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

# Self-hosted fair queueing with Reducto

> Fair queueing by user-id for on-premise deployment

### Fair queueing for Parse and Extract requests

To take advantage of fair queueing on an on-premise deployment of Reducto, you can simply make your existing requests to `/parse` and `/parse_async` as normal, but additionally pass the user-id via a header parameter on your HTTP request. The header parameter is `user-id`.

```python theme={null}
import requests

url = "https://platform.reducto.ai/parse"

payload = { "input": "https://utfs.io/f/140cc88f-6cff-4521-87fd-76ecc6532aef-es0zzc.pdf" }
headers = {
    "user-id": "my_unique_user_id",
    "Authorization": "Bearer <token>"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
```

### Filtering jobs by user-id

To filter jobs by the user-id you can add the user-id via a header parameter similar to how the requests are made above. When the user-id is excluded from the header, all jobs will be returned regardless of which user it is associated with.

Python example for querying jobs by user-id:

```python theme={null}
import requests

url = "https://platform.reducto.ai/jobs"

headers = {
    "user-id": "my_unique_user_id",
    "Authorization": "Bearer <token>"
}

response = requests.get(url, headers=headers)

print(response.json())
```