Cilium install on Kind cluster not working

Is there an existing issue for this?

[X] I have searched the existing issues

What happened?
Following the guide : https://docs.cilium.io/en/stable/gettingstarted/k8s-install-default/
kind v0.20.0 go1.20.5 darwin/arm64
K8S v1.27.3
After cluster id deployed, i'm running
cilium install --version 1.14.5
The output says everyting is fine.
🔮 Auto-detected Kubernetes kind: kind
✨ Running "kind" validation checks
✅ Detected kind version "0.20.0"
ℹ  Using Cilium version 1.14.5
🔮 Auto-detected cluster name: kind-kind
🔮 Auto-detected kube-proxy has been installed
But the Cilium deamonsets never come up.
NAMESPACE            NAME                                         READY   STATUS             RESTARTS      AGE
kube-system          cilium-8cx2r                                 0/1     CrashLoopBackOff   2 (6s ago)    69s
kube-system          cilium-dvcml                                 0/1     CrashLoopBackOff   2 (15s ago)   69s
kube-system          cilium-jp7j8                                 0/1     CrashLoopBackOff   2 (16s ago)   69s
kube-system          cilium-lzpdh                                 0/1     CrashLoopBackOff   2 (6s ago)    69s
kube-system          cilium-operator-775cdf757-sjkq9              1/1     Running            0             69s
kube-system          coredns-5d78c9869d-pt5n2                     0/1     Pending            0             2m54s
kube-system          coredns-5d78c9869d-rvzls                     0/1     Pending            0             2m54s
kube-system          etcd-kind-control-plane                      1/1     Running            0             3m7s
kube-system          kube-apiserver-kind-control-plane            1/1     Running            0             3m7s
kube-system          kube-controller-manager-kind-control-plane   1/1     Running            0             3m7s
kube-system          kube-proxy-94626                             1/1     Running            0             2m47s
kube-system          kube-proxy-bh9d6                             1/1     Running            0             2m51s
kube-system          kube-proxy-jh8pm                             1/1     Running            0             2m54s
kube-system          kube-proxy-kpz6z                             1/1     Running            0             2m51s
kube-system          kube-scheduler-kind-control-plane            1/1     Running            0             3m8s
local-path-storage   local-path-provisioner-6bc4bddd6b-v8wdl      0/1     Pending            0             2m54s

The logs from one of the deamonsets says
│ level=info msg="Waiting until all pre-existing resources have been received" subsys=k8s-watcher                                                                             │
│ level=info msg="Initializing identity allocator" subsys=identity-cache                                                                                │
│ level=info msg="Allocating identities between range" cluster-id=0 max=65535 min=256 subsys=identity-cache                                                                   │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_host.forwarding sysParamValue=1                                                             │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_host.rp_filter sysParamValue=0                                                              │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_host.accept_local sysParamValue=1                                                           │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_host.send_redirects sysParamValue=0                                                         │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_net.forwarding sysParamValue=1                                                              │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_net.rp_filter sysParamValue=0                                                               │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_net.accept_local sysParamValue=1                                                            │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.cilium_net.send_redirects sysParamValue=0                                                          │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.core.bpf_jit_enable sysParamValue=1                                                                          │
│ level=warning msg="Unable to ensure that BPF JIT compilation is enabled. This can be ignored when Cilium is running inside non-host network namespace (e.g. with kind or mi │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.conf.all.rp_filter sysParamValue=0                                                                      │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=net.ipv4.fib_multipath_use_neigh sysParamValue=1                                                                 │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=kernel.unprivileged_bpf_disabled sysParamValue=1                                                                 │
│ level=info msg="Setting sysctl" subsys=sysctl sysParamName=kernel.timer_migration sysParamValue=0                                                                           │
│ level=info msg="Setting up BPF datapath" bpfClockSource=ktime bpfInsnSet="<nil>" subsys=datapath-loader                                                                     │
│ level=info msg="Re-pinning map with ':pending' suffix" bpfMapName=cilium_calls_overlay_2 bpfMapPath=/sys/fs/bpf/tc/globals/cilium_calls_overlay_2 subsys=bpf                │
│ level=info msg="Repinning without ':pending' suffix after failed migration" bpfMapName=cilium_calls_overlay_2 bpfMapPath=/sys/fs/bpf/tc/globals/cilium_calls_overlay_2 subs │
│ level=warning msg="Removed new pinned map after failed migration" bpfMapName=cilium_calls_overlay_2 bpfMapPath=/sys/fs/bpf/tc/globals/cilium_calls_overlay_2 subsys=bpf     │
│ level=fatal msg="Load overlay network failed" error="program cil_from_overlay: replacing clsact qdisc for interface cilium_vxlan: operation not supported" interface=cilium │
│ level=info msg="Node updated" clusterName=kind-kind nodeName=kind-worker subsys=nodemanager                                                                                │
│ level=info msg="Node updated" clusterName=kind-kind nodeName=kind-worker subsys=nodemanager                                                                                │
│ Stream closed EOF for kube-system/cilium-8cx2r (cilium-agent)

Cilium Version
1.14.5
Kernel Version
Darwin jensenrFJ6N6.vmware.com 23.2.0 Darwin Kernel Version 23.2.0: Wed Nov 15 21:53:18 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T6000 arm64
Kubernetes Version
v1.27.3
Sysdump
cilium-sysdump-20240116-141015.zip
Relevant log output
No response
Anything else?
No response
Code of Conduct

[X] I agree to follow this project's Code of Conduct

There is another issue reporting a similar error message: https://github.com/cilium/cilium/issues/30061
Looking at the kernel config in your sysdump, I don't see CONFIG_NET_CLS=y or CONFIG_NET_CLS_ACT=y. Perhaps you can load the sch_ingress module?

Thanks @squeed
Is that the --set ingressController.enabled=true in the CLI or how do i set that ?

No, this is a kernel module. This might be of help: https://docs.cilium.io/en/stable/operations/system_requirements/#ubuntu-22-04-on-raspberry-pi

Thanks @squeed it does. But i have no idea how to implement this on a M1 Macbook, running Docker desktop with Kind.
I run it as the guide on the website describes.

I solved this problem switching from Docker Desktop to colima as container runtime. It seems like an issue in Docker Desktop

@pparshin you are right. That solved it. Thanks

Closing since it seams to be a problems with docker desktop, and switching away from that, solves the problem.


Add an option to return a 406 response

More info: https://evertpot.com/http/406-not-acceptable

Hello,
I noticed that the browser edge does not send an accept-header when doing an OPTIONS-request. Postman or chrome does send the header { 'Accept': '/' } by default.
I use Slim Framework 4 like this:
$app->add((new Middlewares\ContentType(['html', 'json']))->errorResponse());
ContentType::detectFromHeader will not found a corresponding mime-type without the accept header.
I could add the accept-header before the the ContentType-middleware is called when dealing with a OPTIONS-request, but is this the way to handle this problem?
thanks for your effort!
Coen


question about the iou loss

Thanks for you great work!
I wanna ask is the iou loss not concerned when training?

no. we didn't optimize it during fine-tuning.

Hello, I would like to ask why IoU loss was not optimized in this study. What factors were considered?


[Fix] DRC-527 Support dbt version below 1.6

PR checklist

[x] Ensure you have added or ran the appropriate tests for your PR.
[x] DCO signed

What type of PR is this?
Bugfix
What this PR does / why we need it:
When dbt version is < 1.6, The PreviousState class only supports 2 arguments
Which issue(s) this PR fixes:
Special notes for your reviewer:
Does this PR introduce a user-facing change?:

Already fixed


New CLI based on Icicle.Runtime

This removes the old cli command and adds new version of icicle compile and icicle query which are based on the Icicle.Runtime evaluator.
The new commands are significantly simpler to operate, especially compile which has no dependency on the choice of snapshot / chord or what the output format is:
Usage: icicle compile [--max-queries-per-kernel QUERY_COUNT]
                      --input-toml DICTIONARY_TOML --output-c DICTIONARY_C
  Compile a dictionary to its C intermediate form.

Available options:
  --max-queries-per-kernel QUERY_COUNT
                           The maximum number of queries to include in each
                           compute kernel. (default: 100)
  --input-toml DICTIONARY_TOML
                           Path to a TOML dictionary to compile.
  --output-c DICTIONARY_C  Path to write the compiled C dictionary.

The query command grows support for writing out snapshots in zebra format, and also drops support for sparse/dense psv input, and sparse psv output:
Usage: icicle query --dictionary-c DICTIONARY_C --input-zebra INPUT_ZEBRA
                    (--output-zebra OUTPUT_ZEBRA | --output-psv OUTPUT_PSV
                    [--output-psv-schema OUTPUT_PSV_SCHEMA_JSON])
                    (--snapshot SNAPSHOT_DATE | --chord CHORD_DESCRIPTOR)
                    [--max-map-size QUERY_COUNT]
  Run an icicle query over some data.

Available options:
  --dictionary-c DICTIONARY_C
                           Path to a compiled C dictionary.
  --input-zebra INPUT_ZEBRA
                           Path to a zebra binary file.
  --output-zebra OUTPUT_ZEBRA
                           Path to write the zebra binary output file.
  --output-psv OUTPUT_PSV  Path to write the dense psv file.
  --output-psv-schema OUTPUT_PSV_SCHEMA_JSON
                           Location to write the output schema for a dense psv
                           output. (default: <output-path>.schema.json)
  --snapshot SNAPSHOT_DATE Run a snapshot on an inclusive date.
  --chord CHORD_DESCRIPTOR Path to a chord descriptor.
  --max-map-size QUERY_COUNT
                           The maximum allowed size of a map at
                           runtime. (default: 1048576)

I still need to write a test for this with the well typed generator, but there is a pretty decent test which checks that data roundtrips through the compute function correctly.
The chord functionality isn't done yet, I'll do that as a separate PR.
! @tranma @amosr

Chatted IRL, feel free to delete all PSV code. If we need to fix ice, we will copy PSV modules over to ice

Going to remove PSV in a separate PR


[WIP] [Do Not Merge] Adapt Test Suite for CI

Summary of changes:

Parameterized namespaces, instance names, cloud config etc.,
Converted the Yaml to Unstructured to facilitate the above.
Initialize few common things in test init.

To do:

Fix review comments

To do: (To be done after raising it e2e-tests against master)

Test it with Openshift CI / Prow.
Modify Makefile to make use of Build Env. used in Prow.

/ok-to-test

/test

/test

We might need to raise this against master to actually check run the tests. As I think the hook / app maybe configured to run tests for PRs only against master brancg

@deepak1725 +1 I think so too. I would be in favor of merging this to e2e-tests and opening a WIP PR of e2e-tests against master. This way we can push changes up to the shared branch and also get CI running against it. Thoughts?

@deepak1725 +1 I think so too. I would be in favor of merging this to e2e-tests and opening a WIP PR of e2e-tests against master. This way we can push changes up to the shared branch and also get CI running against it. Thoughts?

