langchain/docs/ecosystem/google_search.md

# Google Search Wrapper

This page covers how to use the Google Search API within LangChain.
It is broken into two parts: installation and setup, and then references to the specific Google Search wrapper.

## Installation and Setup
- Install requirements with `pip install google-api-python-client`
- Set up a Custom Search Engine, following [these instructions](https://stackoverflow.com/questions/37083058/programmatically-searching-google-in-python-using-custom-search)
- Get an API Key and Custom Search Engine ID from the previous step, and set them as environment variables `GOOGLE_API_KEY` and `GOOGLE_CSE_ID` respectively

## Wrappers

### Utility

There exists a GoogleSearchAPIWrapper utility which wraps this API. To import this utility:

```python
from langchain.utilities import GoogleSearchAPIWrapper
```

For a more detailed walkthrough of this wrapper, see [this notebook](../modules/utils/examples/google_search.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(["google-search"])
```

For more information on this, see [this page](../modules/agents/tools.md)
Docs refactor (#480) 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> 2023-01-02 16:24:09 +00:00			`# Google Search Wrapper`

			`This page covers how to use the Google Search API within LangChain.`
docs: small typo google_search.md (#692) 2023-01-22 21:09:15 +00:00			`It is broken into two parts: installation and setup, and then references to the specific Google Search wrapper.`
Docs refactor (#480) 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> 2023-01-02 16:24:09 +00:00
			`## Installation and Setup`
			- Install requirements with `pip install google-api-python-client`
			`- Set up a Custom Search Engine, following [these instructions](https://stackoverflow.com/questions/37083058/programmatically-searching-google-in-python-using-custom-search)`
			- Get an API Key and Custom Search Engine ID from the previous step, and set them as environment variables `GOOGLE_API_KEY` and `GOOGLE_CSE_ID` respectively

			`## Wrappers`

			`### Utility`

			`There exists a GoogleSearchAPIWrapper utility which wraps this API. To import this utility:`

			```python
			`from langchain.utilities import GoogleSearchAPIWrapper`
			```

			`For a more detailed walkthrough of this wrapper, see [this notebook](../modules/utils/examples/google_search.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(["google-search"])`
			```

			`For more information on this, see [this page](../modules/agents/tools.md)`