Component loading fails in Next.js 14.2.

I don't know if it's a problem with this library or the changes in nextjs. We will update if there is any missing information.
To explain the error exactly, after the version of nextjs was updated to 14.2, an error occurred when trying to build an mdx poster that includes component rendering.
thank you

mdx-bundler version: ^10.0.2
node version: v20.11.0
npm version: 10.3.0, but i use pnpm 8.15.6

minpeter.xyz [main●] pnpm build

><EMAIL_ADDRESS>build /Users/minpeter/github.com/minpeter/minpeter.xyz
> next build

  ▲ Next.js 14.2.1

   Creating an optimized production build ...
 ✓ Compiled successfully
   Linting and checking validity of types  .. ⨯ ESLint: Invalid Options: - Unknown options: useEslintrc, extensions - 'extensions' has been removed.
 ✓ Linting and checking validity of types
 ✓ Collecting page data
   Generating static pages (51/55)  [=   ]TypeError: Cannot read properties of null (reading 'useState')
    at exports.useState (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/react@18.2.0/node_modules/react/cjs/react.production.min.js:25:394)
    at ne (eval at getMDXExport (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/mdx-bundler@10.0.2_esbuild@0.20.2/node_modules/mdx-bundler/dist/client.js:44:14), <anonymous>:3:25369)
    at nj (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:46251)
    at nM (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:47571)
    at nN (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:64546)
    at nB (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:67538)
    at nD (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:66680)
    at nN (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:64853)
    at nM (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:59102)
    at nN (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:64546) {
  digest: '2592952107'
}

Error occurred prerendering page "/blog/mdx-blog-test". Read more: https://nextjs.org/docs/messages/prerender-error

TypeError: Cannot read properties of null (reading 'useState')
    at exports.useState (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/react@18.2.0/node_modules/react/cjs/react.production.min.js:25:394)
    at ne (eval at getMDXExport (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/mdx-bundler@10.0.2_esbuild@0.20.2/node_modules/mdx-bundler/dist/client.js:44:14), <anonymous>:3:25369)
    at nj (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:46251)
    at nM (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:47571)
    at nN (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:64546)
    at nB (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:67538)
    at nD (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:66680)
    at nN (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:64853)
    at nM (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:59102)
    at nN (/Users/minpeter/github.com/minpeter/minpeter.xyz/node_modules/.pnpm/next@14.2.1_react-dom@18.2.0_react@18.2.0/node_modules/next/dist/compiled/next-server/app-page.runtime.prod.js:12:64546)
 ✓ Generating static pages (55/55)

> Export encountered errors on following paths:
        /blog/[slug]/page: /blog/mdx-blog-test
 ELIFECYCLE  Command failed with exit code 1.

What you did: All dependencies were upgraded to the latest using pnpm upgrade --latest. It was built later.
What happened: The build was not successful. This was the same even after changing the eslint version to ^8.0.0.

Reproduction repository: https://github.com/minpeter/minpeter.xyz content/2023-11-21-mdx 블로그 컴포넌트 실험/mdx-blog-test.mdx post file

I am getting the exact same error since 14.2.
When I import components into my MDX file that use useState things break.
Warning: Invalid hook call. Hooks can only be called inside of the body of a function component. This could happen for one of the following reasons:
1. You might have mismatching versions of React and the renderer (such as React DOM)
2. You might be breaking the Rules of Hooks
3. You might have more than one copy of React in the same app
See https://reactjs.org/link/invalid-hook-call for tips about how to debug and fix this problem.
 ⨯ Internal error: TypeError: Cannot read properties of null (reading 'useState')

Are there any news on this?
Have you been able to solve this @minpeter?

No one paid any attention.
In my case, I am staying on next.js 14.1.4

There is a new update on this issue.
This does not cause all Mdx elements to fail; it only occurs for components imported using an import statement inside a .mdx file.
To use the latest Next.js and Mdx-bundler together, the problem is solved by using a temporarily globally created Mdx.
However, improvements are needed because the import function still fundamentally does not work.
| fyi: ModCodeBlock and Callout can be imported globally in the following way.
"use client";

import { CodeBlock, ModCodeBlock } from "@/components/code-block";
import Callout from "@/components/callout";
import<EMAIL_ADDRESS>
import { getMDXComponent } from "mdx-bundler/client";

export default function PostContent({ code }: any) {
  const Component = getMDXComponent(code);
  return (
    <Component
      components={{
        code: ({ children, className }: any) => {
          const match = /language-(\w+)/.exec(className || "");
          const language = match ? match[1] : "";

          return <CodeBlock language={language} code={children} />;
        },
        ModCodeBlock,
        Callout,
      }}
    />
  );
}

+1

Try fumadocs-mdx, it loads mdx without any problem even in nextjs 15 environment.
https://fumadocs.vercel.app/docs/mdx


Add to Bower

It would be great if nanoajax was added to Bower :)

Feel free to make the bower.json and push it. I'm not too familiar with it.

I registered it on the registry and pushed a latest semver version with bower.json (0.3.1).
/tmp/yoyo $ bower install nanoajax
bower nanoajax#*                cached git://github.com/yanatan16/nanoajax.git#0.3.1
bower nanoajax#*              validate 0.3.1 against git://github.com/yanatan16/nanoajax.git#*
bower nanoajax#~0.3.1          install nanoajax#0.3.1

nanoajax#0.3.1 bower_components/nanoajax
/tmp/yoyo $ ls
bower_components
/tmp/yoyo $ ls bower_components/
nanoajax

Thanks!


Fix filter query

The filter query contained a bug, as it returned all posts from that year, not only the ones that are related to the community.

Closed #106


[Xcode] Add a missing dependency on adjust-times.

rdar://56270635 (DerivedData/Build/Products/Debug/adjust-times: No such file or directory)

Bypassing merge, this code path isn't tested.


final prediction class

Hi,
When having multi-class MIL, if one case is detected as more than one class (e.g. case#1 is detected as class 0 and class 1 and class 2), how do we decide which class is the final prediction? Is it the argmax of bag_prediction?
Thanks!

It will be detected as positive for both classes and possibly false-positive for one of the classes.


Video doesn't work

My friends and I tried https://meething-webrtc-gun.glitch.me/ today but we found that the video chat cannot be enabled due to an exception
Uncaught TypeError: myStream.getVideoTracks is not a function at HTMLButtonElement.<anonymous> (rtc.js:308)
You probably need to update the deployed version or did we miss anything?
We are using Chrome Version 80.0.3987.149 (Official Build) (64-bit)

Hello @yisiliu
Thanks for giving this a try! The glitch version is a "realtime" dev so it might contain dev bugs. The error you're pointing at suggests there are no streams or perhaps video permissions.
            myStream.getVideoTracks()[0].enabled = !(myStream.getVideoTracks()[0].enabled);

Chrome is what we're using so that's fine. Which OS are you using?
Could you attach the browser console logs before the issue strikes?

Thanks for the quick response! I am using OS X Catalina 10.15.3
The full console log is as follows:
gun.js:973 Hello wonderful person! :) Thanks for using GUN, please ask for help on http://chat.gun.eco if anything takes you longer than 5min to figure out!
three.r95.min.js:175 THREE.WebGLRenderer 95
DevTools failed to parse SourceMap: chrome-extension://iplppiggblloelhoglpmkmbinggcaaoc/app/content.js.map
rtc.js:53 Starting! you are 94e1834e-4080-4722-b6c6-079d88813165
rtc.js:42 debug emit key subscribe value {room: "Test_ekvm52qf0xa", socketId: "94e1834e-4080-4722-b6c6-079d88813165", name: "yisiliu"}
rtc.js:308 Uncaught TypeError: myStream.getVideoTracks is not a function
    at HTMLButtonElement.<anonymous> (rtc.js:308)

Before reporting this issue, I have manually enabled the video and audio permission in the site setting but it still didn't work.

That's interesting the function should not be triggered unless you receive an invite. Did you open two windows/tabs with the room or were you alone?

I opened multiple tabs of two rooms - sorry about that mess. Let me clean it up and try again in incognito.

Hello wonderful person! :) Thanks for using GUN, please ask for help on http://chat.gun.eco if anything takes you longer than 5min to figure out!
three.r95.min.js:175 THREE.WebGLRenderer 95
rtc.js:53 Starting! you are ca3e90f9-45f2-4600-b95a-82bf120659e4
rtc.js:42 debug emit key subscribe value {room: "test-yisiliu_hcby1rfb1hn", socketId: "ca3e90f9-45f2-4600-b95a-82bf120659e4", name: "yisiliu"}
?room=test-yisiliu_hcby1rfb1hn:1 [Intervention] Slow network is detected. See https://www.chromestatus.com/feature/5636954674692096 for more details. Fallback font will be used while loading: https://use.fontawesome.com/releases/v5.7.2/webfonts/fa-solid-900.woff2
rtc.js:308 Uncaught TypeError: myStream.getVideoTracks is not a function
    at HTMLButtonElement.<anonymous> (rtc.js:308)

Can't really replicate it. Are you manually clicking the video icon? The local video only appears upon someone joining. The first session should have no output until someone else joins. No need to click anywhere (if that was the case)
Please try this:

Create a new conference, brand new name and join it. Nothing shoud happen.
Open the full link in a new tab. Enter a username.
Watch the console.log of the first session for errors if no video frames appear.

Not sure, but I'm afraid this might also have something to do with it:
[Intervention] Slow network is detected
I've never seen this before but it definitely WOULD impact usage. We should push an update using more peers later and it should mitigate the issue reaching the first Gun peer.

Weird - it works in this setting. Let me try it out with my friends then.
Regarding the gun peer - we can provide one at Linode Tokyo.

@yisiliu that would be an amazing contribution!
Note: 1-to-1 should work fine (ICE permitting) while 3-way and up signaling up still buggy on the joining and notify parts, so you might have to reload multiple times to see each other above 2 participants with this version.