Hey @dymurray, you need to be careful while tagging.
Thanks

@deepakraj1997 ^. Sorry Deepak1725 :)


option customer attributes,

option customer attributes
i can i get the customer attributes values

Sorry, not clear what this issue is. Please use the issue templates.


Add clojure solution

Define three separate functions as predicates, then return the desired results by mapping it over the supplied range

thx!


Change the Result Tables to a TreeWidget

This work was originally designed to fix some bugs relating to the arrow key behavior, however I decided to scrap that work and the result tables in general. Instead, I rewrite the result tables into a single QTreeWidget.
This PR thus simplifies the arrow key behavior!
Closes #76

@ctrueden can you tell me what you think of this behavior?
Things I am aware of:

Pressing the down key after searching something will highlight the Commands line, not the first actual command or Op. I'd really prefer not to write our own logic to skip these, and I had trouble finding anything on the Qt side to skip these top level lines.

Codecov Report

Merging #80 (92995dc) into main (7d7ff85) will decrease coverage by 0.34%.
The diff coverage is 80.95%.

@@            Coverage Diff             @@
##             main      #80      +/-   ##
==========================================
- Coverage   93.26%   92.91%   -0.35%
==========================================
  Files          15       15
  Lines        2345     2329      -16
==========================================
- Hits         2187     2164      -23
- Misses        158      165       +7

Impacted Files
Coverage Δ

src/napari_imagej/widget.py
81.77% <76.69%> (-3.33%)
:arrow_down:

tests/test_ImageJWidget.py
98.98% <100.00%> (+0.64%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Looks great! Can just be cleaned up a bit

Resolved everything, ready to merge once the tests pass


Add WhisperNode Aura + Quasar endpoints

@gh0stdotexe please branch this off of my PR: https://github.com/cosmos/chain-registry/pull/1691


[<1.15] Blaze3D Does Not Yet Exist

I'm happy to create a pull request to fix this issue, but it seems it requires further discussion here after quickly being shut down by @BoogieMonster1O1 in https://github.com/Legacy-Fabric/yarn/issues/113. I have checked the existing threads and found that it hasn't been discussed before on Github.
The package com.mojang.blaze3d should not exist in (mainline) versions below 1.15.
Instead, these classes should be found somewhere under net.minecraft.client.
@MenschenToaster's suggestion was net.minecraft.client.gl.
This only affects a small number of versions for Fabric, but it affects every single version of Legacy Fabric. So I hope that we can come to a consensus.

I'm fine with this as long as you can proof Blaze3D wasn't in the works in 1.14.
Though keep in mind that:

If you open a PR, target 1.14.4 only, the other branches are not worth it
The focus of yarn is usually to map the latest release and latest snapshot, so such issues/PRs should not become a habit (imo)

proof Blaze3D wasn't in the works in 1.14

While versions before 1.15 did share many similarities with the Blaze3D engine, a version officially (partially) implementing it was not released until snapshot 19w34a was released.
And it was followed by many snapshots introducing minor changes to the implementation which seemed to cause new bugs with every update until Minecraft 1.15 was finally released.
I remember it fondly as snapshot reviews on YouTube pointed out just how bad it was during the process.

We cannot build/release versions for 1.14.4 anymore without quite a bit of effort to get it going again. Anything older than 1.14.4 I dont really care for much.
In 1.14.4 there are classes in in b3d package, https://github.com/FabricMC/yarn/blob/1.14.4/mappings/com/mojang/blaze3d/platform/GlStateManager.mapping#L1
This is a none issue as far as I can see, and idk why it would be an issue in the first place.


Add Quake III Arena

Desktop review looks good since I don't own the game. Change the update sources and it's good to go!


Rock paper scissor

PR Description 📜
Please include summary related to the issue you have fixed and describe your PR in brief over here by specifying the issue number on which you were working below
Fixes #11  <your_issue_number>

Mark the task you have completed ✅

[ ] I follow CONTRIBUTING GUIDELINE & CODE OF CONDUCT of this project.
[ ] I have performed a self-review of my own code or work.
[ ] I have commented my code, particularly in hard-to-understand areas.
[ ] My changes generates no new warnings.
[ ] I have followed proper naming convention showed in CONTRIBUTING GUIDELINE
[ ] I have added screenshot for website preview in assets/images
[ ] I have added entries for my game in main README.md
[ ] I have added README.md in my folder
[ ] I have added working video of the game in README.md (optional)
[ ] I have specified the respective issue number for which I have requested the new game.

Add your screenshots(Optional) 📸

Thank you soo much for contributing to our repository 💗

Thank you @Tusharjoshi1703 ,for creating the PR and contributing to our GameZone 💗
Review team will review the PR and will reach out to you soon! 😇
Make sure that you have marked all the tasks that you are done with ✅.
Thank you for your patience! 😀

please don't change anything except game entry in main README file !!!
make sure you add your code freshly in new branch and just add entry only in README !!!!

Thank you  @Tusharjoshi1703 , for your valuable time and contribution in our GameZone 💗.
It’s our GameZone, so Let’s build this GameZone altogether !!🤝
Hoping to see you soon with another PR again 😇
Wishing you all the best for your journey into Open Source🚀


package mcp23xxx - Fixing according datasheet

Notes
Please prefix the issue title with the primary package affected. For example, if
this PR fixes periph.io/x/periph/host/sysfs, prefix the PR title with "sysfs:".
Please add new drivers under "experimental". Wonder what it takes to promote a
driver as "stable"? See https://periph.io/project/#driver-lifetime-management
A stable driver requires the smallest API surface, good unit test code coverage,
good documentation and a page in
https://github.com/periph/website/tree/master/site/content/device so it can show
up at https://periph.io/device.
Mention the issue number it fixes or add the details of the changes if it
doesn't have a specific issue.
Examples:
Fixes #12345
Helps with #12345 but doesn't not completely fix it.

@googlebot I signed it!

Codecov Report

Merging #452 (7ca8b92) into master (d6dbb5a) will decrease coverage by 0.1%.
The diff coverage is n/a.

@@           Coverage Diff            @@
##           master    #452     +/-   ##
========================================
- Coverage    61.8%   61.7%   -0.1%
========================================
  Files         126     126
  Lines       11283   11283
========================================
- Hits         6973    6967      -6
- Misses       4079    4085      +6
  Partials      231     231

Impacted Files
Coverage Δ

...rc/periph.io/x/periph/host/sysfs/thermal_sensor.go
80.4% <0.0%> (-2.7%)
:arrow_down:

...o/x/periph/experimental/devices/mcp9808/mcp9808.go
98.4% <0.0%> (-1.6%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Hi! Thanks for the change. It seems the commit is associated with the user "jan". Can you confirm? That's why the CLA check fail. I'd recommend a git commit --amend then git push -f.
Agreed on the stable migration, I plan to redo all that for next version but sadly have made no progress in the past months.
Do you have a link to a datasheet? There's none in the current package documentation.

 :)

I looked at https://ww1.microchip.com/downloads/en/DeviceDoc/20001952C.pdf but failed to quickly spot the value, which page should I look at?

I looked at https://ww1.microchip.com/downloads/en/DeviceDoc/20001952C.pdf but failed to quickly spot the value, which page should I look at?

@maruel page 12, Table 3-1, and page 17 table 3-5 (bank select is zero on reset). This is an error in my original contribution, thanks @honzakadlec for catching it!

Pushed 19c7e6b260b10719669122fa72fcbd1194e2f0b4 to replace this, since the CLA check was failing. Thanks!


Stats like that of Anki

Hello,
Currently, the plugin does not track the past responses, so we can have the following stats:

Future due (the number of reviews due in the future - count per day)
Review intervals
Card ease

Adding the tracking, we can have:

Past review counts (& possibly a heatmap)
Response types

I hope these cover everything you want

Stats might be useful to help one tweak the algorithm options.


Removed doctoc tag

It's causing issues in our GH pages submodule setup.  Switching the page to use the same format as other notifiers.

The downside of this change is that it means the TOC will no longer be visible when viewing the readme inside GitHub. Are we ok with that?
As an alternative, maybe we could make all of the notifiers have the generated TOC in them (like this library did before this PR), and make whatever changes are needed so that it appears OK on rollbar.com/docs ?


vs code not detected c++ UE5

Describe the bug
title says it all
To Reproduce
Steps to reproduce the behavior:

install the flatpak
create new UE5 project
Go to create new c++ class
it says vs code is not installed, even though I gave UE5 full access to my file system

Hi, this is more issue with Unreal not detecting vscode in all places it should. All I can do from my side is add the ability to change the source code accessor to something your system does have, otherwise you can build your project for editor and open it normally using something like this:
<PATH TO UE4>/Engine/Build/BatchFiles/Linux/Build.sh Linux Development -Project=<PATH TO PROJECTS>/<ProjectName>/<ProjectName>.uproject -TargetType=Editor

After that the project should open as expected

Hi, this is more issue with Unreal not detecting vscode in all places it should. All I can do from my side is add the ability to change the source code accessor to something your system does have, otherwise you can build your project for editor and open it normally using something like this:
<PATH TO UE4>/Engine/Build/BatchFiles/Linux/Build.sh Linux Development -Project=<PATH TO PROJECTS>/<ProjectName>/<ProjectName>.uproject -TargetType=Editor

After that the project should open as expected

I can compile just fine with vs code, its just unreal engine can't detect it and so its not creating the c++ files I need.

Does it happen only when you launch through EAM? or even if you launch outside? I know there is a sandboxing issue with flatpak where it essentially launches the Engine inside the flatpak so it might have issues finding things. If it is the same outside EAM you can also generate the project files...
<PATH TO UE4>/GenerateProjectFiles.sh -Game <PATH TO PROJECTS>/<ProjectName>/<ProjectName>.uproject

Does it happen only when you launch through EAM? or even if you launch outside? I know there is a sandboxing issue with flatpak where it essentially launches the Engine inside the flatpak so it might have issues finding things. If it is the same outside EAM you can also generate the project files...
<PATH TO UE4>/GenerateProjectFiles.sh -Game <PATH TO PROJECTS>/<ProjectName>/<ProjectName>.uproject

lol it crashes if i run it outside of EAM

If you downloaded it through EAM it extracted it from the docker image and you do not need to have docker to run it. There might be an actual issue with the package as it was built. I will test it and see what is going on there.

seems like mangohud was causing the issue of it not launching without flatpak. (I have it globally enabled)


core/_form-group.scss does not import the govuk-form-group styles

lbh-frontend-react is going to require a FormGroup component in order to correctly group form controls. I was looking for the form group styling and I found a file inside core, but it does not import the core govuk-form-group styles inside it. I'm assuming this may be because the styles can be imported from the components where form-group is being used.
I would need both this file and the govuk file seperately imported. The ideal would be to import the lbh-frontend form-group and have that import the govuk-frontend styles.

PR opened with changes

I've merged the PR, will go in with the next release.

When are you planning on releasing the next version? We have a PR waiting for this on lbh-frontend-react.

