---
id: 'ai-vecs-python-client'
title: 'Creating and managing collections'
subtitle: 'Connecting to your database with Colab.'
breadcrumb: 'AI Quickstarts'
---

This guide will walk you through a basic ["Hello World"](https://github.com/supabase/supabase/blob/master/examples/ai/vector_hello_world.ipynb) example using Colab and Supabase Vecs. You'll learn how to:

1. Launch a Postgres database that uses pgvector to store embeddings
1. Launch a notebook that connects to your database
1. Create a vector collection
1. Add data to the collection
1. Query the collection

<$Partial path="database_setup.mdx" />

## Launching a notebook

Launch our [`vector_hello_world`](https://github.com/supabase/supabase/blob/master/examples/ai/vector_hello_world.ipynb) notebook in Colab:

<a
  className="w-64"
  href="https://colab.research.google.com/github/supabase/supabase/blob/master/examples/ai/vector_hello_world.ipynb"
>
  <img src="/docs/img/ai/colab-badge.svg" />
</a>

At the top of the notebook, you'll see a button `Copy to Drive`. Click this button to copy the notebook to your Google Drive.

## Connecting to your database

Inside the Notebook, find the cell which specifies the `DB_CONNECTION`. It will contain some code like this:

```python
import vecs

DB_CONNECTION = "postgresql://<user>:<password>@<host>:<port>/<db_name>"

# create vector store client
vx = vecs.create_client(DB_CONNECTION)
```

Replace the `DB_CONNECTION` with your Session pooler connection string. You can find the connection string on your project dashboard by clicking [Connect](/dashboard/project/_?showConnect=true).

<Admonition type='note'>

SQLAlchemy requires the connection string to start with `postgresql://` (instead of `postgres://`). Don't forget to rename this after copying the string from the dashboard.

</Admonition>

<Admonition type='note'>

You must use the Session pooler connection string with Google Colab since Colab does not support IPv6.

</Admonition>

## Stepping through the notebook

Now all that's left is to step through the notebook. You can do this by clicking the "execute" button (`ctrl+enter`) at the top left of each code cell. The notebook guides you through the process of creating a collection, adding data to it, and querying it.

You can view the inserted items in the [Table Editor](/dashboard/project/_/editor/), by selecting the `vecs` schema from the schema dropdown.

![Colab documents](/docs/img/ai/google-colab/colab-documents.png)

## Next steps

You can now start building your own applications with Vecs. Check our [examples](/docs/guides/ai#examples) for ideas.