Thanks! Let's close this issue until further similar issues pop up again. I will test it with my friends and let you know about our experience.
BTW We are also using GUNDB and you can check out our repo at https://github.com/dimensiondev/maskbook.

That's awesome. The "chat" component of this demo is total garbage and would be nice to integrate with your project if possible. Feel free to open an issue if you'd like to explore that anytime!


Use ember-copy instead of Ember.copy/Ember.Copyable

Ember.copy/Ember.Copyable have been deprecated as of Ember 3.3, but the functionality has been made available via a new ember-copy addon.
Fixes #307.

looks great @workmanw hows this look to you?

To be honest, I'm not sure about this. Do we call .copy internally or is that just a convenience for people who are using it at the application tier?
My concern is if Ember is deprecating this capability (and planning to ultimately remove it), then we should too deprecate it. Suppressing these warnings makes it harder for users to find that they're using a deprecate feature.

@workmanw looks like its used for getDefaultValue https://github.com/lytics/ember-data-model-fragments/blob/66ac3a6121111ca9b2409229251d161bdc365403/addon/attributes.js#L389

Oh it's right in the PR we use it. 🤦♂ . I was more focused on the Ember.Copyable I think. Okay, this is fine with me.


Added prefix to all the category methods

This should avoid conflicts with other libraries (which I just had).

Thanks for the contribution. I will create a new major release out of this, because it's API breaking changes

The 2.3 API enabled to write UIColor(hexString: "ff0000"), but the new API doesn't allow UIColor(hx_hexString: "ff0000")...
This is not really swift-friendly...

Yeah I know there is a Problem with the short-hand calls on swift, this problem is caused by the compiler and you have to move your implementation the class calls
UIColor.hx_colorWith8BitRed(33, green: 44, blue: 66)
UIColor.hx_colorWith8BitRed(22, green: 33, blue: 44, alpha: 0.3)
UIColor.hx_colorWithHexString("AAEEFF")
UIColor.hx_colorWithHexString("AAEEFF", alpha: 0.2)

I added examples to the Readme.md


Issue 51 | R Sreelekshmi

Solves issue #51
Describe the changes you made briefly

[x] Wrote C program to check if a given word is a palindrome.

Added the extension.

Thank you for your contribution


high cpu usage on examples

Why almost all the examples has between 20-30% cpu usage?? I mean, even the helloworld example in release mode its 30% of cpu usage

the examples just go as fast as possible, they don't do anything to save power.

Well, just v-sync is preventing it to be 100%. :)


create a ValidatingAdmissionWebhook to ensure vsecm-managed clusterspiffeids’ clusterspiffeidtemplates have the right format

Given this id:
apiVersion: spire.spiffe.io/v1alpha1
kind: ClusterSPIFFEID
metadata:
name: example
spec:
SPIFFE ID MUST start with "spiffe://vsecm.com/workload/$workloadName/ns/"
for vsecm-safe to recognize the workload and dispatch secrets to it.
spiffeIDTemplate: "spiffe://vsecm.com
/workload/example
/ns/default
/sa/example
/n/{{ .PodMeta.Name }}"
podSelector:
matchLabels:
app.kubernetes.io/name: example
workloadSelectorTemplates:

"k8s:ns:default"
"k8s:sa:example"
The controller will ensure that ns/default/sa/example matches the ns and as selectors of the workloadselectortemplate

app.kubernetes.io/name: example matches the name given in workload/example
{{ .PodMeta.Name }} is literally written as is.
This will ensure that the namespace and service account in the cluster spiffe id matches the workload selector;
and the name part of the clusterspiffe id comes from the actual pod meta and it’s not forged.

From our discussion with Giri:
But what would prevent someone spoofing?
I can create a workload with spiffe id > "spiffe://vsecm.com/vsecm/workload/keycloak/n/keycloak-1122334455/ns/vmware-rms/sa/keyckloak-sa" and pretend to be keycloak
This Admission Controller shall be designed to prevent such scenarios.
The SPIFFEIDTemplate will have to match a pattern to even be admitted into the cluster.
"spiffe://vsecm.com/vsecm/workload/$THIS_NAME_IS_FLEXIBLE/n/{{ .PodMeta.Name }}/ns/{{ .PodMeta.Namespace }}/sa/{{ .PodSpec.ServiceAccount }}"
The {{ .PodMeta.Name }} etc are inferred at the Pods or Jobs etc creation time, so we can be sure that they are the name, namespace, and serviceaccount of the workload.
So for the spoofed ClusterSPIFFEID, the admission controller will say something like
"Any VSecM-managed ClusterSPIFFEID shall have .PodMeta.Name , .PodMeta.Namespace, and .PodSepc.ServiceAccount interpolated into the SPIFFE ID Template dynamically, please refer to for more info" in the error logs. — It can also be pushed as an audit log to warn Ops that someone might be spoofing the system.
And we can be sure that someone cannot spoof it because the admission controller will not allow it.
On our end (in VSecM code) we can ensure that if the workload says “I am keycloak”, its SPIFFE ID has keycloak’s namespace and service account (which cannot be spoofed when admission controller is running)
The only way to break this that I can think of is for someone to internally shell into SPIRE Server, and use SPIRE’s registration CLI to create registration entires manually to maybe bypass the Admission Controller’s check — but that would be a cluster admin, not a third-party developer.
ClusterSPIFFEID CR maintainers intentionally keep it generic to keep it reusable everywhere.
But this admission controller works for us. I can make it configurable and propose a change in their upstream, too

The one downside of this approach is, I am vendor-locking myself into Kubernetes a lot.
So if I want to use VSecM outside Kubernetes, I’ll have to reinvent this Admission Controller, and any other guardrails that use Kubernetes primitives (such as the RBAC around VSecM root key k8s Secret etc)
But maybe VSecM should only be something Kubernetes-native, and should only focus to Kubernetes. — that may be its competitive advantage — As in: it is lightweight, because it does not reinvent an admission controller, it already leverages the control loops that exist in the k8s machinery.


Download checksums and check them on upgrade

Download the generated image checksums during the upgrade and check them against the mounted files
Requirements

[x] Somehow obtain the checksum file with all the checksums together with the upgrade image
[x] Add the check during the upgrade part, once we have mounted the upgrade

Done as part of https://github.com/rancher-sandbox/cOS-toolkit/pull/185

Generate checksums[0] as part of the build process with luet-mtree[1]
Patch those checksums as part of the image metadata[2] with a small python util[3]
That metadata gets uploaded along the image[4]
On upgrade run the image check script[5] as luet plugin[6]
Download the metadata [7]
Extract the checksums from the metadata [8]
Compare the checksums against the extracted files with luet-mtree[9]
Fail if they dont match[10]

[0] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/.github/workflows/build.yaml#L118
[1] https://github.com/Itxaka/luet-mtree
[2] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/.github/workflows/build.yaml#L123
[3] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/.github/append_manifests.py
[4] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/.github/workflows/build.yaml#L324
[5] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/packages/installer/image-mtree-check.sh
[6] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/packages/installer/upgrade.sh#L128
[7] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/packages/installer/image-mtree-check.sh#L25
[8] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/packages/installer/image-mtree-check.sh#L26
[9] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/packages/installer/image-mtree-check.sh#L27
[10] https://github.com/rancher-sandbox/cOS-toolkit/blob/master/packages/installer/image-mtree-check.sh#L39


"Get Jenkins admin password from file." fails

While installing over docker image centos:7
    docker-centos: TASK [geerlingguy.jenkins : Get Jenkins admin password from file.] *************
    docker-centos: fatal: [default]: FAILED! => {"censored": "the output has been hidden due to the fact that 'no_log: true' was specified for this result"}

My playbook is
---

- hosts: all
  roles:
    - role: geerlingguy.java
      java_packages:
        - java-1.8.0-openjdk
    - role: geerlingguy.jenkins
      no_log: false #Also fails without this
      jenkins_package_state: latest
      jenkins_plugins_state: latest
      jenkins_http_port: 8080
      jenkins_admin_username: "admin"
      jenkins_admin_password_file: "../default-jenkins-password.txt"
      jenkins_plugins:
        - blueocean
        - git
        - pipeline-model-definition
      become: true

The default role configuration contains
jenkins_java_options: "-Djenkins.install.runSetupWizard=false"
that cause that the file /var/lib/jenkins/secrets/initialAdminPassword is not created. I've found that information at stackoverflow.com; thak you @lukasz-gawron.
@ottosichert, your solution is based on another mechanism used to create user and set password - the groovy script. But I don't know what is the source of the mentioned file /var/lib/jenkins/secrets/initialAdminPassword. Previous installation of the Jenkins? A manual creation?
IMHO, all referenced to the initialAdminPassword are useless in the geerlingguy.jenkins role.
Generally, the geerlingguy.java role - in my opinion - is inconsistent and unmaintained so I've started creating my own base on that - you can find my fork https://github.com/it-praktyk/ansible-role-jenkins. Any constructive contribution will be welcomed.

I have run into this issue. My use of this role was working until today when I refactored a bit and changed some variable names. Not sure why this would cause this issue, but I did find that I am defining some variable names in an outer playbook-level group_var  which are the same name as the geerling role uses. This caused a known recursion bug in ansible 2.9.10.
@it-praktyk I may have a look at your fork and see if your removal of  initialAdminPassword helps me out.


NO-ISSUE: Remove deleted hosts from metadata

We should clean the list of hosts while reading metadata by removing hosts that are deleted BEFORE installation starts
/cc @omertuc

This hopefully will be unnecessary when (if) we'll implement installation ID
/lgtm

I like this idea, I like that it's the default behavior of the get metadata function, but I also want to make it optional, along with a new signature that lists all the deleted hosts

Maybe just add a "virtual" field to the metadata called deleted_hosts that will contain the deleted hosts

I like the solution, pushed!

/lgtm


where is the detail code for SQL generating by PCFG?