@erbridge I've just released v1.5 which contains this change.

Great. Thanks!


Add Vibe

By submitting this pull request, I promise I have read the contribution guidelines twice and made sure my submission follows it.
⬆⬆⬆⬆⬆⬆⬆⬆⬆⬆

Right now, it looks more like a website than an actual app. I recommend making it look like a proper app.

@sindresorhus
Thanks for the input. The GitHub repo is live, and the link I added is to the repo itself with downloads available in the first section of the README. It's interesting that you see it more as a website rather than an app; could you elaborate? If there are other reasons for holding off on merging, I'm all ears.

@sindresorhus
I've updated the app and the website. Does it make sense now? If not, please let me know. If you don't see any chance please close the pr. Thanks

I'm going to pass on this. Looking at the screenshots, it still looks like a website and not an app. A proper app has a toolbar, more balanced components placements, etc.


Problem with clap v4.5.4

Trying to build plrust 1.2.6 through 1.2.8 results in this error:
error: failed to compile `cargo-pgrx v0.11.4`, intermediate artifacts can be found at `/tmp/cargo-installpit9R4`.
To reuse those artifacts with a future compilation, set the environment variable `CARGO_TARGET_DIR` to that path.

Caused by:
package `clap v4.5.4` cannot be built because it requires rustc 1.74 or newer, while the currently active rustc version is 1.72.0

I wonder if anybody ran into this yet?

What’s the command that caused this error?

I am extracting from my (previously working) Dockerfile:
cd plrust/plrust && cargo install cargo-pgrx --locked

You'd need to install the exact version of cargo-pgrx that plrust uses.
What we end up doing in CI, which runs nightly (and works) is:
$ cargo install cargo-pgrx --version 0.11.0 --locked

How's that work for you?
We have it on our radar to update plrust & postgrestd to the latest rust version, but aren't quite ready to do that yet.

Thank you, this [worked[(https://github.com/omnigres/omnigres/pull/571)!

If you can pluck the version out of plrust/Cargo.toml, that might future-proof you, depending on how you do configure your docker images.  This is what we do in CI for all our pgrx-based projects.
(Probably the thing I dislike most about the crates.io ecosystem is this exact problem -- crates tend to bitrot when combined with cargo's semver rules and such.  I dunno if we're doing something wrong with our dependencies or if upstream crates don't exactly follow semver or what.)


ci: removed installation unnecessary apt dependencies

Turns out the step didn't run (the startsWith(os.runner, 'ubuntu') should have been startsWith(os.runner, 'linux')), but since things work fine without it we might as well drop it altogether.
Edit: I also added a CI badge to the README.

I was taking a look at this PR, and tried to do a fresh install of eeg-notebooks
Some packages might actually be necessary to run. Notice that the test github action does not actually run any tests. pip install -e . works fine on my system, but eegnb runexp does not.
So, the current PR is 'fine' in it's current form.
The real problem isn't the unnecessary apt dependencies, it's the lack of an initial test that might identify installation issues.
I am trying to install eeg-notebooks on a fresh ubuntu 20.04 image and am having issues that seem related to psychopy.
Based on the psychopy documentation for installing linux, it looks like there are at least two manual steps required for this to work on:

install wxPython
install a few debian packages

ref: https://www.psychopy.org/download.html#linux
Debugging Info Below
The initial error I am receiving is:
(venv) ➜  eeg-notebooks git:(master) ✗ eegnb run_notebooks.py
Traceback (most recent call last):
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/bin/eegnb", line 6, in <module>
    from pkg_resources import load_entry_point
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/lib/python3.8/site-packages/pkg_resources/__init__.py", line 3252, in <module>
    def _initialize_master_working_set():
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/lib/python3.8/site-packages/pkg_resources/__init__.py", line 3235, in _call_aside
    f(*args, **kwargs)
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/lib/python3.8/site-packages/pkg_resources/__init__.py", line 3264, in _initialize_master_working_set
    working_set = WorkingSet._build_master()
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/lib/python3.8/site-packages/pkg_resources/__init__.py", line 583, in _build_master
    ws.require(__requires__)
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/lib/python3.8/site-packages/pkg_resources/__init__.py", line 900, in require
    needed = self.resolve(parse_requirements(requirements))
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/lib/python3.8/site-packages/pkg_resources/__init__.py", line 786, in resolve
    raise DistributionNotFound(req, requirers)
pkg_resources.DistributionNotFound: The 'cryptography>=1.3.4; extra == "security"' distribution was not found and is required by requests

If I install additional packages with pip install -r requirements.txt it installs two additional packages:
Installing collected packages: cryptography, pyOpenSSL
Successfully installed cryptography-3.2.1 pyOpenSSL-20.0.0

Then the following error:
(venv) ➜  eeg-notebooks git:(master) ✗ eegnb runexp
Traceback (most recent call last):
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/bin/eegnb", line 11, in <module>
    load_entry_point('eeg-notebooks', 'console_scripts', 'eegnb')()
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/__main__.py", line 73, in main
    cli = CLI(args.command)
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/cli.py", line 9, in __init__
    getattr(self, command)()
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/cli.py", line 41, in runexp
    from .utils import run_experiment
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/utils.py", line 5, in <module>
    from eegnb.experiments.auditory_oddball import auditoryaMMN
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/experiments/auditory_oddball/auditoryaMMN.py", line 9, in <module>
    from psychopy import visual, core, event, sound
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/lib/python3.8/site-packages/psychopy/sound/__init__.py", line 99, in <module>
    raise exceptions.DependencyError(
psychopy.exceptions.DependencyError: No sound libs could be loaded. Tried: ['sounddevice', 'PTB', 'pyo', 'pygame']
Check whether the necessary sound libs are installed
0.9089  WARNING         sounddevice audio lib was requested but not loaded: sounddevice not working
0.9103  WARNING         PTB audio lib was requested but not loaded: psychtoolbox audio failed to import
0.9108  WARNING         pyo audio lib was requested but not loaded: ModuleNotFoundError("No module named 'pyo'")
0.9112  WARNING         pygame audio lib was requested but not loaded: ModuleNotFoundError("No module named 'pygame'")

I install pyo and pygame, but still receive an error
(venv) ➜  eeg-notebooks git:(master) ✗ eegnb runexp
pygame 2.0.0 (SDL 2.0.12, python 3.8.5)
Hello from the pygame community. https://www.pygame.org/contribute.html

WxPython is not found for the current python version.
Pyo will use a minimal GUI toolkit written with Tkinter (if available).
This toolkit has limited functionnalities and is no more
maintained or updated. If you want to use all of pyo's
GUI features, you should install WxPython, available here:
http://www.wxpython.org/

Traceback (most recent call last):
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/venv/bin/eegnb", line 11, in <module>
    load_entry_point('eeg-notebooks', 'console_scripts', 'eegnb')()
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/__main__.py", line 73, in main
    cli = CLI(args.command)
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/cli.py", line 9, in __init__
    getattr(self, command)()
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/cli.py", line 41, in runexp
    from .utils import run_experiment
  File "/home/jnaulty/github.com/neurotechx/eeg-notebooks/eegnb/cli/utils.py", line 10, in <module>
    import h5py
ModuleNotFoundError: No module named 'h5py'
0.9997  WARNING         sounddevice audio lib was requested but not loaded: sounddevice not working
1.0008  WARNING         PTB audio lib was requested but not loaded: psychtoolbox audio failed to import
1.1016  WARNING         For experiments that use audio stimuli, timing will be much better if you upgrade your PsychoPy installation to a 64bit Python3 installation and use the PTB backend.

after installing that, we finally get to the wxpython error
(venv) ➜  eeg-notebooks git:(master) ✗ eegnb runexp
pygame 2.0.0 (SDL 2.0.12, python 3.8.5)
Hello from the pygame community. https://www.pygame.org/contribute.html

WxPython is not found for the current python version.
Pyo will use a minimal GUI toolkit written with Tkinter (if available).
This toolkit has limited functionnalities and is no more
maintained or updated. If you want to use all of pyo's
GUI features, you should install WxPython, available here:
http://www.wxpython.org/

0.9734  WARNING         sounddevice audio lib was requested but not loaded: sounddevice not working
0.9745  WARNING         PTB audio lib was requested but not loaded: psychtoolbox audio failed to import
1.0757  WARNING         For experiments that use audio stimuli, timing will be much better if you upgrade your PsychoPy installation to a 64bit Python3 installation and use the PTB backend.

dang.

installing wxPython worked ;)
I had to install gtk3: sudo apt install libgtk-3-dev
Then reinstalled wxPython: pip install --no-cache wxPython (this took about ~15 minutes on my computer to recompile everything with the gtk3 bindings).

Closing because #54 is in a state to merge and resolves issues related to building + testing eeg-notebooks on linux

@jnaulty Good call, and nice work on #54!
I cherry-picked 2cc53f7 directly onto master.


Example of increased strictness on linting

This increases prospector base profile to medium strictness, enables pep257,
and adds some additional pylint rules to filter out docstring related failures.
This limits docstrings to methods/classes less than 10 lines, which should be
readable already. Docstrings wouldn't hurt in this case of course, but we won't
require them on everything.

Only 1072 errors, :cake:

Down to 983 failures with more lenient rules around docstring required construct length. This number is inflated as it includes the fixes to projects/ in #1580, which would bring this down to ~800 failures.

Looks like this is mostly up to date with where we are currently. I've repushed it w/ a merge from master, to see where we are :)

There are a couple of new additions that we should target here -- a recent PEP now specifies that class should not have a space between class definition in docstring, conflicting with an older PEP that states otherwise.
I've been using this profile locally, by overriding the default with my vim settings. That's a great way to work on this incrementally until we're ready to take more chunks off.

Adding a few exceptions and turning pep257 off gets us down to ~200 mostly
valid errors (unused imports & arguments, etc)
On Fri, Jan 15, 2016 at 11:36 AM, Anthony<EMAIL_ADDRESS>wrote:

There are a couple of new additions that we should target here -- a recent
PEP now specifies that class should not have a space between class
definition in docstring, conflicting with an older PEP that states
otherwise.
I've been using this profile locally, by overriding the default with my
vim settings. That's a great way to work on this incrementally until we're
ready to take more chunks off.
—
Reply to this email directly or view it on GitHub
https://github.com/rtfd/readthedocs.org/pull/1581#issuecomment-172062948
.

--
Eric Holscher
Maker of the internet residing in Portland, Oregon
http://ericholscher.com

Would be worth trying to get this up to medium, at least for the unused import checks -- I generally delete them when I find them, but would be good to have in CI.

I'd rather keep pep257 and attack this incrementally, pep257 has useful requirements.
A better option is to add the pylint options to the prospector config manually, starting with missing imports.

Okay, I'm making this a thing. I've added a secondary file and a secondary pass to prospector. The secondary pass uses path exclusion, so we can slowly bring in paths during cleanup.

@agjohnson this ready to merge?


