forked from Archives/langchain
985496f4be
Big docs refactor! Motivation is to make it easier for people to find resources they are looking for. To accomplish this, there are now three main sections: - Getting Started: steps for getting started, walking through most core functionality - Modules: these are different modules of functionality that langchain provides. Each part here has a "getting started", "how to", "key concepts" and "reference" section (except in a few select cases where it didnt easily fit). - Use Cases: this is to separate use cases (like summarization, question answering, evaluation, etc) from the modules, and provide a different entry point to the code base. There is also a full reference section, as well as extra resources (glossary, gallery, etc) Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
909 B
909 B
SerpAPI
This page covers how to use the SerpAPI search APIs within LangChain. It is broken into two parts: installation and setup, and then references to specific Pinecone wrappers.
Installation and Setup
- Install requirements with
pip install google-search-results
- Get a SerpAPI api key and either set it as an environment variable (
SERPAPI_API_KEY
)
Wrappers
Utility
There exists a SerpAPI utility which wraps this API. To import this utility:
from langchain.utilities import SerpAPIWrapper
For a more detailed walkthrough of this wrapper, see this notebook.
Tool
You can also easily load this wrapper as a Tool (to use with an Agent). You can do this with:
from langchain.agents import load_tools
tools = load_tools(["serpapi"])
For more information on this, see this page