Hi
Thanks for the source code. but i'm a little confused about where the detail code for SQL generating by PCFG in the papper "Learning to Synthesize Data for Semantic Parsing".
I found the guideline in readme.md mainly focus  on the sql2nl
I'm doing some experiment about generating some code having different grammar with SQL, your method with PCFG inspire me a lot, could you explain how can we get the new SQL by PCFG, i mean the source code. Thanks!!

ehmm I'm not entirely sure about your question.
So the PCFG file is here https://github.com/berlino/tensor2struct-public/blob/main/tensor2struct/utils/pcfg.py, and you can take a look at this script https://github.com/berlino/tensor2struct-public/blob/main/experiments/sql2nl/scripts/collect_spider_src_tgt.py to see how to use it to generate new SQL.


Inconsistent options of spawn vs invoke for specifying ID

Description
There is a discrepancy between how we set ID for an invoked service vs a spawned actor.
Expected Result
Consistent way to configure an ID for an interpreter.
Actual Result
For invoked services, one has to specify an id option.
invoke: {
  src: someMachine,
  id: 'machine1',
}

For spawned actors, one has to specify a name option.
entry: assign({
  actorRef: () => spawn(someMachine, { name: 'machine2' })
})

Additional context
Both spawned actors, and invoked services are listed in the service.children map side by side, keyed by their id/name.

In xstate@beta, these are now both id:
invoke: {
  // ...
  id: 'machine1'
}

entry: assign({
  actorRef: ({ spawn }) => spawn(someMachine, { id: 'machine2' })
})


Detailing Config Option ButtonText

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powerquery-docs/HandlingDataAccess.md
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@dougklo the author tag is invalid I guess cpopell. Can you do the tech review, or recommend someone else?


Nuxi 3.0.0-rc.13   版本 NuxtLink 切换页面路由失效

Describe the bug
bug 重现分支
https://gitee.com/cestr/bsc-geega-web/tree/1.0.0-stage-1%2Fdevelop/
正常分支 "nuxt": "^3.0.0-rc.11",
https://gitee.com/cestr/bsc-geega-web/tree/1.0.0-stage-1%2Fmain/
Reproduction
https://gitee.com/cestr/bsc-geega-web/tree/1.0.0-stage-1%2Fdevelop/
System Info
OS:Windows 10 22H2
Edge: 107
Node: 16.18.0
npm: 8.19.2
pnpm: 7.14.1

Used Package Manager
pnpm
Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guide.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Check that this is a concrete bug. For Q&A, please open a GitHub Discussion instead.
[X] The provided reproduction is a minimal reproducible of the bug.

Seems to work fine for me now with 3.0


Cho tui link tải

.

https://github.com/KurumiFake/AmongCord/actions , cái mới nhất.

ít literally that button lol

its*


Getting ConversationBufferMemory to work with create_pandas_dataframe_agent

I have been trying to add memory to my create_pandas_dataframe_agent agent and ran into some issues.
I created the agent like this
agent = create_pandas_dataframe_agent(
    llm=llm,
    df=df,
    prefix=prefix,
    suffix=suffix,
    max_iterations=4,
    input_variables=["df", "chat_history", "input", "agent_scratchpad"],
)

and ran into
  File "/path/projects/test/langchain/main.py", line 42, in <module>
    a = agent.run("This is a test")
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/homebrew/lib/python3.11/site-packages/langchain/chains/base.py", line 213, in run
    return self(args[0])[self.output_keys[0]]
           ^^^^^^^^^^^^^
  File "/opt/homebrew/lib/python3.11/site-packages/langchain/chains/base.py", line 106, in __call__
    inputs = self.prep_inputs(inputs)
             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/homebrew/lib/python3.11/site-packages/langchain/chains/base.py", line 185, in prep_inputs
    raise ValueError(
ValueError: A single string input was passed in, but this chain expects multiple inputs ({'input', 'chat_history'}). When a chain expects multiple inputs, please call it by passing in a dictionary, eg `chain({'foo': 1, 'bar': 2})

I was able to fix it by modifying the create_pandas_dataframe_agent to accept the memory object and then passing that along to  the AgentCreator like so:
return AgentExecutor.from_agent_and_tools(
        agent=agent,
        tools=tools,
        verbose=verbose,
        return_intermediate_steps=return_intermediate_steps,
        max_iterations=max_iterations,
        max_execution_time=max_execution_time,
        early_stopping_method=early_stopping_method,
        memory=memory,
    )

Not sure what I did wrong or if I am misunderstanding something in general, maybe this is just the current behavior and adding memory would be a feature request?

Just wanted to add that I'm going thru the excat smae issue.
memory = ConversationBufferMemory(memory_key="chat-history", return_messages=True)

# create and return the chat agent
agent = initialize_agent(
        tools=tools,
        llm=model,
        agent="chat-conversational-react-description",
        verbose=True,
        memory=memory
)

search_me = "how to cook a banana"

agent.run(search_me)

@eike-heimpel is it working for you? I am also having a similar issue where I am using multiple tools. One is RetrievalQA and the next is the Pandas toolkit. But Pandas toolkit is not able to access memory. Any solution for this?

Just to add to the features request to have the Panda agent use memory

@tevslin This worked for me
"""Agent for working with pandas objects."""
from typing import Any, List, Optional

from langchain.agents.agent import AgentExecutor
# from langchain.agents.agent_toolkits.pandas.prompt import PREFIX, SUFFIX
from langchain.agents import ZeroShotAgent
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.llm import LLMChain
from langchain.llms.base import BaseLLM
from langchain.tools.python.tool import PythonAstREPLTool
from langchain.memory import ConversationBufferMemory

memory = ConversationBufferMemory(memory_key="chat_history")
def create_pandas_dataframe_agent(
    llm: BaseLLM,
    df: Any,
    callback_manager: Optional[BaseCallbackManager] = None,
    prefix: str = PREFIX,
    suffix: str = SUFFIX,
    input_variables: Optional[List[str]] = None,
    verbose: bool = False,
    return_intermediate_steps: bool = False,
    max_iterations: Optional[int] = 15,
    max_execution_time: Optional[float] = None,
    early_stopping_method: str = "force",
    **kwargs: Any,
) -> AgentExecutor:
    """Construct a pandas agent from an LLM and dataframe."""
    import pandas as pd

    if not isinstance(df, pd.DataFrame):
        raise ValueError(f"Expected pandas object, got {type(df)}")
    if input_variables is None:
        input_variables = ["df", "input", "agent_scratchpad"]
    tools = [PythonAstREPLTool(locals={"df": df})]

    PREFIX = """
            You are working with a pandas dataframe in Python. The name of the dataframe is `df`.
            You should use the tools below to answer the question posed of you:"""

    SUFFIX = """
            This is the result of `print(df.head())`:
            {df}
            Begin!
            {chat_history}
            Question: {input}
            {agent_scratchpad}"""

    prompt = ZeroShotAgent.create_prompt(
        tools,
        prefix=PREFIX,
        suffix=SUFFIX,
        input_variables=["df", "input", "chat_history", "agent_scratchpad"]
    )

    print(prompt)

    partial_prompt = prompt.partial(df=str(df.head()))

    llm_chain = LLMChain(
        llm=llm,
        prompt=partial_prompt,
        callback_manager=callback_manager,
    )

    tool_names = [tool.name for tool in tools]

    agent = ZeroShotAgent(
        llm_chain=llm_chain,
        allowed_tools=tool_names,
        callback_manager=callback_manager,
        **kwargs,
    )
    return AgentExecutor.from_agent_and_tools(
        agent=agent,
        tools=tools,
        verbose=verbose,
        return_intermediate_steps=return_intermediate_steps,
        max_iterations=max_iterations,
        max_execution_time=max_execution_time,
        early_stopping_method=early_stopping_method,
        callback_manager=callback_manager,
        memory = memory
    )

Thank you.  That works very well. I did have to change the defaults of PREFIX and SUFFIX since they were undefined.
for production I'd suggest that memory be defined by the caller an passed in as an optional parameter with a default of NONE. Also the defaults for SUFFIX and PREFIX can be changed in prompts.py in the \pandas folder or overridden by the caller, Are you going to create a pull-request for this?

Thank you. That works very well. I did have to change the defaults of PREFIX and SUFFIX since they were undefined.
for production I'd suggest that memory be defined by the caller and passed in as an optional parameter with a default of None. Also the defaults for SUFFIX and PREFIX can be changed in prompts.py in the \pandas folder or overridden by the caller, Are you going to create a pull-request for this?

Sure I will create one!!

I just meant that the code which invokes create_pandas_dataframe_agent should allocate the memory buffer if it wants one and pass it as an optional parameter to create_pandas_dataframe_agent.

I just meant that the code which invokes create_pandas_dataframe_agent should allocate the memory buffer if it wants one and pass it as an optional parameter to create_pandas_dataframe_agent.

If the memory parameter is optional, then in the prompt the input variable {chat_history} would also be an optional parameter.

You are absolutely right. Thanks.
From: Rishav Dash @.>
Sent: Monday, May 1, 2023 11:11 AM
To: hwchase17/langchain @.>
Cc: Tom Evslin @.>; Mention @.>
Subject: Re: [hwchase17/langchain] Getting ConversationBufferMemory to work with create_pandas_dataframe_agent (Issue #3106)
I just meant that the code which invokes create_pandas_dataframe_agent should allocate the memory buffer if it wants one and pass it as an optional parameter to create_pandas_dataframe_agent.
If the memory parameter is optional, then in the prompt the input variable {chat_history} would also be an optional parameter.
—
Reply to this email directly, view it on GitHub https://github.com/hwchase17/langchain/issues/3106#issuecomment-1529818780 , or unsubscribe https://github.com/notifications/unsubscribe-auth/AGLSBBSSRCX5LBDIX7N3MKLXD7HBZANCNFSM6AAAAAAXDCEVV4 .
You are receiving this because you were mentioned.  https://github.com/notifications/beacon/AGLSBBREKIUAJRDC7ZLV3S3XD7HBZA5CNFSM6AAAAAAXDCEVV6WGG33NNVSW45C7OR4XAZNMJFZXG5LFINXW23LFNZ2KUY3PNVWWK3TUL5UWJTS3F4XJY.gif Message ID: @.*** @.***> >

@tevslin @Rishav-hub thanks for taking a look here, this sounds good! Is there a PR already that I could take a look at?