[Add][Doc] Goose book skeleton

Close issue #316
What?
One element of issue #306.
Why?
We require source files to build before adding a GitHub
workflow to deploy the book.
How?
We add Markdown skeleton files per the mdbook requirements.
Signed-off-by: Begley Brothers Inc<EMAIL_ADDRESS>

Superseded by #325 which includes the book skeleton. Closing as duplicate.


Client Definitions based on free algebras - Unary Services

This PR solves partially the issue https://github.com/frees-io/freestyle-rpc/issues/11 .
It brings some free algebras on top of Grpc for RPC clients. Concretely, it solves:

Channel Configuration.
Channel Algebra to be able to create new RPC calls, based on method descriptors and some call options.
ClientCalls Algebra to perform the different types of calls (unary, client streaming, server streaming and bidirecctional).

It also updates the demo code to use these algebras, composing RPC services as freestyle modules:
@module
trait ClientAPP {
  val greetingClientM: GreetingClientM
  val echoClientM: EchoClientM
}

object GreetingClientApp {

  val messageRequest = MessageRequest("Freestyle")
  val echoRequest    = EchoRequest("echo...")

  def unaryDemo[F[_]](implicit APP: ClientAPP[F]): FreeS[F, (String, String, String)] = {

    val greetingClientM: GreetingClientM[F] = APP.greetingClientM
    val echoClientM: EchoClientM[F]         = APP.echoClientM

    val defaultOptions = CallOptions.DEFAULT

    for {
      hi   <- greetingClientM.sayHello(messageRequest, defaultOptions)
      bye  <- greetingClientM.sayGoodbye(messageRequest, defaultOptions)
      echo <- echoClientM.echo(echoRequest, defaultOptions)
    } yield {
      println(s"Received -> (${hi.message}, ${bye.message}, ${echo.message})")
      (hi.message, bye.message, echo.message)
    }
  }

  def runProgram[F[_]](implicit M: Monad[F]) = {

    Await.result(unaryDemo[ClientAPP.Op].interpret[Future], Duration.Inf)
  }
}

Codecov Report

Merging #16 into master will not change coverage.
The diff coverage is 0%.

@@         Coverage Diff          @@
##           master   #16   +/-   ##
====================================
  Coverage       0%    0%
====================================
  Files          10    14    +4
  Lines         130   154   +24
  Branches        3     2    -1
====================================
- Misses        130   154   +24

Impacted Files
Coverage Δ

...ng/src/main/scala/greeting/GreetingServerApp.scala
0% <ø> (ø)
:arrow_up:

...eting/src/main/scala/greeting/GreetingClient.scala
0% <ø> (ø)
:arrow_up:

...ng/src/main/scala/greeting/GreetingClientApp.scala
0% <0%> (ø)
:arrow_up:

rpc/src/main/scala/client/implicits.scala
0% <0%> (ø)

...ng/src/main/scala/greeting/runtime/implicits.scala
0% <0%> (ø)
:arrow_up:

rpc/src/main/scala/client/package.scala
0% <0%> (ø)

...in/scala/client/handlers/ClientCallsMHandler.scala
0% <0%> (ø)

rpc/src/main/scala/server/implicits.scala
0% <0%> (ø)
:arrow_up:

...c/main/scala/client/handlers/ChannelMHandler.scala
0% <0%> (ø)

... and 3 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update f9b3fad...6faf553. Read the comment docs.


调用发消息接口后，emit 出的消息事件对应的消息时间不正确

Sorry, you did not follow the ISSUE Template, and there's not enough information about your problem.
In order to help us to find the problem out, and help other developers to search, you should provide all the detail information about the issue. Please make sure you are following the ISSUE Template, answer all the question, and the more important: provide the steps to reproduce the problem.
Also, please paste the full log instead of the log picture
I'll close this issue. Please re-submit a new issue to provide the information that needed.


New KeyError for B_RatedEnergy with 2.2.5-pre2

Describe the bug
After upgrading to 2.2.5-pre2, the following KeyError appears in my logs:
2022-10-10 07:36:35.065 ERROR (MainThread) [homeassistant.components.sensor] Error while setting up solaredge_modbus_multi platform for sensor
Traceback (most recent call last):
  File "/usr/src/homeassistant/homeassistant/helpers/entity_platform.py", line 289, in _async_setup_platform
    await asyncio.gather(*pending)
  File "/usr/src/homeassistant/homeassistant/helpers/entity_platform.py", line 428, in async_add_entities
    await asyncio.gather(*tasks)
  File "/usr/src/homeassistant/homeassistant/helpers/entity_platform.py", line 691, in _async_add_entity
    await entity.add_to_platform_finish()
  File "/usr/src/homeassistant/homeassistant/helpers/entity.py", line 777, in add_to_platform_finish
    self.async_write_ha_state()
  File "/usr/src/homeassistant/homeassistant/helpers/entity.py", line 533, in async_write_ha_state
    self._async_write_ha_state()
  File "/usr/src/homeassistant/homeassistant/helpers/entity.py", line 571, in _async_write_ha_state
    state = self._stringify_state(available)
  File "/usr/src/homeassistant/homeassistant/helpers/entity.py", line 539, in _stringify_state
    if (state := self.state) is None:
  File "/usr/src/homeassistant/homeassistant/components/sensor/__init__.py", line 404, in state
    value = self.native_value
  File "/config/custom_components/solaredge_modbus_multi/sensor.py", line 1760, in native_value
    > self._platform.decoded_model["B_RatedEnergy"]
KeyError: 'B_RatedEnergy'

This is most likely happening because my battery got fully drained overnight and is currently showing 0% in the app for available energy.
I can grab logs if necessary, but I suspect it's just a case of checking for the existence of the key in decoded_model before creating the sensor.

Thanks, I made a mistake: B_RatedEnergy is not in decoded_model, it's in decoded_common

Fixed in PR #128 and will make a new pre-release.


mj-spacer creates odd whitespace in email client preview

Describe the bug
The mj-spacer module produces white space on email preview on mail app (mac). Every  with a height or padding parameter, regardless of the position in the DOM produces a whitespace step on the message preview panel.
Please see the screenshot below
To Reproduce
Steps to reproduce the behavior:

Create a file with this MJML code: <mjml>...</mjml>
Add some
Send the HTML to an email address from within the mjml app
See error

Expected behavior
Whitespace is prepended to the message preview.
MJML environment:

OS: MacOS
MJML Version v3.0.4
MJML App v^4.12.0

Email sending environment:

mailjet

Affected email clients (for rendering issues):

Email Client: Apple Mail
OS: Mac

Screenshots

Additional context
The more mj-spacer you add the bigger the whitespace. Regardless of the height or padding value of the mj-spacer, the space that is prepended remains the same … it seems like an odd empty character. Also I figured that self-closing or css-class or mj-class references make no difference.

Yeah mj-spacer has a non visible character to ensure it get displayed on some clients. Just use padding if it bother you.

I figured that mj-preview in the head handles the mail app problem!
Maybe some documentation on the mj-spacer section would do the trick.


tests: increase fudge factors

Description of change
Make some tests less likely to fail.
Maybe we should just drop these tests.
But let's see if we can make them less flaky.

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 74.81%. Comparing base (f520399) to head (08e8f9e).

Additional details and impacted files
@@           Coverage Diff           @@
##             main      #88   +/-   ##
=======================================
  Coverage   74.81%   74.81%
=======================================
  Files         132      132
  Lines       34367    34367
=======================================
  Hits        25710    25710
  Misses       8657     8657

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

You can't guarantee that a blocking operation with a timeout will not take more than timeout+delta, unless you have an RTOS and you are not using python. If you rely on the fact that this timeouts will return "on time" you already have a bug in your code.
In fact, I'm not sure it makes any sense at all to check how much time passed in those tests, but if this commit fixes the flaky tests we can leave them.
If they fail again, I'll just drop them completely.
The actual amount of time that those operation take is completely outside of our control and influenced by stuff (i.e. other processes running on the machine) that have nothing to do with valkey-py.


Change k6 dependency to v0.45.1

A transitive dependency was removed. v0.45.0 was patched to address the issue. See grafana/k6#3252.

Codecov Report

Merging #5 (1c60d27) into master (1b48d1d) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master       #5   +/-   ##
=======================================
  Coverage   83.87%   83.87%
=======================================
  Files           4        4
  Lines         217      217
=======================================
  Hits          182      182
  Misses         24       24
  Partials       11       11


Resource requests for runner pods

Is there a way to configure resource requests/limits for runner Pod? Looking at CRD spec (runnerPodTemplate section), I only found resources section for initContainers, and couldn't figure out how to set it for the main container. If there's currently no way, consider this a feature request.

@chanwit is there any workaround for that problem? It's a bit problematic to guaranty CPU and RAM for the runners which leads into frozen pods in some cases. I was thinking about https://github.com/redhat-cop/patch-operator as last resort ...

Will prioritize this feature to make sure it's included in v0.15.0.
Thank you for the ping @odise.

@odise As a workaround, we do use limit ranges that force resource requests upon all pods that don't have them in the namespace. You can also use any mutating admission controller (e.g. kyverno). However, these are all just that - workarounds - and they introduce more moving parts. A native support would be much better.

Will prioritize this feature to make sure it's included in v0.15.0.
Thank you for the ping @odise.

Can I know when this issue will be resolved?

ouch. sorry that this work slipped thru the cracks, @creatorKoo @odise
I put this on the board.

Relates to https://github.com/weaveworks/tf-controller/issues/786.

@luizbafilho have we implemented this?


"Get it on string" in badges page

The "Get it on" string on badge pages looks good in English.

Unfortunately, it's a split sentence.
Do not translate it literally. Keep it as short as possible. It should be a call to action. It's always followed by "Flathub", so for example, "Get it on Flathub".
As you guessed, it's problematic in non-SVO languages like Turkish (an SOV language).

A proper translation might be a sentence similar to the following:
"Flathub'dan
Edin"
"Flathub'dan
Al"
"Flathub
İle Kur"
/Reported by Berk Elyesa

Thanks for reporting, it's really broken for many SOV languages like Japanese, Turkish, Korean, Hindi... etc indeed.
I made a little page for a broader overview, hope it's helpful

Little ping @jimmac xP

FWIW I’m be interested in working on this once the details have been decided on properly.

I think weblate will warn/error if the source translation has special strings such as \n and your translation misses them. So that could work, but needs us to verify this. The easiest way would without breaking anything, would probably be creating that translation in addition to what we have and maybe create a copy of the api, that's using that translation.
If we've confirmed it's working, wait for / migrate translations and then remove the current implementation and replace it with the newer.


Uncancelable AsyncTask

I have a fix for this and will gladly submit a PR if you're interested in incorporating it into your library.
The current implementation doesn't allow for cancelling of the asynctask.  This causes unexpected behavior when used in a RecyclerView as the task may complete after the ViewHolder has been rebound to a different element.   It also is a potential cause of crashes if the task completes after the Activity has been destroyed (during screen orientation change, backgrounding the app, or simply dismissing the activity to navigate to another screen in the app).
My change would add a cancel() method to the public API of the TextCrawler as well as cancellation handling inside the for loops of the async tasks.

https://github.com/LeonardoCardoso/Android-Link-Preview/pull/18

Thanks, @theGnartist . Merged!

