Queue upstream when loading apps via gr.Interface.load()

[apolinario]

If app A uses gr.Interface.load() to load an app B that contains a your_app.launch(enable_queue=True), the queue does not get respected when the app B is executed from the app A. So if there are 3 app A users, and all trigger app B at the same time, app B runs 3x in parallel, regardless if enable_queue was set to True on app B.

This implies in two things:

1. Any person can bypass the app B queue by using app A
2. The host machine of app B may OOM if multiple users are running it from app A, as no queue is in place

This can currently be mitigated by adding a enable_queue=True to app A however this two shortcomings:

1. app A developer has to have the goodwill to include the queuing function there (including using gr.Interface.load() privately via localhost - which can be an easy way to bypass any queue), if they don't, app B gets resource drained outside of their control
2. This makes app A inefficient. Suppose app A not only loads app B but also loads apps C and D with gr.Interface.load(). If enable_queue is on app A, now when you call apps B, C, D from it, they get into the same queue, even though each could have very different internal queues (this happens with MindsEye Lite)

Suggested solution:

• Add the app A users that are calling app B to the same queue as native app B users

If that gets implemented make sure to de-register from app B's queue the users that leave/give up on app A too, otherwise an infinite queue could arise

[apolinario]

@abidlabs, this may be important to include when bringing the ability to load 3.x spaces with gr.Interface.load()

[abidlabs]

Thanks for the catch and the heads up @apolinario! Will implement appropriately

[omerXfaruq]

We need to check if the loaded space is a queued space and create a ws connection from Backend.

[abidlabs]

Hi @apolinario, we are planning on making queuing on by default everywhere (#2215) -- and it already has been on by default on Spaces for quite some time.

I'm wondering whether that makes this issue redundant as it basically is the second approach that you've mentioned (App A will have queuing on by default, whether or not the developer has the good will to do this). The other point about efficiency is still there, but I wonder whether that could be remedied in a different way -- for example by having separate queues for different events.

[apolinario]

Imo it doesn't make this issue redundant. I really think the ideal solution to this issue is passing the queue information downstream and sharing the queue between the main application and the loaded application. I don't know if that is possible but I feel otherwise this still makes gr.Interface.load() kind of unusable on high-load/large queue applications

The reason why making queuing default everywhere mitigates a bit but doesn't solve the issue, is that now the two queues (from app A and app B) are independent. So this means that even with two queues, the users from app a still skip the queue of app b, and also it can OOM app b as - in case they don't communicate - a request can come in parallel and consume more requests than the machine supports.

[apolinario]

So for example, if I want to load the Stable Diffusion Spaces into another application "Stable Diffusion Captioner" (SDC) that first runs Stable Diffusion and then an image captioning model.

If "Stable Diffusion Captioner" doesn't share the queue with the Stable Diffusion Spaces, even if it has a queue on its own turned on by default, the SDC user will still skip everyone in the original Stable Diffusion queue when they execute the job - which is not great. But imo the worst part, if Stable Diffusion is executing a job at that moment (which is likely), it would get the request from SDC in parallel, and then it would OOM and die.

The ideal scenario is that SDC when requests from Stable Diffusion Spaces gets their request as the last one in the original app queue.