@tevslin @Rishav-hub thanks for taking a look here, this sounds good! Is there a PR already that I could take a look at?

Till now I have not made a PR regarding this.

Will we create a PR for this?
It sounds like it would be great and have a great use case 😄

@tevslin @Rishav-hub thanks for taking a look here, this sounds good! Is there a PR already that I could take a look at?

Till now I have not made a PR regarding this.

Will the PR also work with OpenAI functions?

I am facing an error saying "chat_history" not defined. What mistake might I have committed?

I am facing an error saying "chat_history" not defined. What mistake might I have committed?

Can you send the code which is throwing this particular error?

I made it worked all!
Example code at stackoverflow:
https://stackoverflow.com/questions/76500981/how-to-add-conversational-memory-to-pandas-toolkit-agent/76562847#76562847

@tevslin @Rishav-hub thanks for taking a look here, this sounds good! Is there a PR already that I could take a look at?

Till now I have not made a PR regarding this.

hi Rishav, thanks for the great work!
can I just clarify that to implement memory for create_pandas_dataframe_agent, all you did was to change the function defined?
can I also ask if you're comfortable sharing your script that runs the agent? I'm having some issues implementing memory for the pandas df agent.

Doing this worked for me:
 memory=ConversationBufferMemory(memory_key="chat_history", input_key='input', output_key="output")
and while calling the agent:
response = agent(     {         "input": query     } )
Quoting from this: https://github.com/langchain-ai/langchain/issues/2068#issuecomment-1494537932

from langchain.memory.buffer import ConversationBufferMemory
import pinecone
from langchain.vectorstores import Pinecone
from langchain.chat_models import ChatOpenAI
from langchain.chains import LLMChain
from langchain.chains import RetrievalQA
from langchain.chains import ConversationalRetrievalChain
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.prompts import PromptTemplate
from langchain.chains.router import MultiRetrievalQAChain
from langchain.chains.question_answering import load_qa_chain
from langchain.agents import AgentType, initialize_agent
from langchain.tools import Tool
from flask import Flask, render_template, request, jsonify
import os
app = Flask(name)
#Initialize Openai
from dotenv import load_dotenv
Load environment variables from .env file
load_dotenv('.env')
OPENAI_API_KEY =  os.getenv("OPENAI_API_KEY")
PINECONE_API_KEY = os.getenv('PINECONE_API_KEY')
PINECONE_API_ENV = os.getenv('PINECONE_API_ENV')
Initialize pinecone and set index
pinecone.init(
api_key=PINECONE_API_KEY,
environment=PINECONE_API_ENV
)
index_name = "main"
Initialize embeddings and AI
projectwe_embeddings = OpenAIEmbeddings()
Prompt Template
template = """
QUESTION:
{question}
CHAT HISTORY:
{chat_history}
ANSWER:
"""
prompt = PromptTemplate(input_variables=["chat_history", "question"], template=template)
#FOR PROJECTWE
projectwe_retriever = Pinecone.from_existing_index(index_name=index_name, embedding=projectwe_embeddings, namespace="ProjectWe-Virtual Assistant")
#projectwe memory
projectwe_memory = ConversationBufferMemory(memory_key="chat_history", input_key="question",return_messages=True)
Llms
llm = ChatOpenAI(temperature=0)
projectwe_chain = LLMChain(llm=llm, prompt=prompt,output_key='question')
#ProjectWe-Chain
chain1 = load_qa_chain(llm, chain_type="stuff", memory=projectwe_memory)
p_chain = ConversationalRetrievalChain(
retriever=projectwe_retriever.as_retriever(),
question_generator=projectwe_chain,
combine_docs_chain=chain1,
)
#For MUSE
Initialize embeddings and AI
muse_embeddings = OpenAIEmbeddings()
Prompt Template
template = """
QUESTION:
{question}
CHAT HISTORY:
{chat_history}
ANSWER:
"""
prompt = PromptTemplate(input_variables=["chat_history", "question"], template=template)
muse_memory = ConversationBufferMemory(memory_key="chat_history", input_key="question",return_messages=True)
muse_retriever = Pinecone.from_existing_index(index_name=index_name, embedding=muse_embeddings, namespace="cust-muse-mojomosaic-pinecone")
Llms
llm = ChatOpenAI(temperature=0)
muse_chain = LLMChain(llm=llm, prompt=prompt,output_key='question')
#ProjectWe-Chain
chain2 = load_qa_chain(llm, chain_type="stuff", memory=muse_memory)
m_chain = ConversationalRetrievalChain(
retriever=muse_retriever.as_retriever(),
question_generator=muse_chain,
combine_docs_chain=chain2,
)
#initilaize tool
tools=[
Tool.from_function(
func=p_chain.run,
name="ProjectWe_Virtual_Assistant",
description="DESCRIBE ProjectWe"
),
Tool.from_function(
func=m_chain.run,
name="Muse",
description="Generate sections from Muse Bootstrap snippets for ProjectWe_Virtual_Assistant"
)
]
Set up Agent
model_name="gpt-4"
agent_llm = ChatOpenAI(temperature=0.2,model_name=model_name)
#Agent memory
agent_memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
chatagent = initialize_agent(tools, agent_llm, agent=AgentType.OPENAI_FUNCTIONS, memory = agent_memory,verbose=True)
@app.route('/')
def index():
return render_template("flow.html")
@app.route('/send_message', methods=['POST'])
def ask():
message = request.form['message']
if chatagent is None:
return jsonify({'message': 'Agent not initialized'})
response = chatagent.run ({'input': {'question': message, 'chat_history': []}})
mem = agent_memory.save_context({'question': message}, {'answer': response})
chat_history = agent_memory.load_memory_variables({})['chat_history']
print("Response", response)
return jsonify({'message': response, 'memory': chat_history})
if name == 'main':
app.run(port = 5005, debug=True)
Whole error:
> Entering new AgentExecutor chain...
Invoking: Muse with ProjectWe
<IP_ADDRESS> - - [01/Nov/2023 00:30:17] "POST /send_message HTTP/1.1" 500 -
Traceback (most recent call last):
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\flask\app.py", line 2213, in call
return self.wsgi_app(environ, start_response)
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\flask\app.py", line 2193, in wsgi_app
response = self.handle_exception(e)
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\flask\app.py", line 2190, in wsgi_app
response = self.full_dispatch_request()
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\flask\app.py", line 1486, in full_dispatch_request
rv = self.handle_user_exception(e)
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\flask\app.py", line 1484, in full_dispatch_request
rv = self.dispatch_request()
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\flask\app.py", line 1469, in dispatch_request
return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)
File "D:\mojosolo_projects\mojobob\conver.py", line 125, in ask
response = chatagent.run ({'input': {'question': message, 'chat_history': []}})
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\chains\base.py", line 487, in run
return self(args[0], callbacks=callbacks, tags=tags, metadata=metadata)[
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\chains\base.py", line 292, in call
raise e
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\chains\base.py", line 286, in call
self._call(inputs, run_manager=run_manager)
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\agents\agent.py", line 1039, in _call
next_step_output = self._take_next_step(
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\agents\agent.py", line 894, in _take_next_step
observation = tool.run(
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\tools\base.py", line 356, in run
raise e
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\tools\base.py", line 328, in run
self._run(*tool_args, run_manager=run_manager, **tool_kwargs)
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\tools\base.py", line 499, in _run
self.func(
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\chains\base.py", line 487, in run
return self(args[0], callbacks=callbacks, tags=tags, metadata=metadata)[
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\chains\base.py", line 268, in call
inputs = self.prep_inputs(inputs)
File "C:\Users\MUAZ\AppData\Local\Programs\Python\Python39\lib\site-packages\langchain\chains\base.py", line 415, in prep_inputs
raise ValueError(
ValueError: A single string input was passed in, but this chain expects multiple inputs ({'question', 'chat_history'}). When a chain expects multiple inputs,
please call it by passing in a dictionary, eg chain({'foo': 1, 'bar': 2})

@tevslin This worked for me
"""Agent for working with pandas objects."""
from typing import Any, List, Optional

from langchain.agents.agent import AgentExecutor
# from langchain.agents.agent_toolkits.pandas.prompt import PREFIX, SUFFIX
from langchain.agents import ZeroShotAgent
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.llm import LLMChain
from langchain.llms.base import BaseLLM
from langchain.tools.python.tool import PythonAstREPLTool
from langchain.memory import ConversationBufferMemory

memory = ConversationBufferMemory(memory_key="chat_history")
def create_pandas_dataframe_agent(
    llm: BaseLLM,
    df: Any,
    callback_manager: Optional[BaseCallbackManager] = None,
    prefix: str = PREFIX,
    suffix: str = SUFFIX,
    input_variables: Optional[List[str]] = None,
    verbose: bool = False,
    return_intermediate_steps: bool = False,
    max_iterations: Optional[int] = 15,
    max_execution_time: Optional[float] = None,
    early_stopping_method: str = "force",
    **kwargs: Any,
) -> AgentExecutor:
    """Construct a pandas agent from an LLM and dataframe."""
    import pandas as pd

    if not isinstance(df, pd.DataFrame):
        raise ValueError(f"Expected pandas object, got {type(df)}")
    if input_variables is None:
        input_variables = ["df", "input", "agent_scratchpad"]
    tools = [PythonAstREPLTool(locals={"df": df})]

    PREFIX = """
            You are working with a pandas dataframe in Python. The name of the dataframe is `df`.
            You should use the tools below to answer the question posed of you:"""

    SUFFIX = """
            This is the result of `print(df.head())`:
            {df}
            Begin!
            {chat_history}
            Question: {input}
            {agent_scratchpad}"""

    prompt = ZeroShotAgent.create_prompt(
        tools,
        prefix=PREFIX,
        suffix=SUFFIX,
        input_variables=["df", "input", "chat_history", "agent_scratchpad"]
    )

    print(prompt)

    partial_prompt = prompt.partial(df=str(df.head()))

    llm_chain = LLMChain(
        llm=llm,
        prompt=partial_prompt,
        callback_manager=callback_manager,
    )

    tool_names = [tool.name for tool in tools]

    agent = ZeroShotAgent(
        llm_chain=llm_chain,
        allowed_tools=tool_names,
        callback_manager=callback_manager,
        **kwargs,
    )
    return AgentExecutor.from_agent_and_tools(
        agent=agent,
        tools=tools,
        verbose=verbose,
        return_intermediate_steps=return_intermediate_steps,
        max_iterations=max_iterations,
        max_execution_time=max_execution_time,
        early_stopping_method=early_stopping_method,
        callback_manager=callback_manager,
        memory = memory
    )

How to use the function to start asking questions? @Rishav-hub

Thank you. That works very well. I did have to change the defaults of PREFIX and SUFFIX since they were undefined.
for production I'd suggest that memory be defined by the caller and passed in as an optional parameter with a default of None. Also the defaults for SUFFIX and PREFIX can be changed in prompts.py in the \pandas folder or overridden by the caller, Are you going to create a pull-request for this?

