# Source: https://docs.embedchain.ai/components/data-sources/gmail.md

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.embedchain.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# 📬 Gmail

To use GmailLoader you must install the extra dependencies with `pip install --upgrade embedchain[gmail]`.

The `source` must be a valid Gmail search query, you can refer `https://support.google.com/mail/answer/7190?hl=en` to build a query.

To load Gmail messages, you MUST use the data\_type as `gmail`. Otherwise the source will be detected as simple `text`.

To use this you need to save `credentials.json` in the directory from where you will run the loader. Follow these steps to get the credentials

1. Go to the [Google Cloud Console](https://console.cloud.google.com/apis/credentials).
2. Create a project if you don't have one already.
3. Create an `OAuth Consent Screen` in the project. You may need to select the `external` option.
4. Make sure the consent screen is published.
5. Enable the [Gmail API](https://console.cloud.google.com/apis/api/gmail.googleapis.com)
6. Create credentials from the `Credentials` tab.
7. Select the type `OAuth Client ID`.
8. Choose the application type `Web application`. As a name you can choose `embedchain` or any other name as per your use case.
9. Add an authorized redirect URI for `http://localhost:8080/`.
10. You can leave everything else at default, finish the creation.
11. When you are done, a modal opens where you can download the details in `json` format.
12. Put the `.json` file in your current directory and rename it to `credentials.json`

```python  theme={null}
from embedchain import App

app = App()

gmail_filter = "to: me label:inbox"
app.add(gmail_filter, data_type="gmail")
app.query("Summarize my email conversations")
```