Gradlew genEclipseRuns Error. Why did this happen? - minecraft-forge

I'm fairly new to modding, soo can someone help?
Forge 1.17.1.1-37.0.103. Adoptium 16.0.2.7
Ran cmd Command: gradlew genEclipseRuns
My logs:
Could not resolve all files for configuration ':runtimeClasspathCopy'.
> Could not find net.minecraftforge:forge:1.17.1-37.0.103_mapped_official_1.17.1.
Searched in the following locations:
- file:/C:/Users/Classified/.gradle/caches/forge_gradle/bundeled_repo/net/minecraftforge/forge/1.17.1-37.0.103_mapped_official_1.17.1/forge-1.17.1-37.0.103_mapped_official_1.17.1.pom
- file:/C:/Users/Classified/.gradle/caches/forge_gradle/bundeled_repo/net/minecraftforge/forge/1.17.1-37.0.103_mapped_official_1.17.1/forge-1.17.1-37.0.103_mapped_official_1.17.1.jar
Required by:
project :
* Try:
Run with --stacktrace option to get the stack trace. Run with --info or --debug option to get more log output. Run with --scan to get full insights.
* Get more help at https://help.gradle.org
Deprecated Gradle features were used in this build, making it incompatible with Gradle 8.0.
You can use '--warning-mode all' to show the individual deprecation warnings and determine if they come from your own scripts or plugins.
See https://docs.gradle.org/7.2/userguide/command_line_interface.html#sec:command_line_warnings
Checked the location and did not find the folder bundeled_repo

I had the same problem. Install Gradle here and reinstall Adoptium, making sure to have the "set Java home path" option to Will Install On This Hard Drive. Run the build again and it should work!

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Build failed with 500, please run 'jupyter lab build' on the server for full output in Jupyter lab

I am trying to add an extension in the jupyter lab. I go to extensions tab and click "install" on the extension. After a few seconds i get a pop up saying Build failed with 500, please run 'jupyter lab build' on the server for full output
could anyone tell me how to resolve it or find the logs related to that error atleast.
Using terminal, try jupyter lab build, which will produce an output on your AppData\Local\Temp folder (if you are on Windows). The log file will give more info on what is causing the failure during the build.
I had the same issue and npm dependencies were the culprit. I have updated conda with conda update -n base -c defaults conda and and yarn with conda install yarn and it solved the issue for me.
Also try looking at this one Jupyter Labs: “RuntimeError: npm dependencies failed to install” When Building.
For me this was fixed by pinning down a lower version of nodejs.
conda install -c conda-forge 'nodejs<16.14' did the trick. My resolution steps:
Install an environment from scratch conda create -c conda-forge -n <your_env_name> 'python>=3.8,<3.11' 'jupyterlab>=3.10'
Then attempt a nodejs install for example conda install -c conda-forge 'nodejs<16.14'
Attempt to build with jupyter lab build in terminal.
It's currently May 2022. Please note versions change a lot and very fast, when you face this same issue :)
On the UI (User Interface) of Jupyter Lab you see
Build failed with 524, please run 'jupyter lab build' on the server for full output
You open a console and run
jupyter lab build
Which ends with
An error occurred.
RuntimeError: JupyterLab failed to build
See the log file for details: /tmp/jupyterlab-debug-2znox977.log
Inside the log you see
FATAL ERROR: Ineffective mark-compacts near heap limit Allocation failed - JavaScript heap out of memory
Run again
jupyter lab build --minimize=False
This completes successfully.
Explanation:
dev-build: This option controls whether a dev or a more streamlined production build is used. This option will default to
False (i.e., the production build) for most users. However, if you
have any labextensions installed from local files, this option will
instead default to True. Explicitly setting dev-build to False
will ensure that the production build is used in all circumstances.
minimize: This option controls whether your JS bundle is minified during the Webpack build, which helps to improve JupyterLab's overall
performance. However, the minifier plugin used by Webpack is very
memory intensive, so turning it off may help the build finish
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In my case, the VM (Virtual Machine) had 3.75GB RAM and before crashing it was using ~3GB (you can see with htop in another console/terminal [image below]).

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