@tevslin Can you please share your SUFFIX and PREFIX that you have used for working with a CSV  that uses memory and do not hallucinate much on the response. Thanks in advance

I haven’t been using Langchain lately as much as I appreciate it  (busy with Autogen) and have never used it with CSVs,
From: 3dhunter97 @.>
Sent: Friday, January 12, 2024 1:49 AM
To: langchain-ai/langchain @.>
Cc: Tom Evslin @.>; Mention @.>
Subject: Re: [langchain-ai/langchain] Getting ConversationBufferMemory to work with create_pandas_dataframe_agent (Issue #3106)
Thank you. That works very well. I did have to change the defaults of PREFIX and SUFFIX since they were undefined.
for production I'd suggest that memory be defined by the caller and passed in as an optional parameter with a default of None. Also the defaults for SUFFIX and PREFIX can be changed in prompts.py in the \pandas folder or overridden by the caller, Are you going to create a pull-request for this?
@tevslin https://github.com/tevslin  Can you please share your SUFFIX and PREFIX that you have used for working with a CSV that uses memory and do not hallucinate much on the response. Thanks in advance
—
Reply to this email directly, view it on GitHub https://github.com/langchain-ai/langchain/issues/3106#issuecomment-1888522623 , or unsubscribe https://github.com/notifications/unsubscribe-auth/AGLSBBQCHBVLBFTVH5NNZ6DYODMG5AVCNFSM6AAAAAAXDCEVV6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQOBYGUZDENRSGM .
You are receiving this because you were mentioned.  https://github.com/notifications/beacon/AGLSBBXSEETFCXGZESQQXI3YODMG5A5CNFSM6AAAAAAXDCEVV6WGG33NNVSW45C7OR4XAZNMJFZXG5LFINXW23LFNZ2KUY3PNVWWK3TUL5UWJTTQSCIX6.gif Message ID: @.*** @.***> >

Error ModuleNotFoundError: No module named 'langchain.tools.python.tool'

https://python.langchain.com/docs/integrations/tools/python

I am having some issues with the agent and agent executor. I have a pipeline as such.
class LanguageModelLoaderGPU:
    # @suppress_error_output
    model_cfg = TapexModel()

    def __init__(self, model_name=None, model_file=None):
        self.model_name = self.model_cfg.model_name if model_name is None else model_name
        self.model_file = self.model_cfg.model_file if model_file is None else model_file
        self.verbose = False

        quantization_config = BitsAndBytesConfig(
            load_in_8bit=True,
            llm_int8_threshold=100.0)

        _model = BartForConditionalGeneration.from_pretrained(
            self.model_cfg.t_model_name,
            torch_dtype=torch.float16,
            cache_dir="./models",
            # max_new_tokens=256,
            # top_p=0.95,
            # top_k=5,
            # quantization_config=quantization_config,
        )
        _tokenizer = TapexTokenizer.from_pretrained(
            self.model_cfg.t_model_name,
            model_max_length=512,
            cache_dir="./models",
        )
        pipe_summary = pipeline("table-question-answering", model=_model, tokenizer=_tokenizer, max_new_tokens=1024)
        hf_summary = HuggingFacePipeline(pipeline=pipe_summary)

        self.model = hf_summary

And I am trying to use the agent.invoke.
class CliViewer:
    def __init__(self, file_name):
        self.file_name = file_name
        self.df = pd.read_csv(file_name)

        print("getting llm model", self.df.head())

        _llm = LanguageModelLoaderGPU()
        # chat_memory = PandasChatMemory(_llm.model).with_history().with_summary()
        chat_memory = PandasChatMemory(_llm.model).get_memory()
        #
        # print("initializing pandas agent")
        self.agent = create_pandas_dataframe_agent(
            llm=_llm.model,
            df=self.df,
            # suffix=SUFFIX_WITH_DF,
            agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
            prefix=TEMPLATE,
            early_stopping_method='generate',
            max_iterations=5,
            include_df_in_prompt=True,
            agent_executor_kwargs={
                'handling_parsing_errors': "Check your output and make sure it conforms!",
                'memory': chat_memory,
            },
            verbose=True,
        )

        print("pandas agent loading complete", self.df.head())
        # session = PromptSession(history=FileHistory(".agent-history-file"))
        # while True:
        question = "How many matches did Chennai Super Kings win and lose?"

        print("invoking agent")
        result = self.agent.invoke({"input": question}, callbacks=[StreamingStdOutCallbackHandler()])
        print("result", result)

I am getting an error.
Short summary:
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/src/views/clileet.py", line 114, in __init__
    result = self.agent.invoke({"input": question}, callbacks=[StreamingStdOutCallbackHandler()])
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    raise ValueError(
ValueError: Keyword argument `table` should be a list of dict, but is <generator object TableQuestionAnsweringArgumentHandler.__call__.<locals>.<genexpr> at 0x16dc0ecf0>

Trace:
Traceback (most recent call last):
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/main.py", line 53, in <module>
    main()
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/main.py", line 47, in main
    run_cli_command(args)
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/main.py", line 23, in run_cli_command
    CliViewer(args.file)
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/src/views/clileet.py", line 114, in __init__
    result = self.agent.invoke({"input": question}, callbacks=[StreamingStdOutCallbackHandler()])
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain/chains/base.py", line 163, in invoke
    raise e
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain/chains/base.py", line 153, in invoke
    self._call(inputs, run_manager=run_manager)
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain/agents/agent.py", line 1432, in _call
    next_step_output = self._take_next_step(
                       ^^^^^^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain/agents/agent.py", line 1138, in _take_next_step
    [
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain/agents/agent.py", line 1166, in _iter_next_step
    output = self.agent.plan(
             ^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain/agents/agent.py", line 397, in plan
    for chunk in self.runnable.stream(inputs, config={"callbacks": callbacks}):
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/runnables/base.py", line 2685, in stream
    yield from self.transform(iter([input]), config, **kwargs)
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/runnables/base.py", line 2672, in transform
    yield from self._transform_stream_with_config(
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/runnables/base.py", line 1743, in _transform_stream_with_config
    chunk: Output = context.run(next, iterator)  # type: ignore
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/runnables/base.py", line 2636, in _transform
    for output in final_pipeline:
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/runnables/base.py", line 1209, in transform
    for chunk in input:
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/runnables/base.py", line 4532, in transform
    yield from self.bound.transform(
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/runnables/base.py", line 1226, in transform
    yield from self.stream(final, config, **kwargs)
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/language_models/llms.py", line 386, in stream
    yield self.invoke(input, config=config, stop=stop, **kwargs)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/language_models/llms.py", line 248, in invoke
    self.generate_prompt(
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/language_models/llms.py", line 569, in generate_prompt
    return self.generate(prompt_strings, stop=stop, callbacks=callbacks, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/language_models/llms.py", line 748, in generate
    output = self._generate_helper(
             ^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/language_models/llms.py", line 606, in _generate_helper
    raise e
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_core/language_models/llms.py", line 593, in _generate_helper
    self._generate(
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/langchain_community/llms/huggingface_pipeline.py", line 266, in _generate
    responses = self.pipeline(
                ^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/transformers/pipelines/table_question_answering.py", line 344, in __call__
    pipeline_inputs = self._args_parser(*args, **kwargs)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/alexday/dev/llmexperiments/csv-agents-llm/.venv/lib/python3.12/site-packages/transformers/pipelines/table_question_answering.py", line 54, in __call__
    raise ValueError(
ValueError: Keyword argument `table` should be a list of dict, but is <generator object TableQuestionAnsweringArgumentHandler.__call__.<locals>.<genexpr> at 0x16dc0ecf0>

Help please?


Clone client repository

User story

As a user
I want to get requisite knowledge of existing emba webservice
In order to analyze and implement new compatible functionalities.

Acceptance criteria

The client repo: https://github.com/e-m-b-a/emba must be cloned by every developer.
The developers have gained knowledge regarding emba webservice structure and module usage.

Definition of done

Code review from peers has been completed and passed

Code is fully implemented and commented
Adheres to coding guidelines
Commits are not squashed
Code is checked into the repository

Unit tests for backend have been written and are passing
Manual performance tests on the browser are passing
No critical bugs are open

Completed!


