1d6070b93987956689e367341" + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/reference/integrations.md b/docs/reference/integrations.md index 3119fe65..ec6b964b 100644 --- a/docs/reference/integrations.md +++ b/docs/reference/integrations.md @@ -21,6 +21,9 @@ The following use cases require specific installs and api keys: - _GoogleSearchAPI_: - Install requirements with `pip install google-api-python-client` - Get a Google api key and either set it as an environment variable (`GOOGLE_API_KEY`) or pass it to the LLM constructor as `google_api_key`. You will also need to set the `GOOGLE_CSE_ID` environment variable to your custom search engine id. You can pass it to the LLM constructor as `google_cse_id` as well. +- _WolframAlphaAPI_: + - Install requirements with `pip install wolframalpha` + - Get a Wolfram Alpha api key and either set it as an environment variable (`WOLFRAM_ALPHA_APPID`) or pass it to the LLM constructor as `wolfram_alpha_appid`. - _NatBot_: - Install requirements with `pip install playwright` - _Wikipedia_: diff --git a/langchain/__init__.py b/langchain/__init__.py index 071b8a3e..c0bddaa9 100644 --- a/langchain/__init__.py +++ b/langchain/__init__.py @@ -29,6 +29,7 @@ from langchain.prompts import ( from langchain.serpapi import SerpAPIChain, SerpAPIWrapper from langchain.sql_database import SQLDatabase from langchain.utilities.google_search import GoogleSearchAPIWrapper +from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper from langchain.vectorstores import FAISS, ElasticVectorSearch verbose: bool = False @@ -44,6 +45,7 @@ __all__ = [ "SerpAPIWrapper", "SerpAPIChain", "GoogleSearchAPIWrapper", + "WolframAlphaAPIWrapper", "Cohere", "OpenAI", "BasePromptTemplate", diff --git a/langchain/agents/load_tools.py b/langchain/agents/load_tools.py index 57ee5516..c5e8b43d 100644 --- a/langchain/agents/load_tools.py +++ b/langchain/agents/load_tools.py @@ -13,6 +13,7 @@ from langchain.requests import RequestsWrapper from langchain.serpapi import SerpAPIWrapper from langchain.utilities.bash import BashProcess from langchain.utilities.google_search import GoogleSearchAPIWrapper +from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper def _get_python_repl() -> Tool: @@ -39,6 +40,14 @@ def _get_google_search() -> Tool: ) +def _get_wolfram_alpha() -> Tool: + return Tool( + "Wolfram Alpha", + WolframAlphaAPIWrapper().run, + "A wrapper around Wolfram Alpha. Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Input should be a search query.", + ) + + def _get_requests() -> Tool: return Tool( "Requests", @@ -61,6 +70,7 @@ _BASE_TOOLS = { "requests": _get_requests, "terminal": _get_terminal, "google-search": _get_google_search, + "wolfram-alpha": _get_wolfram_alpha, } diff --git a/langchain/utilities/__init__.py b/langchain/utilities/__init__.py index 7085c2e2..797d64b0 100644 --- a/langchain/utilities/__init__.py +++ b/langchain/utilities/__init__.py @@ -4,11 +4,13 @@ from langchain.requests import RequestsWrapper from langchain.serpapi import SerpAPIWrapper from langchain.utilities.bash import BashProcess from langchain.utilities.google_search import GoogleSearchAPIWrapper +from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper __all__ = [ "BashProcess", "RequestsWrapper", "PythonREPL", "GoogleSearchAPIWrapper", + "WolframAlphaAPIWrapper", "SerpAPIWrapper", ] diff --git a/langchain/utilities/wolfram_alpha.py b/langchain/utilities/wolfram_alpha.py new file mode 100644 index 00000000..085ee592 --- /dev/null +++ b/langchain/utilities/wolfram_alpha.py @@ -0,0 +1,59 @@ +"""Util that calls WolframAlpha.""" +from typing import Any, Dict, Optional + +from pydantic import BaseModel, Extra, root_validator + +from langchain.utils import get_from_dict_or_env + + +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 #: :meta private: + wolfram_alpha_appid: Optional[str] = None + + class Config: + """Configuration for this pydantic object.""" + + extra = Extra.forbid + + @root_validator() + def validate_environment(cls, values: Dict) -> Dict: + """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 + + # TODO: Add error handling if keys are missing + return values + + def run(self, query: str) -> str: + """Run query through WolframAlpha and parse result.""" + res = self.wolfram_client.query(query) + # Includes only text from the response + answer = next(res.results).text + if answer is None or answer == "": + return "No good Wolfram Alpha Result was found" + return answer diff --git a/poetry.lock b/poetry.lock index 8cadfa13..7a0fc260 100644 --- a/poetry.lock +++ b/poetry.lock @@ -348,31 +348,31 @@ numpy = ">=1.15.0" [[package]] name = "blobfile" -version = "2.0.0" +version = "2.0.1" description = "Read GCS, ABS and local paths with the same interface, clone of tensorflow.io.gfile" category = "main" optional = true python-versions = ">=3.7.0" files = [ - {file = "blobfile-2.0.0-py3-none-any.whl", hash = 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"wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "weaviate-client", "redis", "google-api-python-client", "wolframalpha"] llms = ["manifest-ml", "torch", "transformers"] [metadata] lock-version = "2.0" python-versions = ">=3.8.1,<4.0" -content-hash = "e6d702a8244b8646db76252fedde20b938ebc33214ac8d912681b190e769be0f" +content-hash = "bc82687494f292761179416f1da8357b3e25657df45f87dc509281767a94ab02" diff --git a/pyproject.toml b/pyproject.toml index 218084dc..fa178842 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,6 +29,7 @@ tiktoken = {version = "^0", optional = true, python="^3.9"} pinecone-client = {version = "^2", optional = true} weaviate-client = {version = "^3", optional = true} google-api-python-client = {version = "2.70.0", optional = true} +wolframalpha = {version = "5.0.0", optional = true} [tool.poetry.group.docs.dependencies] autodoc_pydantic = "^1.8.0" @@ -73,7 +74,7 @@ playwright = "^1.28.0" [tool.poetry.extras] llms = ["cohere", 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b/tests/integration_tests/test_wolfram_alpha_api.py @@ -0,0 +1,9 @@ +"""Integration test for Wolfram Alpha API Wrapper.""" +from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper + + +def test_call() -> None: + """Test that call gives the correct answer.""" + search = WolframAlphaAPIWrapper() + output = search.run("what is 2x+18=x+5?") + assert "x = -13" in output