@aleedy  how to use it?


VALUE NOT DISPLAY

Hi, I have an issue with my solar and grid values not being displayed, even though the flow from the panel is active. Do you have a solution for this problem, and how can I resolve it? Thanks, everyone.

Hi, sorry to hear that. There seems to be a problem with the query, try turning on the "Table View", just above the plugin's viewport. This will show you the actual query output fields and their values. Then, attach the screenshot to your issue so that we could provide you with further assistance.

Closing due to inactivity or redundancy


Read me polish

[ ] We should mention that this is a plugin for flake8

[ ] Explain how to run it or add a link to flake8's documentation that shows how to run flake8 might be even better

[ ] List which error codes PAR001 etc. mean what and which examples trigger which code.

[ ] I'd recommend removing the neo4j logo as this is not exactly a neo4j product. However, it it probably worth mentioning that the project was developed in the first place to improve the code quality of several neo4j Python projects.


Using tesseract on MNIST returns an empty string

I want to recognise digits in MNIST. The scale of MNIST image is 28*28. I have the images in csv file, each row is an image. It is a flatten image (scale 784).
I tried this code but the string returned by Tesseract is empty.
import numpy as np
import matplotlib.pyplot as pt
import pandas as pd
data  = pd.read_csv("train.csv").to_numpy()
#training dataset
xtrain=data[0:7000, 1:]
train_label=data[0:7000, 0]
#testing data
xtest= data[7000:, 1:]
actual_label = data[7000:, 0]
d=xtest[10]
d.shape=(28,28)
pt.imshow(d, cmap='gray')
pt.show()
import pytesseract
from PIL import Image
im = Image.fromarray((d).astype(np.uint8))
pt.imshow(im)
import cv2
#Grayscale image
ret,img = cv2.threshold(np.array(im), 125, 255, cv2.THRESH_BINARY)
pt.imshow(img)
text = pytesseract.image_to_string(img)
print(text)
I tried also to capture the image and i tried to read it as a png, but still Tesseract gives an empty string.
How can i correct the code to get the digits from MNIS

First issue: tesseract was trained on rendered fonts. The MNIST dataset contains a large collection of handwritten single digits (0-9).
Second issue: tesseract was trained on text lines containing mostly words and not too many numbers.
Basically, you need to use images in the dataset to train a new model. I don't know the right parameters and how well it will work.

Thanks a lot for your answer!

Were you able to use tesseract and mnist dataset together? @amitdo @CommunicativeEngineer


Checkout specific branch during clone operation

This PR fixes https://github.com/microsoft/vscode/issues/161968

This changes the behaviour of ref. Now it only works for branch references, not commit IDs.


🔧 Android Build FAILED Task :app:compileDevelopmentDebugJavaWithJavac

How were you trying to build the app?
When I tried to run my app using yarn android. Its fails.
Full build logs

> Task :app:compileDevelopmentDebugJavaWithJavac
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPluginPackage.java:19: error: cannot find symbol
    FrameProcessorPlugin.register(new VisionCameraCodeScannerPlugin());
                        ^
  symbol:   method register(VisionCameraCodeScannerPlugin)
  location: class FrameProcessorPlugin
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPlugin.java:40: error: VisionCameraCodeScannerPlugin is not abstract and does not override abstract method callback(Frame,Map<String,Object>) in FrameProcessorPlugin
public class VisionCameraCodeScannerPlugin extends FrameProcessorPlugin {
       ^
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPlugin.java:62: error: method does not override or implement a method from a supertype
  @Override
  ^
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPlugin.java:251: error: incompatible types: String cannot be converted to Map<String,Object>
    super("scanCodes");
          ^
Note: Some input files use or override a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
Note: Some messages have been simplified; recompile with -Xdiags:verbose to get full output
4 errors

Project dependencies
"react-native": "0.72.5",
"react-native-reanimated": "3.3.0",
 "react-native-vision-camera": "3.7.1",
 "react-native-worklets-core": "^0.2.0",

VisionCamera Version
3.7.1
Target platforms
Android
Operating system
MacOS
Can you build the VisionCamera Example app?
No, I cannot build the Example app either
Additional information

[ ] I am using Expo
[X] I have enabled Frame Processors (react-native-worklets-core)
[X] I have read the Troubleshooting Guide
[X] I agree to follow this project's Code of Conduct
[X] I searched for similar issues in this repository and found none.

Hey.
According to these error messages:
    FrameProcessorPlugin.register(new VisionCameraCodeScannerPlugin());
                        ^
  symbol:   method register(VisionCameraCodeScannerPlugin)
  location: class FrameProcessorPlugin
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPlugin.java:40: error: VisionCameraCodeScannerPlugin is not abstract and does not override abstract method callback(Frame,Map<String,Object>) in FrameProcessorPlugin
public class VisionCameraCodeScannerPlugin extends FrameProcessorPlugin {
       ^
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPlugin.java:62: error: method does not override or implement a method from a supertype
  @Override
  ^
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPlugin.java:251: error: incompatible types: String cannot be converted to Map<String,Object>
    super("scanCodes");
          ^

..I can assume that you are using a QR Code scanner plugin (which you did not mention here) and this fails to build. If you would remove the Code Scanner plugin, it would build.
So you should probably create the issue in the Code Scanner plugin, not in the main VisionCamera repo.

From this line specifically:
/Users/maheshbhusanoor/android/app/src/main/java/com/instore/visioncameracodescanner/VisionCameraCodeScannerPlugin.java:251: error: incompatible types: String cannot be converted to Map<String,Object>
    super("scanCodes");
          ^

I can see that the Code Scanner plugin is using an old API, this constructor doesn't exist like that anymore, that was V2. The plugin needs to be upgraded, see the documentation. But you also didn't mention anything about the plugin, so I cannot help you

Can you build the VisionCamera Example app?
No, I cannot build the Example app either

Did you really try to build the example app, or did you just pick that value so I don't ignore your issue?
The errors are code scanner plugin specific, so I doubt that the example app also fails to build.


Implement typing game skeleton using JavaFX

Changed tab command syntax from tab typinggame to tab game for convenience

Guide to launch the typing game

Type tab game in console
StartWindow appears
Click the Start button
Typing game launches in a new window
Play the game by typing to score points.
Once the game is over, GAME OVER appears.
Manually close the GameWindow to exit the game

Areas for improvements (in decreasing order of priority):

Improve CSS.
Implement unit testing.
There is a known bug that is it is possible to open multiple GameWindows which may result in performance issues. One way to solve it is to limit the user to 1 GameWindow at any given time.
Remove the need for user to open a new GameWindow. It would be good if the GameWindow fits in the MainWindow of Typee.
Improve user experience when the game is over.

😃 😃 😃

Fixes #80


⚠ Bofrost.at has degraded performance

In 0562fef, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 2121 ms

Resolved: Bofrost.at performance has improved in 1f62989 after 7 minutes.


update the readme with the latest help

Note that somewhere in the last few releases the options for --log.format changed (probably due to a previous module upgrade from prometheus, since that cli option comes from prometheus).
This fixes the documentation.
Before:
      --log.format="logger:stderr"
                          Set the log target and format. Example: "logger:syslog?appname=bob&local=7" or "logger:stdout?json=true"

Current:
      --log.format=logfmt  Output format of log messages. One of: [logfmt, json]

Thank you


Support tar archives created on macOS

On macOS, number fields end with a space instead of padding the front
with an extra 0 (this is noted in the tar.spec file on line 201). I've also switched mode to be parsed as an octal number instead of as a string to match the way the other number fields are parsed, and also because on macOS the mode string ends in a trailing space so it's easier to just parse as a number.
I've added a new tar to the simple example, created by extracting the test.tar and re-tarring it on macOS.

Thanks !


Fix method=POST when using principal attribute to initiate MFA flow

This fixes the bug in the principal attribute resolver code that was fixed for the request argument extractor code in Unicon/cas-mfa#121.

Closed this because it was merged in Unicon/cas-mfa@07c15a5ec26674ca471b5593924ec44adc367f47


Data Collection Client Access

Hello,
We are implementing an installation of Suma and have a question about the security of the Data Collection Client. It seems as though anyone can startup a new session and start collecting data if they know the right URL to go to. I'm not sure if this is a problem beyond possibly skewing the reported data. Is this something that we should be concerned about? Did anyone else do anything to secure their data collection client or have any recommendations about how it could be done?
Thanks.
Jonahlyn

Hi @jonahlyn did you happen to do address this? We are looking at doing the same, however we are looking at putting it behind Shibboleth to address this for our uses.


Can O' Spam: Watch caready.vn

Can O' Spam requests the watch of the watch_keyword caready\.vn. See the MS search here and the Stack Exchange search in text, in URLs, and in code.

caready\.vn has been seen in 1 true positive, 0 false positives, and 0 NAAs.

Approved by cigien in Charcoal HQ


Auth servers proper resolution

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Checklist:

[x] I have performed a self-review of my own code
[x] My changes generate no new warnings

Addresses #31


Fix CVE-2024-31584 in pytorch

Merge Checklist

All boxes should be checked before merging the PR (just tick any boxes which don't apply to this PR)

[x] The toolchain has been rebuilt successfully (or no changes were made to it)
[x] The toolchain/worker package manifests are up-to-date
[x] Any updated packages successfully build (or no packages were changed)
[x] Packages depending on static components modified in this PR (Golang, *-static subpackages, etc.) have had their Release tag incremented.
[x] Package tests (%check section) have been verified with RUN_CHECK=y for existing SPEC files, or added to new SPEC files
[x] All package sources are available
[x] cgmanifest files are up-to-date and sorted (./cgmanifest.json, ./toolkit/scripts/toolchain/cgmanifest.json, .github/workflows/cgmanifest.json)
[x] LICENSE-MAP files are up-to-date (./SPECS/LICENSES-AND-NOTICES/data/licenses.json, ./SPECS/LICENSES-AND-NOTICES/LICENSES-MAP.md, ./SPECS/LICENSES-AND-NOTICES/LICENSE-EXCEPTIONS.PHOTON)
[x] All source files have up-to-date hashes in the *.signatures.json files
[x] sudo make go-tidy-all and sudo make go-test-coverage pass
[x] Documentation has been updated to match any changes to the build system
[x] If you are adding/removing a .spec file that has multiple-versions supported, please add @microsoft/cbl-mariner-multi-package-reviewers team as reviewer (Eg. golang has 2 versions 1.18, 1.21+)
[x] Ready to merge

Summary

What does the PR accomplish, why was it needed?
Applying patch to fix CVE-2024-31584
Change Log

patch CVE-2024-31584

Does this affect the toolchain?