Media: Do not store transient data on resource objects

Context

Summary
Remove the local, isMuting, isTrimming and isTranscoding properties from the resource object stored in elements. This means, a large refactor, meaning all the references to this properties, in code and in tests. Use the media queue hook to work out if an resource is transcoding or local.
There are two kinds of resources lookups required. By ID or by original id. For muting/transcoding/trimming resources, there are cases where need to lookup by id ( like in the media library ) and cases where we need to lookup state by the original id. This is because, while a resource is processing, it doesn't have an id yet, it uses a temp id. So we have to lookup via the old resources id.
I have fixed all tests and added a couple of new ones for the new functionality found in the reducer.
Relevant Technical Choices

To-do

User-facing changes

Testing Instructions

[ ] This is a non-user-facing change and requires no QA

This PR can be tested by following these steps:
This change effects all parts of uploading assets, ALL upload interactions will need to be tests. Including.

Upload of Image, video and gifs.
Muting of videos.
Trimming of videos and trimming a trimmed video.
Transcoding videos.
Uploading via the WP media dialog.
Dragging into canvas.
Pasting image into canvas
Dragging animated gif onto canvas and convert to mp4.

All video uploads, should include a time stamp, is muted icon and poster image.
Upload of Image.

Open editor.
Drag a png/jpeg file into canvas / media library.
See progress bar appear on new media item added to library and save button disabled.
Progress bar finishes.
Save button re-enabled

Upload of Video.

Open editor.
Drag a mp4/webm file into canvas / media library.
See progress bar appear on new media item added to library and save button disabled. You should be able to hover over save button / new item in media library, saying that transcoding is taking place.  Trimming / muting options should be hidden.
Progress bar finishes.
Save button re-enabled / Trimming / muting buttons should appear

Upload of animated gif.

Open editor.
Drag a animated fig file into canvas / media library.
See progress bar appear on new media item added to library and save button disabled. You should be able to hover over save button / new item in media library, saying that transcoding is taking place.
Progress bar finishes.
Save button re-enabled

Muting a video.

Open editor.
Insert a video ( that has sound ) into canvas.
In documents sidebar, under video options click mute video.
See progress bar appear on new media item added to library and save button disabled. You should be able to hover over save button / new item in media library, saying that transcoding is taking place.
Progress bar finishes.
Save button re-enabled

Trimming video

Open editor.
Insert a video into canvas.
In documents sidebar, under video options click trim.
Trimming video to 10 seconds.
Click trim to start trimming process.
See progress bar appear on new media item added to library and save button disabled. You should be able to hover over save button / new item in media library, saying that transcoding is taking place.
Progress bar finishes.
Save button re-enabled.

Retrimming video

Follow steps in trimming video.
On video video, retrim video, following steps in trimming video.

Pasting file

Copy jpg/mp4/gif into clip from desktop / folder.
Open editor.
Paste file into canvas.
See progress bar appear on new media item added to library and save button disabled.
Progress bar finishes.
Save button re-enabled

Upload via the WP media dialog.

Open editor.
Click on upload button.
See WP media dialog open.
Upload jpg/animated gif/video into WP media dialog.
Insert new asset into page.
See dialog close.
See new asset in media library and element in canvas.

Transcode existing video.

Go to Media > Upload
Upload 1080p / 4K mp4 video.
Open editor.
Insert 1080p / 4K mp4 video into canvas.
Add title to story.
Publish story.
Open checklist.
See option to opertize video.
Click opertize video.
See progress bar appear on new media item added to library and save button disabled. You should be able to hover over save button / new item in media library, saying that transcoding is taking place.
Progress bar finishes.
Save button re-enabled.

Reviews
Does this PR have a security-related impact?

Does this PR change what data or activity we track or use?

Does this PR have a legal-related impact?

Checklist

[x] This PR addresses an existing issue and I have linked this PR to it in ZenHub
[x] I have tested this code to the best of my abilities
[x] I have verified accessibility to the best of my abilities (docs)
[x] I have verified i18n and l10n (translation, right-to-left layout) to the best of my abilities
[x] This code is covered by automated tests (unit, integration, and/or e2e) to verify it works as intended (docs)
[x] I have added documentation where necessary
[x] I have added a matching Type: XYZ label to the PR

Fixes #9577

@spacedmonkey There's currently something off with the states while processing. E.g. try trimming or muting a video.
Previously, when trimming a video, the Trim button got disabled in the design panel and showed that it was trimming + showed the circular progress. Similar for Muting IIRC. Currently, visibly nothing seems to happen in the design panel, the trim mode just exits. (It can be seen in the Media panel that the video is processing, so the functionality is working in the background but there's no indication of it anymore in the design panel).

That fixed the issue for me, can you retest.

Unfortunately, I'm still seeing some issues with re-trimming, specifically when re-trimming a second time.
When re-trimming a video for the second time, it should show the total length of the trimmer according to the original video, and the current selected length based on the new trimmed video. Currently, when re-trimming a video shorter, and then trying to re-trim, it shows the maximum length of the video right away (instead of the trimmed length).
Steps to reproduce:

Add a non-trimmed video.
Trim the video (e.g. from 15 seconds to 6 seconds) - works
Wait until trimming finishes and open the trimmer again - works
Now re-trim the video again (e.g. from 6 seconds to 2 seconds) - visibly seems to work
Open the trimmer again. The trimmer still shows 6 seconds as the length instead of 2 seconds. - incorrect value

So the initial trimming works. The first re-trimming works. And then trying to re-trim the second time, there's something not right.
Thoughts?

Unfortunately, I'm still seeing some issues with re-trimming, specifically when re-trimming a second time.

@spacedmonkey I'm testing on main just in case and seeing the same issue there. I'll do some more testing but looks like it's not related to this PR.

@spacedmonkey FYI this has some conflicts now.

@spacedmonkey FYI there are some lint errors.


Use clang for inspecting macros instead of compiling the binary.

This allows cross-compilation and is simpler and faster as it doesn't touch the filesystem.
It's a complete rewrite of check_features() so it's easier just to read it rather than the diff.

@FreezyLemon I've updated this to cover the latest changes and fixed it so that the output is the same as the current build.rs, verified for ffmpeg 4.0-7.0 on macOS.

Thanks for updating the PR!


cannot upload a file on article submission

I cannot upload a file in the first step of the article submission.

could you be more specific about which step?

BTW, I could uploaded a file.

Yes this step. I logged in as beyza, dergipark

I first did not upload any file and said save&next. Then next page did not open and I tried to upload a file then.

the problem is about #933 and which users has api key.


Crawling hands drop the wrong item

🐛 Bug Report
Crawling hands seem to drop the wrong trophy item. The one in the Slayer log is correct, which is the same one that the in-game log uses.
Simulation showing wrong item:
What it should drop (First item):

duplicate of #2106


Arm modes in scenes always "Arm Home" or "Arm away" and independent of modes in the alarmo settings

Alarmo Version
v1.8.1
HA Version
2021.12.10
Bug description
The arm modes when adding Alarmo as a unit in scenes are independent of the choosen ones in the alarmo settings. I have set up "arm away" and "arm night" but the modes displayed in scenes are "armed away", and "armed home". Also, it does not seem that i am able to "disarm" the alarm in a scene. I am able to manually change this in the scenes.yaml however, so the bug is only in the UI
Steps to reproduce
No response
Relevant log output
No response

This is a known issue in HA.
I can make an alarm with 4 arm modes:

If I click on the circle with the icon, I get the 'more info' dialog with only 2 arm modes:

I guess this dialog is the same when you use the alarm in a scene.
Unfortunately this UI belongs to HA itself, I cannot change it from Alarmo.
The issue has been reported in 2020 already, but is not solved yet, see: https://github.com/home-assistant/frontend/discussions/11287.
I cannot help you with this bug. The.bug is in HA, not in Alarmo.
PS: I am not sure if you can use the alarm in scenes, because you (may) need to enter the pin code for arming/disarming. I don't think you can configure a scene to do this.


TETP-25 Employer can accept terms before publish

Allow link Confirm Dialog. Upgrade hsd-react in tet/admin
Description :sparkles:
Issues :bug:
Testing :alembic:
Screenshots :camera_flash:
Additional notes :spiral_notepad:

Codecov Report

Merging #895 (27d0f42) into develop (ee045b2) will decrease coverage by 31.79%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##           develop     #895       +/-   ##
============================================
- Coverage    62.98%   31.18%   -31.80%
============================================
  Files          862      368      -494
  Lines        23067     7805    -15262
  Branches      2311     1622      -689
============================================
- Hits         14528     2434    -12094
+ Misses        8149     5131     -3018
+ Partials       390      240      -150

Impacted Files
Coverage Δ

...admin/src/components/editor/form/ActionButtons.tsx
0.00% <ø> (ø)

...components/jobPostings/JobPostingsListItemMenu.tsx
0.00% <ø> (ø)

...s/applications/applicationList/ApplicationList.tsx
95.00% <0.00%> (-5.00%)
:arrow_down:

...applications/applicationList/useApplicationList.ts
35.63% <0.00%> (-1.15%)
:arrow_down:

...s/forms/application/step4/ApplicationFormStep4.tsx
0.00% <0.00%> (ø)

...ed/src/components/confirm-dialog/ConfirmDialog.tsx

frontend/shared/src/contexts/DialogContext.tsx

frontend/shared/src/hooks/useConfirm.ts

frontend/shared/src/components/layout/Layout.sc.ts

...it/applications/migrations/0009_attachments_api.py

... and 489 more

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Outdated ggplot2 package version.

Hi team,
The ggplot2 version was recently updated on Power BI Service to support version 3.3.2. Please kindly update this version on the supported versions in R script.
Regards!

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: df17e088-5cff-4882-79fc-cc7deb09843d
Version Independent ID: 641ddc87-0314-47c4-bee7-684ebe7f8e6e
Content: Learn which R packages are supported - Power BI
Content Source: powerbi-docs/connect-data/service-r-packages-support.md
Service: powerbi
Sub-service: pbi-data-sources
GitHub Login: @davidiseminger
Microsoft Alias: davidi

Hi, @NairaMSFT -- thanks for your comment!
Question: I selected the link in the ggplot2 row of the table, https://cran.r-project.org/web/packages/ggplot2/index.html. It lists the version as 3.3.3.
Should we put 3.3.2 or 3.3.3 in the table?
Thanks!

