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>
32 lines
909 B
Markdown
32 lines
909 B
Markdown
# SerpAPI
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This page covers how to use the SerpAPI search APIs within LangChain.
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It is broken into two parts: installation and setup, and then references to specific Pinecone wrappers.
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## Installation and Setup
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- Install requirements with `pip install google-search-results`
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- Get a SerpAPI api key and either set it as an environment variable (`SERPAPI_API_KEY`)
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## Wrappers
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### Utility
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There exists a SerpAPI utility which wraps this API. To import this utility:
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```python
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from langchain.utilities import SerpAPIWrapper
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```
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For a more detailed walkthrough of this wrapper, see [this notebook](../modules/utils/examples/serpapi.ipynb).
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### Tool
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You can also easily load this wrapper as a Tool (to use with an Agent).
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You can do this with:
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```python
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from langchain.agents import load_tools
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tools = load_tools(["serpapi"])
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```
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For more information on this, see [this page](../modules/agents/tools.md)
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