NO
Associated issues

#xxxx

Links to CVEs

https://nvd.nist.gov/vuln/detail/CVE-2024-31584

Test Methodology

Pipeline build id: https://dev.azure.com/mariner-org/mariner/_build/results?buildId=560281&view=results

Closing this PR since fix is merged to fasttrack in https://github.com/microsoft/azurelinux/pull/8962


Binary download on IPFS/IPNS?

Would it be nice to be able to fetch the beaker binary from fetch it from IPFS (or DAT, but I'm unfamiliar with it), next to the S3 option, utilising the automatic integrity checks?

Yes, that'd be a good idea.

S3 is too slow in some regions, so this is a good idea.

$ ipfs add beaker-browser-setup-0.7.11.exe
added Qme2ZBwZwBS4y3ENrMby4BusJy1JgDx8GHwpqhrSa9MXH7 beaker-browser-setup-0.7.11.exe

Just in case, do wait for someone trusted to confirm. :)


Make confix flexible

@cristianoc Can I ask your intention to sync? Is it what you're implementing?
// A.res
@@jsxConfig({version: 3})

@react.compoent
let make = () => body // 1

@@jsxConfig({version: 4})

@react.compoent
let make = () => body // 2

// B.res

@react.component
let make = () => body // 3

A.res, 1 -> V3
A.res, 2 -> V4
B.res, 3 -> by bsconfig.json

If it is your intention, then I have an idea without merging V3 and V4 into one. I prefer to separate it for the future maintaining.

Yes. Feel free to continue from where I have left.
As mentioned, there's really no fusion between V3 and V4. And it's easy to copy back to separate files later.

Ah! Finally, I figure your intention out. Thank you for your implementation, I'll look into it. I have an idea to implement your intention, I'll ping you once I've done it. Please check that out later. We can compare and mature the trade-off between implementations, then choose it.

I think if you continue from this PR it's better.
As we avoid tens of review back and forth later to clean things up.
The structure of the code has not changed really.

I assume your idea is not incompatible with the cleanup I have done.

I like what you've done in this PR. But, I have a little idea to implement your intention from my PR, I'll show you how it looks. Maybe if you don't like it, then it will be totally fine with me. We can keep developing the V4 from this PR. I think that showing the codes would be the best communication for this implementation.

I like what you've done in this PR. But, I have a little idea to implement your intention from my PR, I'll show you how it looks. Maybe if you don't like it, then it will be totally fine with me. We can keep developing the V4 from this PR. I think that showing the codes would be the best communication for this implementation.

Sure go for it.
Though merging to this later might take more time. Or maybe not. Let's see.

I guess your idea is you'll try to do 2 separate traversals, one for V3 and one for V4, and each one will transform only the things that are in V3/V4 current config. If that's the idea, let's see how it comes.

That won't work for inner modules.

I just made a commit of it https://github.com/rescript-lang/syntax/pull/586/commits/572a8c7dbfb9e0fc1251ea1e452363263cb89f64

I just made a commit of it 572a8c7

Yea it does not work for inner modules.

I think there is a test case of inner modules. Is it what you refer to? https://github.com/rescript-lang/syntax/blob/master/tests/ppx/react/innerModule.res

I think there is a test case of inner modules. Is it what you refer to? https://github.com/rescript-lang/syntax/blob/master/tests/ppx/react/innerModule.res

I mean switch between 3 and 4 inside an inner module.

I mean switch between 3 and 4 inside an inner module.

Wow, I didn't notice that @@jsxConfig can be used inside modules not top-level only.
@@jsxConfig({version: 4})

@react.component
let make = () => {
  @@jsxConfig({version: 3})
  <div> ... </div>
}

Is it what you mean switching inside the inner module?

Correct, my idea is not working for the inner module.

I think I didn't fully understand the spec of @@jsxConfig.

There are many details that can be easily missed. That's why I wanted to code directly to show the idea.

Agree!
Alright, we can move forward from this PR. I'm afraid I can't push directly this branch, can I?

Agree!
Alright, we can move forward from this PR. I'm afraid I can't push directly this branch, can I?

You can just copy the commits. Or I'll move them later to your branch when I'm back.

You can just copy the commits. Or I'll move them later to your branch when I'm back.

I'll cherry-pick your commits!

Incorporated already.


Asks for OPENAI_KEY when it's not needed

I'm playing around with Qdrant as a vector store index using sentence-transformer embeddings from HuggingFace.
However, when I try to create an index, I get an error message Did not find openai_api_key, please add an environment variable OPENAI_API_KEY which contains it, or pass  openai_api_key as a named parameter.. I'm not using any OpenAI API, so why is llama-index asking for the key?
model_name = "sentence-transformers/all-mpnet-base-v2"
embed_model_lang = LangchainEmbedding(HuggingFaceEmbeddings(model_name=model_name))
data = "hello world"
documents = embed_model_lang.get_text_embedding(data)
index = GPTQdrantIndex(documents, collection_name="test", client=client, embed_model=embed_model_lang)

@mjp0 if you have more questions beyond @logan-markewich's super helpful response, please join the discord community (https://discord.gg/dGcwcsnxhU) and continue the discussion there!

I'm playing around with Qdrant as a vector store index using sentence-transformer embeddings from HuggingFace.
However, when I try to create an index, I get an error message Did not find openai_api_key, please add an environment variable OPENAI_API_KEY which contains it, or pass openai_api_key as a named parameter.. I'm not using any OpenAI API, so why is llama-index asking for the key?
model_name = "sentence-transformers/all-mpnet-base-v2"
embed_model_lang = LangchainEmbedding(HuggingFaceEmbeddings(model_name=model_name))
data = "hello world"
documents = embed_model_lang.get_text_embedding(data)
index = GPTQdrantIndex(documents, collection_name="test", client=client, embed_model=embed_model_lang)

Can you share a example how to create embeddings with your documents WITHOUT openai api key?
Reading this repository have feeling that they work ONLY for openai ...

I'm playing around with Qdrant as a vector store index using sentence-transformer embeddings from HuggingFace.
However, when I try to create an index, I get an error message Did not find openai_api_key, please add an environment variable OPENAI_API_KEY which contains it, or pass openai_api_key as a named parameter.. I'm not using any OpenAI API, so why is llama-index asking for the key?
model_name = "sentence-transformers/all-mpnet-base-v2"
embed_model_lang = LangchainEmbedding(HuggingFaceEmbeddings(model_name=model_name))
data = "hello world"
documents = embed_model_lang.get_text_embedding(data)
index = GPTQdrantIndex(documents, collection_name="test", client=client, embed_model=embed_model_lang)

Can you share a example how to create embeddings with your documents WITHOUT openai api key?
Reading this repository have feeling that they work ONLY for openai ...
PS: Spuriously, the link about how to make custom LLM in the answer not works

There are two models, the embed model and the llm
You'll need to set both in the service context, and pass your service context into the index
https://colab.research.google.com/drive/16QMQePkONNlDpgiltOi7oRQgmB8dU5fl?usp=sharing

There are two models, the embed model and the llm
You'll need to set both in the service context, and pass your service context into the index
https://colab.research.google.com/drive/16QMQePkONNlDpgiltOi7oRQgmB8dU5fl?usp=sharing

Thank you for the answer, but the simple example is missing.
Am i wrong if conclude that embedding is private technology of OpenAI and there is no way to use on other LLMs?
I can't find a simple example of python script using embeddings WITHOUT to use OpenAI API.
The only one alternative is Extensible retrieval augmented system of OpenChatKit!, BUT it is in experimental stage

hf_predictor = HuggingFaceLLMPredictor(
    max_input_size=2048,
    max_new_tokens=256,
    temperature=0.25,
    do_sample=False,
    query_wrapper_prompt=query_wrapper_prompt,
    tokenizer_name="Writer/camel-5b-hf",
    model_name="Writer/camel-5b-hf",
    device_map="auto",
    tokenizer_kwargs={"max_length": 2048},
    model_kwargs={"torch_dtype": torch.bfloat16}
)

embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2"))

service_context = ServiceContext.from_defaults(chunk_size_limit=512, llm_predictor=hf_predictor, embed_model=embed_model)

This runs everything locally, on your machine, no openai

hf_predictor = HuggingFaceLLMPredictor(
    max_input_size=2048,
    max_new_tokens=256,
    temperature=0.25,
    do_sample=False,
    query_wrapper_prompt=query_wrapper_prompt,
    tokenizer_name="Writer/camel-5b-hf",
    model_name="Writer/camel-5b-hf",
    device_map="auto",
    tokenizer_kwargs={"max_length": 2048},
    model_kwargs={"torch_dtype": torch.bfloat16}
)

embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2"))

service_context = ServiceContext.from_defaults(chunk_size_limit=512, llm_predictor=hf_predictor, embed_model=embed_model)

This runs everything locally, on your machine, no openai

I put in text file your code and start "python yourcode.py" and receive a bunch of errors.
Can you be so kind to provide a simple example of local text python file, not colab or any remote service?
Here is my code:
import torch
from llama_index.llm_predictor import HuggingFaceLLMPredictor
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
from langchain.llms import GPT4All
from llama_index.node_parser.simple import SimpleNodeParser
from llama_index.langchain_helpers.text_splitter import TokenTextSplitter
from llama_index import (
GPTVectorStoreIndex,
LangchainEmbedding,
LLMPredictor,
ServiceContext,
StorageContext,
download_loader,
PromptHelper
)
from llama_index.prompts.prompts import SimpleInputPrompt
This will wrap the default prompts that are internal to llama-index
taken from https://huggingface.co/Writer/camel-5b-hf
query_wrapper_prompt = SimpleInputPrompt(
"Below is an instruction that describes a task. "
"Write a response that appropriately completes the request.\n\n"
"### Instruction:\n{query_str}\n\n### Response:"
)
NOTE: the first run of this will download/cache the weights, ~20GB
hf_predictor = HuggingFaceLLMPredictor(
max_input_size=2048,
max_new_tokens=256,
temperature=0.25,
do_sample=False,
query_wrapper_prompt=query_wrapper_prompt,
tokenizer_name="models/ggml-gpt4all-j-v1.3-groovy.bin",
model_name="models/ggml-gpt4all-j-v1.3-groovy.bin",
device_map="auto",
tokenizer_kwargs={"max_length": 2048},
model_kwargs={"torch_dtype": torch.bfloat16}
)
embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2"))
service_context = ServiceContext.from_defaults(chunk_size_limit=512, llm_predictor=hf_predictor, embed_model=embed_model)
index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
index.storage_context.persist(persist_dir="source_documents")
query_engine = index.as_query_engine(streaming=True, similarity_top_k=3, service_context=service_context)
response_stream = query_engine.query("What are the main climate risks to our Oceans?")
response_stream.print_response_stream()

hf_predictor = HuggingFaceLLMPredictor(
    max_input_size=2048,
    max_new_tokens=256,
    temperature=0.25,
    do_sample=False,
    query_wrapper_prompt=query_wrapper_prompt,
    tokenizer_name="Writer/camel-5b-hf",
    model_name="Writer/camel-5b-hf",
    device_map="auto",
    tokenizer_kwargs={"max_length": 2048},
    model_kwargs={"torch_dtype": torch.bfloat16}
)

embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2"))

service_context = ServiceContext.from_defaults(chunk_size_limit=512, llm_predictor=hf_predictor, embed_model=embed_model)