Hi, @NairaMSFT -- thanks for your comment!
Question: I selected the link in the ggplot2 row of the table, https://cran.r-project.org/web/packages/ggplot2/index.html. It lists the version as 3.3.3.
Should we put 3.3.2 or 3.3.3 in the table?
Thanks!

Thanks, @NairaMSFT ! Change is made, will be live later today.

Thanks, @NairaMSFT ! Change is made, will be live later today.

Thanks a lot for the help!

Thanks a lot for the help!


Syntax error in translation file

Hello a recent update caused this bug

ParseError: syntax error, unexpected ''Load previous items'' (T_CONSTANT_ENCAPSED_STRING), expecting ']' in /vendor/kop/yii2-scroll-pager/messages/en/general.php:6

which is because of a missing comma , after the second key=>value pair declared in the mentioned file
return [
    'Load more items' => 'Load more items',
    'You reached the end' => 'You reached the end'
    'Load previous items' => 'Load previous items'
];

Hi.
Fixed in #106
Please try to update


HBASE-24968 : Move META_COMPARATOR to subclass MetaCellComparator

Break subclass referencing of MetaCellComparator from superclass CellComparatorImpl
static initializer by moving META_COMPARATOR to subclass MetaCellComparator

Closes #2329
Signed-off-by: Duo Zhang<EMAIL_ADDRESS>

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1.8.0_232

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https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk8-hadoop2-check/output/patch-unit-hbase-server.txt

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/testReport/

Max. process+thread count
2758 (vs. ulimit of 12500)

modules
C: hbase-common hbase-client hbase-server U: .

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/console

versions
git=2.17.1 maven=(cecedd343002696d0abb50b32b541b8a6ba2883f)

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:broken_heart: -1 overall

Vote
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+0 :ok:
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0m 28s
Docker mode activated.

-0 :warning:
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0m  6s
Unprocessed flag(s): --brief-report-file --spotbugs-strict-precheck --whitespace-eol-ignore-list --whitespace-tabs-ignore-list --quick-hadoopcheck

_ Prechecks _

_ branch-2 Compile Tests _

+0 :ok:
mvndep
0m 16s
Maven dependency ordering for branch

+1 :green_heart:
mvninstall
5m 10s
branch-2 passed

+1 :green_heart:
compile
2m 33s
branch-2 passed

+1 :green_heart:
shadedjars
8m 33s
branch has no errors when building our shaded downstream artifacts.

-0 :warning:
javadoc
0m 34s
hbase-client in branch-2 failed.

-0 :warning:
javadoc
0m 17s
hbase-common in branch-2 failed.

-0 :warning:
javadoc
0m 49s
hbase-server in branch-2 failed.

_ Patch Compile Tests _

+0 :ok:
mvndep
0m 21s
Maven dependency ordering for patch

+1 :green_heart:
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4m 57s
the patch passed

+1 :green_heart:
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2m 24s
the patch passed

+1 :green_heart:
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2m 24s
the patch passed

+1 :green_heart:
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7m 51s
patch has no errors when building our shaded downstream artifacts.

-0 :warning:
javadoc
0m 16s
hbase-common in the patch failed.

-0 :warning:
javadoc
0m 32s
hbase-client in the patch failed.

-0 :warning:
javadoc
0m 44s
hbase-server in the patch failed.

_ Other Tests _

+1 :green_heart:
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2m  4s
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+1 :green_heart:
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3m 11s
hbase-client in the patch passed.

-1 :x:
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192m 32s
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235m 54s

Subsystem
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Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2332

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 9046cea512dc 4.15.0-112-generic #113-Ubuntu SMP Thu Jul 9 23:41:39 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
branch-2 / a765d859f9

Default Java
2020-01-14

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-client.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-common.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-server.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-common.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-client.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-server.txt

unit
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/artifact/yetus-jdk11-hadoop3-check/output/patch-unit-hbase-server.txt

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/testReport/

Max. process+thread count
2381 (vs. ulimit of 12500)

modules
C: hbase-common hbase-client hbase-server U: .

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2332/1/console

versions
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MINOR: Update year in NOTICE

More detailed description of your change,
if necessary. The PR title and PR message become
the squashed commit message, so use a separate
comment to ping reviewers.
Summary of testing strategy (including rationale)
for the feature or bug fix. Unit and/or integration
tests are expected for any behaviour change and
system tests should be considered for larger changes.
Committer Checklist (excluded from commit message)

[ ] Verify design and implementation
[ ] Verify test coverage and CI build status
[ ] Verify documentation (including upgrade notes)

ping one of @ijuma @cmccabe for review

I'll cherry-pick this back one merged

Merged #8207 into trunk

cherry-picked to 2.4


Custom MultiLanguage Behavior (Recursion issue)

I've created custom MultiLanguage Behavior. As it seems it works properly. But When I'm debugging the result set. I see Recursion. That is the only issue. Is there any problem or not?

No, it's not a problem.


Invalid call. Nonexistent function 'reload' in base 'GDScript'.

Tested versions
v4.3.beta1.mono.official [a4f2ea91a]
System information
Godot v4.3.beta1.mono - Windows 10.0.17763 - Vulkan (Forward+) - dedicated NVIDIA GeForce RTX 2060 (NVIDIA; <IP_ADDRESS>49) - AMD Ryzen 9 5950X 16-Core Processor (32 Threads)
Issue description
Coding like this:
extends Node

var obj = RefCounted.new()
var gds = GDScript.new()

func _ready():
	gds.source_code = "func a():return 100"
	gds.reload()
	obj.set_script(gds)
	var rs = obj.a()
	prints(rs)

This code work before 4.3dev6 and output 100.
Steps to reproduce
run the MRP, it report error
Minimal reproduction project (MRP)
gdstest.zip

Bisecting points to #92035 as the culprit:

Cherry-picked #92609 and seems to solve this issue

this is probly bc if there were any errors compiling (possibly another gdscript bug related to built-in scripts), sets the script as not 'valid', then https://github.com/godotengine/godot/pull/92035 restricted GDScript member functions too much so that reload wasnt a valid function if the script isnt valid, thats what https://github.com/godotengine/godot/pull/92609 fixes

Oh no, this issue was broken my project. but it not fixed in 4.2beta2, so I can't update to beta2 for test my project, it make me so sad.
Can this issue fixed in the next version(4.3beta3)?

@CsloudX There's a PR pending review: #92609. If you can test it and confirm it fixes your issue, that helps the review process to have confidence that it covers potentially more complex cases than the ones in MRPs. See https://docs.godotengine.org/en/stable/contributing/workflow/testing_pull_requests.html for instructions on how to test a PR.

@CsloudX There's a PR pending review: #92609. If you can test it and confirm it fixes your issue, that helps the review process to have confidence that it covers potentially more complex cases than the ones in MRPs. See https://docs.godotengine.org/en/stable/contributing/workflow/testing_pull_requests.html for instructions on how to test a PR.


[Feature Request] SSE/EventStream debuging

Can we look into adding an EventStream client? it would be really helpful to debug SSEs and they are really starting to take off.

This is still interesting.

Any interest in this anymore?

Still interested

Because this is closed?

+1

Any progress on this?
The same seems to be asked for Postman but like this issue - went quiet...
https://github.com/postmanlabs/postman-app-support/issues/6682

This is still interesting.

👍

+1

Any update on this?

+1000

Need this ❤

up

Insomnia has a better UI/UX and usability but i have to switch between hopscotch for websockets & sse. quite annoying.
Can we get at least an ETA?

1


broken modal on safari

probably has to do with flexbox that's set on the modal

temporary fix for the bug see PR
https://github.com/rijkvanzanten/obachine/pull/48


dependency require-from-string v2.0.2 is broken

oops - it looks like this is just an issue on the private registry I'm using. disregard.

What did you do to fix the issue? We're also behind a private registry and are having trouble with this.

We haven't fixed it yet - I was just able to isolate the issue. If you compare the tarball that is provided by the public registry to that provided by your private registry, you'll notice it's different and has a different sha.
$ curl -s https://registry.npmjs.org/require-from-string | jq '.versions["2.0.2"].dist'
{
  "integrity": "sha512-Xf0nWe6RseziFMu+Ap9biiUbmplq6S9/p+7w7YXP/JBHhrUDDUhwa+vANyubuqfZWTveU//DYVGsDG7RKL/vEw==",
  "shasum": "89a7fdd938261267318eafe14f9c32e598c36909",
  "tarball": "https://registry.npmjs.org/require-from-string/-/require-from-string-2.0.2.tgz",
  "fileCount": 4,
  "unpackedSize": 3422
}

$ curl -s https://registry.npmjs.org/require-from-string/-/require-from-string-2.0.2.tgz | shasum
89a7fdd938261267318eafe14f9c32e598c36909  -

$ curl -s https://registry......./require-from-string | jq '.versions["2.0.2"].dist'
{
  "integrity": "sha512-Xf0nWe6RseziFMu+Ap9biiUbmplq6S9/p+7w7YXP/JBHhrUDDUhwa+vANyubuqfZWTveU//DYVGsDG7RKL/vEw==",
  "shasum": "89a7fdd938261267318eafe14f9c32e598c36909",
  "tarball": "https://registry....../r/require-from-string/_attachments/require-from-string-2.0.2.tgz",
  "fileCount": 4,
  "unpackedSize": 3422
}

$ curl -s https://registry....../r/require-from-string/_attachments/require-from-string-2.0.2.tgz | shasum
9fce58558db06add0e02da5771ac3b6cd93881a9  -

@davidlukerice FYI we were finally able to fix this issue on our private registry. It looks like somehow the require-from-string tarball was changed at some point. require-from-string-2.0.2.tgz
The public NPM registry does not guarantee sameness for tarballs. So if your private registry fetched the tarball when it was first published, but then the tarball was since updated, your private registry will be out of date. It seems like a fix would be to have the private registry detect that the sha has changed and so fetch the new tarball to match.
We just manually uploaded the newer tarball to our private repo.


