Add local development hot-reloading for experiment reports

[myanvoos]

To my understanding, right now while an experiment is running locally with ./run-all-experiments.py, the results go in the results directory (or as specified by the user) whenever they're available. The results-report directory is only updated after we manually run python -m report.web -r results -o results-report. This means that currently there's no automatic refresh/update of the report while the experiment is still running locally.

It might be good to add a functionality that watches the results directory for any new finished experiment, then automatically updates results-report (or equivalent) and hot-reloads the HTTP server accordingly. So you can run the local HTTP server alongside experiments. Perhaps this can be triggered with a --watch flag on ./run_all_experiments.py or on python -m report.web -r results -o results-report.

Discussion much appreciated :) I'll have an experimental PR for demonstration up later this week.

[myanvoos]

A small note: There's a upload_report.sh script that runs as a subprocess of docker_run.sh that basically does a similar thing, but these scripts don't seem to be triggered in a basic local workflow like

./run_all_experiments.py \
    --model=<model-name> \
    --benchmarks-directory='./benchmark-sets/comparison'

[Karanjot786]

Hi @myanvoos, I'm very interested in working on this feature. I agree that having automatic hot-reloading of the experiment reports would greatly improve the local development workflow, especially when running experiments with ./run_all_experiments.py. My plan is to add a --watch flag (or similar) that watches the results and report directories and automatically updates the results-report along with hot-reloading the HTTP server.

Could you please assign this issue to me so I can start working on it? Thanks!

[Vinay152003]

Hi everyone,

I've submitted PR #869 which implements the hot-reloading functionality for experiment reports. This PR introduces a new --watch flag to run_all_experiments.py that uses Python's watchdog library to monitor the results directory. When changes are detected, it automatically triggers an update of the results-report directory by running the report generation command.

Thank you for the discussion and feedback so far. I'm looking forward to your review and am happy to make further adjustments if needed!

[myanvoos]

Hi @Vinay152003 and @Karanjot786 ,

I think before working on this issue we should discuss with @DonggeLiu and @DavidKorczynski about whether this is worth doing or not first. I opened the issue for discussion only as I am not a maintainer of this repo and this is just an idea of mine. We should consider how the idea fits into the broader structure of the project before jumping ahead to implement it since it may lead to headaches for maintainers later on. Especially since as mentioned there's the upload_report.sh script that basically does the same thing but runs from docker_run.sh only.

[Karanjot786]

Hi @myanvoos,

I completely agree with your points. That’s exactly why I’m reaching out—to open a discussion with @DonggeLiu and @DavidKorczynski about how this idea might fit into the broader project structure. I want to ensure that if we move forward, it aligns well with the maintainers' vision and minimizes potential headaches.

[DonggeLiu]

Thanks @myanvoos for proposing this, @Vinay152003 for the PR, and @Karanjot786 for the discussion.
My thoughts:

1. This is indeed a low priority task, given we run most of our experiments online, which automatically run report.web every few minutes.
2. Would it be too often If we update the report every time the results directory changes? The report.web takes sometime to complete in large experiments.
3. If we are going to add this feature, I would prefer to separate it from run-all-experiments.py. E.g., Another script that we can manually start and keeps running in parallel. run-all-experiments.py already takes a lot of command line args and let's avoid overcomplicates it.

[Karanjot786]

Hi @DonggeLiu,

Thanks for the feedback. I agree that a separate, manually-triggered script for hot-reloading makes sense, especially to avoid overloading run-all-experiments.py. We could also consider throttling updates to manage load during large experiments.
Looking forward to your experimental PR!

[myanvoos]

Thanks @myanvoos for proposing this, @Vinay152003 for the PR, and @Karanjot786 for the discussion. My thoughts:

1. This is indeed a low priority task, given we run most of our experiments online, which automatically [run `report.web` every few minutes](https://github.com/google/oss-fuzz-gen/blob/main/report/upload_report.sh#L105).

2. Would it be too often If we update the report every time the results directory changes? The `report.web` takes sometime to complete in large experiments.

3. If we are going to add this feature, I would prefer to separate it from `run-all-experiments.py`. E.g., Another script that we can manually start and keeps running  in parallel. `run-all-experiments.py` already takes a lot of command line args and let's avoid overcomplicates it.

A separate process sounds good since this task is mainly targeting local development workflows and should be optional. I reckon we can have something like run-report-server.py that has the following command line args:

./run-report-server.py \ 
		-r <results-dir> \ 
		-o <output-dir> \ 
		[-p <port>] \ 
		[-i <interval-seconds>] \ 
		[-w | --watch-fs] \
		[-t | --watch-template]

where

# Generate reports once and serve them, no hot-reloading (default)
./run-report-server.py -r <results-dir> -o <output-dir> 

# Generate reports with time-based reloading (every 10 minutes to match with the cloud script) 
./run-report-server.py -r <results-dir> -o <output-dir> -i 600 

# Generate reports with filesystem watching (reload on changes) 
./run-report-server.py -r <results-dir> -o <output-dir> -w 

# Generate reports with both time and filesystem-based reloading 
./run-report-server.py -r <results-dir> -o <output-dir> -i 600 -w

# Generate reports with both time and filesystem-based reloading
# This watches the report/ folder too for development purposes
./run-report-server.py -r <results-dir> -o <output-dir> -i 600 -w -t

Edit: Or we can extend the existing command line argument parser in web.py instead

[DonggeLiu]

Yep, extending web.py sounds good.