This runs everything locally, on your machine, no openai

I put in text file your code and start "python yourcode.py" and receive a bunch of errors.
Can you be so kind to provide a simple example of local text python file, not colab or any remote service?
Here is my code:
import torch
from llama_index.llm_predictor import HuggingFaceLLMPredictor
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
from langchain.llms import GPT4All
from llama_index.node_parser.simple import SimpleNodeParser
from llama_index.langchain_helpers.text_splitter import TokenTextSplitter
from llama_index import (
GPTVectorStoreIndex,
LangchainEmbedding,
LLMPredictor,
ServiceContext,
StorageContext,
download_loader,
PromptHelper
)
from llama_index.prompts.prompts import SimpleInputPrompt
query_wrapper_prompt = SimpleInputPrompt(
"Below is an instruction that describes a task. "
"Write a response that appropriately completes the request.\n\n"
"### Instruction:\n{query_str}\n\n### Response:"
)
max_input_size=2048,
max_new_tokens=256,
temperature=0.25,
do_sample=False,
query_wrapper_prompt=query_wrapper_prompt,
tokenizer_name="models/ggml-gpt4all-j-v1.3-groovy.bin",
model_name="models/ggml-gpt4all-j-v1.3-groovy.bin",
device_map="auto",
tokenizer_kwargs={"max_length": 2048},
model_kwargs={"torch_dtype": torch.bfloat16}
)
embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2"))
service_context = ServiceContext.from_defaults(chunk_size_limit=512, llm_predictor=hf_predictor, embed_model=embed_model)
index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
index.storage_context.persist(persist_dir="source_documents")
query_engine = index.as_query_engine(streaming=True, similarity_top_k=3, service_context=service_context)
response_stream = query_engine.query("What are the main climate risks to our Oceans?")
response_stream.print_response_stream()

Here is my refined, but still NOT working code with error "ImportError: cannot import name 'BaseOutputParser' from 'langchain.schema'":
import torch
from llama_index.prompts.prompts import SimpleInputPrompt
query_wrapper_prompt = SimpleInputPrompt(
"Below is an instruction that describes a task. "
"Write a response that appropriately completes the request.\n\n"
"### Instruction:\n{query_str}\n\n### Response:"
)
hf_predictor = HuggingFaceLLMPredictor(
max_input_size=2048,
max_new_tokens=512,
temperature=0.25,
do_sample=False,
query_wrapper_prompt=query_wrapper_prompt,
tokenizer_name="./models/ggml-gpt4all-j-v1.3-groovy.bin",
model_name="./models/ggml-gpt4all-j-v1.3-groovy.bin",
device_map="auto",
tokenizer_kwargs={"max_length": 2048},
# uncomment this if using CUDA to reduce memory usage
model_kwargs={"torch_dtype": torch.float16}
)
prompt_helper = PromptHelper(max_input_size=2048, num_output=512, max_chunk_overlap=50)
embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2"))
service_context = ServiceContext.from_defaults(chunk_size_limit=512, llm_predictor=hf_predictor, embed_model=embed_model)
index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
index.storage_context.persist(persist_dir="source_documents")
query_engine = index.as_query_engine(streaming=True, similarity_top_k=4, service_context=service_context)
response_stream = query_engine.query("What are the main climate risks to our Oceans?")
response_stream.print_response_stream()

can anyone comment if we can run everything in an offline where we have downloaded the models. So no need for a connectkion to huggingface.co

The colab notebook I linked uses local huggingface embeddings...

Your colab notebook example requires open_api key which is the opposite of the question ...

@AngelTs once again, of course you can use local models without openai
While this thread is pretty old now, here's a detailed example right from our docs, the updated usage for v0.7.9. Much of the LLM setup is specific to stable lm, you'll want to see the model card from huggingface for full setup details
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
from llama_index import LangchainEmbedding, ServiceContext

embed_model = LangchainEmbedding(
  HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
)

from llama_index.prompts import Prompt

system_prompt = """<|SYSTEM|># StableLM Tuned (Alpha version)
- StableLM is a helpful and harmless open-source AI language model developed by StabilityAI.
- StableLM is excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
- StableLM is more than just an information source, StableLM is also able to write poetry, short stories, and make jokes.
- StableLM will refuse to participate in anything that could harm a human.
"""

# This will wrap the default prompts that are internal to llama-index
query_wrapper_prompt = Prompt("<|USER|>{query_str}<|ASSISTANT|>")

import torch
from llama_index.llms import HuggingFaceLLM
llm = HuggingFaceLLM(
    context_window=4096,
    max_new_tokens=256,
    generate_kwargs={"temperature": 0.7, "do_sample": False},
    system_prompt=system_prompt,
    query_wrapper_prompt=query_wrapper_prompt,
    tokenizer_name="StabilityAI/stablelm-tuned-alpha-3b",
    model_name="StabilityAI/stablelm-tuned-alpha-3b",
    device_map="auto",
    stopping_ids=[50278, 50279, 50277, 1, 0],
    tokenizer_kwargs={"max_length": 4096},
    # uncomment this if using CUDA to reduce memory usage
    # model_kwargs={"torch_dtype": torch.float16}
)
service_context = ServiceContext.from_defaults(
    chunk_size=1024,
    llm=llm,
    embed_mode=embed_model
)

# set global settings
from llama_index import set_global_service_context
set_global_service_context(service_context)

https://gpt-index.readthedocs.io/en/latest/core_modules/model_modules/llms/usage_custom.html#example-using-a-huggingface-llm
https://gpt-index.readthedocs.io/en/latest/core_modules/model_modules/embeddings/usage_pattern.html#embedding-model-integrations
https://gpt-index.readthedocs.io/en/latest/core_modules/supporting_modules/service_context.html

can anyone comment if we can run everything in an offline where we have downloaded the models. So no need for a connection to huggingface.co

I just can say that for some reason guys here DO NOT WANT to provide a simple example WITHOT openaAI api key (maybe they are their contractors, or employees or whatever ...)
So if your goal is to achieve privacy, true privacy of your data, this is not the right place to seek TRUE answer!
(i asked them [polite] couple of times to proved a simple example without openai infrastructure and they offered me colab notebook EXACTLY for openai (see upper post). I will not sped time here any more ...

@AngelTs I just provided a clear example of using local models from huggingface... in any case, best of luck in your LLM journey

I am also getting the following error:
Traceback (most recent call last):
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/venv/lib/python3.11/site-packages/llama_index/core/embeddings/utils.py", line 59, in resolve_embed_model
    validate_openai_api_key(embed_model.api_key)
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/venv/lib/python3.11/site-packages/llama_index/embeddings/openai/utils.py", line 104, in validate_openai_api_key
    raise ValueError(MISSING_API_KEY_ERROR_MESSAGE)
ValueError: No API key found for OpenAI.
Please set either the OPENAI_API_KEY environment variable or openai.api_key prior to initialization.
API keys can be found or created at https://platform.openai.com/account/api-keys

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/app.py", line 78, in <module>
    index = VectorStoreIndex.from_documents(documents)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/venv/lib/python3.11/site-packages/llama_index/core/indices/base.py", line 145, in from_documents
    return cls(
           ^^^^
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/venv/lib/python3.11/site-packages/llama_index/core/indices/vector_store/base.py", line 71, in __init__
    else embed_model_from_settings_or_context(Settings, service_context)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/venv/lib/python3.11/site-packages/llama_index/core/settings.py", line 274, in embed_model_from_settings_or_context
    return settings.embed_model
           ^^^^^^^^^^^^^^^^^^^^
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/venv/lib/python3.11/site-packages/llama_index/core/settings.py", line 67, in embed_model
    self._embed_model = resolve_embed_model("default")
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ck/fugazi_tech/rag_projects/llama_banker/venv/lib/python3.11/site-packages/llama_index/core/embeddings/utils.py", line 66, in resolve_embed_model
    raise ValueError(
ValueError:
******
Could not load OpenAI embedding model. If you intended to use OpenAI, please check your OPENAI_API_KEY.
Original error:
No API key found for OpenAI.
Please set either the OPENAI_API_KEY environment variable or openai.api_key prior to initialization.
API keys can be found or created at https://platform.openai.com/account/api-keys

Consider using embed_model='local'.
Visit our documentation for more embedding options: https://docs.llamaindex.ai/en/stable/module_guides/models/embeddings.html#modules
******

Even though I am exclusively passing huggingfaceEmbedding in my code:
# Create embeddings instance explicitly with HuggingFaceEmbeddings
embed_model = LangchainEmbedding(HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2"))

llm = Bedrock(
    model_id=llamaModelId,
    model_kwargs={'max_gen_len': 2048, 'top_p': 0.5, 'temperature': 0.9}
)

service_context = ServiceContext.from_defaults(
    chunk_size=1024,
    llm=llm,
    embed_model=embed_model  # Use the globally set HuggingFaceEmbeddings
)

# Set the global service context
llama_index.global_service_context = service_context

Why is this the case, I couldnt find any resolution to this problem in any of the linked issues here. Could you please assist me in the right direction here @logan-markewich

Using the following solved the problem for me:
embed_model = LangchainEmbedding(SentenceTransformerEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2"))
instead of using this:
embed_model = LangchainEmbedding(HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2"))

bump


Use a json commit body to include queue metadata

As we were discussing here, it would be convenient to allow the queue to add metadata in the commit body. I think this was the final version:
Commit body
NewJobMessage:
{
  "name": "create-job",
  "metadata": {
     "version": 1,
  }
  "payload": "{\"previous_ref\": \"...\",\n     \"current_ref\": \"...\",\n     \"submodule\": \"...\",\n     \"submoudle_url\": \"...\",\n}"
}

StartJobMessage:
{
  "name": "begin-job",
  "metadata": {
     "version": 1,
     "job_number": 1,
     "job_commit": "0fdf0db843a2010702b7c8d2e446966e9302f40e",
  },
  "payload": ""
}

FinishJobMessage:
{
  "name": "finish-job",
  "metadata": {
     "version": 1,
     "job_number": 1,
     "job_commit": "0fdf0db843a2010702b7c8d2e446966e9302f40e",
  },
  "payload": ""
}

@da2ce7 @yeraydavidrodriguez please review this.

I would like to use and enforce a JSON SCHEMA: We could use https://github.com/ajv-validator/ajv for example.


Link the Docs Contributor and Style Guides

Link the Docs Contributor and Style Guides and tighten up the language for clarity and flow.

