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

# Step 4: Partitioner API

> Configure the document partitioning service

Next, you'll need to set up the partitioner API. This will be used to partition documents into chunks for vectorization. More information can be found [here](https://github.com/agentset-ai/partition-api).

<Note>
  Make sure `REDIS_HOST`, `REDIS_PORT`, and `REDIS_PASSWORD` match the values in your
  Upstash Redis database created in [Step 2](/open-source/step-2-upstash).
</Note>

## Set up environment variables

Once you have the partitioner API running, set these environment variables in your `.env` file:

```TypeScript .env theme={null}
PARTITION_API_URL= // the URL of the partitioner API (e.g. https://example.modal.run/ingest)
PARTITION_API_KEY= // the API key for the partitioner API
```

## Next Steps

Once you've completed the Partitioner API setup, proceed to [Step 5: Supabase](/open-source/step-5-supabase) to set up your PostgreSQL database.