/kind/documentation

/kind documentation

/meow

/meow

/lgtm


added : performNoDeepMerging for contact_endpoints config statements

different "contact_endpoints" configurations (in the bundle m6web_cassandra.clients section) now override old ones, instead of being appended.

:+1:

May be add a specific test to verify that never happen again ?

:metal:


add comment and format values in correct branch

Description
Second try at adding a comment on the first line and formatting the values in the env.example file
Type of change
Please delete options that are not relevant.

[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Checklist:

[ ] My code follows the style guidelines of this project
[ ] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] My changes generate no new warnings

Correct! Great work!


Replace flakeheaven, pyupgrade, and isort with ruff

@edgarrmondragon has proven Ruff's value and suitability across several repositories within the Meltano GitHub org.
We should be able to use it to replace flakeheaven, pyupgrade, and isort within the Meltano repository. This should significantly reduce the amount of time it takes for our linters to run. Additionally this will increase the number of lint issues which can be auto-fixed, and will significantly reduce the number of dev dependencies we have.
Some of the Flake8/Flakeheaven lint plugins we use are not yet supported by Ruff:

flake8-broken-line, but Black handles this.
flake8-rst-docstrings, but we use Markdown docstrings.
flake8-string-format, but we primarily use f-strings instead of str.format. We use str.format in 4 places, and all of those should be switched to use f-strings instead (because they aren't using an str.format-exclusive features like unpacking an argument list into the format string).
flake8-typing-as-t. We may want to open an issue https://github.com/charliermarsh/ruff requesting support for this flake8 plugin. flake8-import-conventions is supported, but it doesn't affect from ... import ... style import statements, only import module as bad_alias.
wemake-python-styleguide. Personally I'm okay with losing the WPS lint rules. I find that they're just as likely to be detrimental to the quality of the code as they are to improve it. We have 452 noqa comments within this repository, and 344 of them are for WPS rules. Of the 136 disabled lint rules within pyproject.toml, 98 of them are WPS rules. There are definitely plenty of good rules we'd be losing, but the most important/impactful rules tend to find their way into other flake8 plugins and related tools.

We'll lose the Flakeheaven baseline (see https://github.com/charliermarsh/ruff/issues/1149), but Ruff can add noqa comments using the --add-noqa, so once we've switched over and addressed every new lint issue uncovered that we want to address, we can easily add a noqa comment to the remaining ones. This adds some visual noise compared to a baseline file, but has the benefit of being explicit about what rules are being ignored and where.
Ruff can also automatically remove unused noqa comments, which will make this transition easier since it saves us from having to go through 452 existing noqa comments to see which ones are no longer necessary :sweat_smile:
Ruff rule classes to enable:

[ ] "A",   # flake8-builtins
[ ] "ANN", # flake8-annotations
[ ] "ARG", # flake8-unused-arguments
[x] "B",   # flake8-bugbear: https://github.com/meltano/meltano/pull/7445
[x] "C4",  # flake8-comprehensions: https://github.com/meltano/meltano/pull/7444
[x] "COM", # flake8-commas: https://github.com/meltano/meltano/pull/7435
[ ] "D",   # pydocstyle/flake8-docstrings
[ ] "DTZ", # flake8-datetime: https://github.com/meltano/meltano/pull/8265
[x] "E",   # pycodestyle (error): https://github.com/meltano/meltano/pull/7401/
[ ] "EM",  # flake8-errmsg
[x] "F",   # pyflakes: https://github.com/meltano/meltano/pull/7401/
[ ] "FBT", # flake8-boolean-trap
[ ] "ICN", # flake8-import-conventions
[x] "I",   # isort: https://github.com/meltano/meltano/pull/7409
[ ] "INP", # flake8-no-pep420
[x] "ISC", # flake8-implicit-str-concat: https://github.com/meltano/meltano/pull/7434
[x] "N",   # pep8-naming: https://github.com/meltano/meltano/pull/8415
[ ] "PGH", # pygrep-hooks
[ ] "PIE", # flake8-pie
[x] "PT",  # flake8-pytest-style: https://github.com/meltano/meltano/pull/7473
[ ] "PTH", # flake8-use-pathlib
[ ] "Q",   # flake8-quotes
[ ] "RET", # flake8-return
[x] "RSE", # flake8-raise: https://github.com/meltano/meltano/pull/7446
[ ] "RUF", # Ruff-specific rules
[x] "SIM", # flake8-simplify: https://github.com/meltano/meltano/pull/7447
[ ] "T10", # flake8-debugger
[ ] "T20", # flake8-print
[x] "TCH", # flake8-type-checking: https://github.com/meltano/meltano/pull/8294
[x] "TID", # flake8-tidy-imports: https://github.com/meltano/meltano/pull/7493
[x] "UP",  # pyupgrade: https://github.com/meltano/meltano/pull/7413
[x] "W",   # pycodestyle (warning): https://github.com/meltano/meltano/pull/7401/
[ ] "YTT", # flake8-2020

Very excited to see this. And a great write-up, thank you!

Ruff can add noqa comments using the --add-noqa, so once we've switched over and addressed every new lint issue uncovered that we want to address, we can easily add a noqa comment to the remaining ones. This adds some visual noise compared to a baseline file, but has the benefit of being explicit about what rules are being ignored and where.

In theory at least, I actually this a lot. 👍 Especially combined with:

Ruff can also automatically remove unused noqa comments, which will make this transition easier since it saves us from having to go through 452 existing noqa comments to see which ones are no longer necessary 😅

@nkclemson has expressed interest in tackling the missing rules, so he might start opening PRs.


Average rating drift

It seems that the average mu values tend to inflate over many duels, i.e. the mu gained by the winner can be non-negligibly greater than the mu lost by the loser. Is this an expected phenomenon?
The effect seems to be subtle, but large enough to make me doubt that it's due to numerical precision issues. In some of my experiments, the average mu increased by about 5% (10k ratings, 100k duels).
If this is not intended behavior, I can share more details of course.

Ok, I read the paper a bit and it appears they make no attempt to stop rating inflation. It turns out that the drift is caused by this update rule which isn't symmetric:
let delta = (self.team_params[team_idx].sigma_sq / c) * (s - piq);


Roll Flutter Engine from 82de3347ccd7 to 458956228dad (13 revisions)

https://github.com/flutter/engine/compare/82de3347ccd7...458956228dad
2023-12-07<EMAIL_ADDRESS>Reverts "Update clang revision from 00396e6a1a0b7 to b3a9e8f7c0afb00." (flutter/engine#48802)
2023-12-07<EMAIL_ADDRESS>Update clang revision from 00396e6a1a0b7 to b3a9e8f7c0afb00. (flutter/engine#48705)
2023-12-07<EMAIL_ADDRESS>Roll Skia from c68e050e9198 to f49ec3e6c1b1 (1 revision) (flutter/engine#48790)
2023-12-07<EMAIL_ADDRESS>Roll Skia from af998f66ae73 to c68e050e9198 (1 revision) (flutter/engine#48788)
2023-12-07<EMAIL_ADDRESS>Reland "Replace use of Fontmgr::RefDefault with explicit creation calls" (flutter/engine#48764)
2023-12-07<EMAIL_ADDRESS>Roll Skia from 308f3d9bef2c to af998f66ae73 (1 revision) (flutter/engine#48784)
2023-12-07<EMAIL_ADDRESS>Roll Skia from 2b33ff5642c3 to 308f3d9bef2c (1 revision) (flutter/engine#48777)
2023-12-07<EMAIL_ADDRESS>Roll Dart SDK from 4b22e6430c20 to b6d5e010d2c5 (1 revision) (flutter/engine#48776)
2023-12-07<EMAIL_ADDRESS>Roll Skia from 0753f680c573 to 2b33ff5642c3 (1 revision) (flutter/engine#48772)
2023-12-07<EMAIL_ADDRESS>Roll Skia from 0f1822e9137a to 0753f680c573 (1 revision) (flutter/engine#48771)
2023-12-07<EMAIL_ADDRESS>Roll Skia from dbcf508d1dce to 0f1822e9137a (1 revision) (flutter/engine#48769)
2023-12-07<EMAIL_ADDRESS>Roll Dart SDK from be8a95b6717d to 4b22e6430c20 (1 revision) (flutter/engine#48768)
2023-12-07<EMAIL_ADDRESS>Roll Skia from 8ebf43ba1c09 to dbcf508d1dce (1 revision) (flutter/engine#48766)
If this roll has caused a breakage, revert this CL and stop the roller
using the controls here:
https://autoroll.skia.org/r/flutter-engine-flutter-autoroll
Please CC chinmaygarde@google.com,rmistry<EMAIL_ADDRESS>on the revert to ensure that a human
is aware of the problem.
To file a bug in Flutter: https://github.com/flutter/flutter/issues/new/choose
To report a problem with the AutoRoller itself, please file a bug:
https://issues.skia.org/issues/new?component=1389291&template=1850622
Documentation for the AutoRoller is here:
https://skia.googlesource.com/buildbot/+doc/main/autoroll/README.md

Commit queue failed; closing this roll.


[Help] Migration from cluster redis to keydb cluster

Hey everyone,

I have cluster-redis and one standalone keydb server can i use replicaof  command for migration and later on i make keydb-server as cluster mode ?
In KeyDB cluster, is it possible to setup multi-master in cross regions ?

Yes!

Yes!

multi-master what they have talked about in documentation is related to standalone keydb instances not cluster mode , correct me if I am wrong


Add sysinfo provider

This PR adds a sysinfo provider to apex-tux. Details on its requirements have been added to the README. It is not a default feature of the main crate, but can be added with --feature sysinfo, as it requires additional dependencies (namely libstatgrab and lm_sensors).
The module also has a variety of config options, which are documented in settings.toml.
Additionally, this PR moves the usb feature's requirement of apex-input/hotkeys into its own hotkeys feature so that hotkey binding can be entirely turned off (it causes panics when running as a non-interactive daemon).

I have added a commit that instead uses the sysinfo crate, it seems I missed this crate when looking at the others on crates.io.
While this crate does offer all the functionalities necessary (unlike some of the other existing crates), when compared to the earlier apex-sysinfo crate, it does not seem to be as efficient with CPU time. The libstatgrab version runs on my machine at around 0.6% utilization on average, while the sysinfo crate version sits around 2-3% utilization, using more CPU time over time. This is at the same polling interval, and both versions essentially poll the same amount of information, and have to do the same amount of filtering of sensors and net interfaces to retrieve the configured stats.
So, while the crate is more easily cross-platform, libstatgrab doesn't need the CPU as much, if that advantage is enough to justify bringing in the system dependency and the custom apex-sysinfo bindings crate.

Thank you for taking the time to benchmark the two ideas. I'm somewhat wary of adding an unsafe dependency to the code base which is why from a purely architectural & maintenance standpoint I'd like to outsource as much of the unsafe-ness as possible.
I'm currently on vacation and can't really compile / test these changes so I'd like to postpone them until I return.

Hi, I've finally managed to merge these changes as a part of #30. Thank you so much for your contribution!