[Snyk] Upgrade org.apache.commons:commons-text from 1.9 to 1.10.0

This PR was automatically created by Snyk using the credentials of a real user.Snyk has created this PR to upgrade org.apache.commons:commons-text from 1.9 to 1.10.0.
:information_source: Keep your dependencies up-to-date. This makes it easier to fix existing vulnerabilities and to more quickly identify and fix newly disclosed vulnerabilities when they affect your project.

The recommended version is 1 version ahead of your current version.
The recommended version was released 3 months ago, on 2022-09-24.

The recommended version fixes:

Severity
Issue
PriorityScore (*)
Exploit Maturity

Arbitrary Code Execution SNYK-JAVA-ORGAPACHECOMMONS-3043138
726/1000  Why? Proof of Concept exploit, Has a fix available, CVSS 8.1
Proof of Concept

(*) Note that the real score may have changed since the PR was raised.

Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open upgrade PRs.
For more information:
🧐 View latest project report
🛠 Adjust upgrade PR settings
🔕 Ignore this dependency or unsubscribe from future upgrade PRs

Coverage: 82.644%. Remained the same when pulling 04105bcec5f12faf23643b3c46c2f1fdefa0f4e6 on snyk-upgrade-b7e9c57170f8b3e8736245f01bd30f36 into 73cf3fa50ffded237ada96ff6fe06bb7dcceba0a on main.


[question] Applying Dopamine to MultiAgent Environments

I like the compact implementations of Dopamine, and was looking to apply it to the next step to ALE, which is the multi-agent ALE from PettingZoo. As far as I have searched on this issue, Dopamine does not support multiple agents as per #23. However, the Hanabi Learning Environment [paper] [code] [post] attempts to solve a multiagent problem, and the Rainbow Agent
provided is also based on Dopamine. The problem is that I am not entirely sure that multi-agent environments that use vectorized environments, where each agent is in a separate environment on its own but all agents share the observation space, can use Dopamine's Rainbow Agents off-the-shelf.
My question is:

If I want to adapt Dopamine's Agents to use in a Petting Zoo environment, should I look towards Hanabi's Rainbow Agent?
If not, what changes might be required in Dopamine to make it work in a multi-agent setting? I can attempt to do this if the contributors can provide some guideline. A reference issue is perhaps #110 (as mentioned, using one environment makes it slow. Libraries like Stable Baselines or RLlib which support vector environments are supposedly much faster).

As a side note, I have gone through this and the associated colab but not sure if this is going down the same path as I want.
Thank you.

hi,
modifying dopamine for multi-agent settings is do-able, but the specifics
will vary depending on your use case. if you want to have all agents
running on the same environment with shared observation spaces, i would
suggest modifying run_experiment.py so you create and maintain multiple
agents there.
On Sun, May 2, 2021 at 8:50 AM Farrukh Ali @.***> wrote:

I like the compact implementations of Dopamine, and was looking to apply
it to the next step to ALE, which is the multi-agent ALE from PettingZoo
https://www.pettingzoo.ml/atari. As far as I have searched on this
issue, Dopamine does not support multiple agents as per #23
https://github.com/google/dopamine/issues/23. However, the Hanabi
Learning Environment [paper https://arxiv.org/pdf/1902.00506.pdf] [code
https://github.com/deepmind/hanabi-learning-environment] [post
http://www.marcgbellemare.info/blog/a-cooperative-benchmark-announcing-the-hanabi-learning-environment/]
attempts to solve a multiagent problem, and the Rainbow Agent
https://github.com/deepmind/hanabi-learning-environment/blob/master/hanabi_learning_environment/agents/rainbow/rainbow_agent.py
provided is also based on Dopamine. However, I am not entirely sure that
multi-agent environments that use vectorized environments, where each agent
is in a separate environment on its own but all agents share the
observation space, can use Dopamine's Rainbow Agents off-the-shelf.
My question is:

If I want to adapt Dopamine's Agents to use in a Petting Zoo
environment, should I look towards Hanabi's Rainbow Agent?
If not, what changes might be required in Dopamine to make it work
in a multi-agent setting? I can attempt to do this if the contributors can
provide some guideline. A reference issue is perhaps #110
https://github.com/google/dopamine/issues/110 (as mentioned, using
one environment makes it slow. Libraries like Stable Baselines or RLlib
which support vector environments are supposedly much faster).

As a side note, I have gone through this
https://github.com/google/dopamine/tree/master/docs#modifying-and-extending-agents
and the associated colab
https://colab.research.google.com/github/google/dopamine/blob/master/dopamine/colab/agents.ipynb
but not sure if this is going down the same path as I want.
Thank you.
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/google/dopamine/issues/175, or unsubscribe
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.

thanks @psc-g , is there a resource already available that I could use to modify run_experiment.py? I have gone through the Dopamine Colabs but I don't think its there.

we don't have any examples yet, there are likely forks that have done
something similar.
perhaps this will be useful, it is some code i wrote for a paper of mine
https://arxiv.org/abs/1911.09291 where i modified the Runner to fill in a
replay buffer and then generate some visualizations:
https://github.com/google-research/google-research/blob/master/bisimulation_aaai2020/dopamine/run_experiment.py
hope this helps!
On Thu, May 6, 2021 at 9:34 AM Farrukh Ali @.***> wrote:

thanks @psc-g https://github.com/psc-g , is there a resource already
available that I could use to modify run_experiment.py? I have gone through
the Dopamine Colabs
https://github.com/google/dopamine/tree/master/dopamine/colab but I
don't think its there.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/google/dopamine/issues/175#issuecomment-833527025,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AE3CCMN5I3N6ZRG5BAC2KZTTMKLFNANCNFSM437L4GTA
.

thank you for the reference @psc-g,  I will explore it some time soon. Following what you said, I will try to create two Runners here and replace the atari_lib.create_atari_environment with a different gym-compatible multi-agent environment, and go on from there.
I am going to close this issue now but if I build on this or if you come across some Dopamine based multi-agent implementation, please do share.
Thanks!


Added trigger hide to tabs

Added a trigger('hide') to oldTab so It would be possible to hook to the tab hide event in the same way you can hook to the show event now.

Cool, thanks!


Cache bugfix + coverage bump

Current coverage is 52.60% (diff: 41.93%)

Merging #142 into master will decrease coverage by 0.03%

@@             master       #142   diff @@
==========================================
  Files            99         99
  Lines          4990       4988     -2
  Methods           0          0
  Messages          0          0
  Branches          0          0
==========================================
- Hits           2627       2624     -3
- Misses         2121       2128     +7
+ Partials        242        236     -6

Powered by Codecov. Last update 2db53f2...8e4ec30

Merged into #141


tracker update: JAX, kiwisolver, rpds-py updates, add Pythran

Since it's getting holiday time and this is a minor update that I'm pretty sure is correct, I'll self-merge here.


Mide

Hi @mide358,
You did great with the web version :). However, I think you need to do some fixes on the mobile version.
The tabs, below the navs, in the header section is a little out of place on mobile view. Try adding max-width to the carousel container to resolve this.
Also, kindly pull develop branch into your local machine and merge it with your work (mide branch), try to reconcile any merging-conflicts before creating a pull request on (develop branch).
Please let's ensure all pull requests are made into develop branch and not main branch.
CC. @misspee007


$translateChangeSuccess fires in tests

Subject of the issue
I'm writing tests and have $rootScope.on('$translateChangeSuccess') but it always fires even i dont change the language so test always misleading. Started with version 2.9.2
Your environment

version of angular-translate 11.1.1
version of angular 1.5
which browser and its version chrome

Steps to reproduce
Tell us how to reproduce this issue. Please provide a working demo, you can use this template as a base.
Expected behaviour
Should not fire $translateChangeSuccess in tests
Actual behaviour
always fires $translateChangeSuccess

As written in the template for the issue: Please provide a working code example. Otherwise it is hard to guess the issue. Thanks.

Hello,
I'm closing this issue due inactivity. We have asked for additional details, but you could not helped us. Therefore we close this issue as not reproducible.
If you still have an issue, please create a new issue because we cannot be sure to track closed issues.


Add support for WebWorker with worker-loader (#3660)

Use worker-loader to turn any file that ends with .worker.js into a WebWorker.
Closes #3660
Here is the sample WebWorker code I used to test this:
// hello.worker.js

let helloInterval;

const sayHello = () => {
  self.postMessage({ message: 'Hello' });
};

self.addEventListener('message', event => {
  if (event.data.run === true) {
    self.postMessage({ status: 'Worker started' });
    helloInterval = setInterval(sayHello, 1000);
  }

  if (event.data.run === false) {
    self.postMessage({ status: 'Worker stopped' });
    clearInterval(helloInterval);
  }
});

// index.js

import React from 'react';
import ReactDOM from 'react-dom';
import './index.css';
import App from './App';
import * as serviceWorker from './serviceWorker';
import HelloWorker from './hello.worker.js';

ReactDOM.render(<App />, document.getElementById('root'));

// If you want your app to work offline and load faster, you can change
// unregister() to register() below. Note this comes with some pitfalls.
// Learn more about service workers: http://bit.ly/CRA-PWA
serviceWorker.unregister();

const helloWorker = new HelloWorker();
let messageCount = 0;

helloWorker.postMessage({ run: true });

helloWorker.onmessage = event => {
  if (event.data.status) {
    console.log('STATUS', event.data.status);
  }

  if (event.data.message) {
    messageCount += 1;
    console.log('MESSAGE', event.data.message);

    if (messageCount >= 5) {
      helloWorker.postMessage({ run: false });
    }
  }

}

This looks good to be merged. I hope we can use this soon to fix janks 👍

Awesome. Looking forward to this getting merged!

Nice!
Might be helpful to include notes on use-case, including limitations. As examples,

handling overlapping tasks for multiple workers, or one or more workers per component and one or more components rendered
worker termination, e.g., per task or on unmount?

Cool, the changes work in my current project perfectly @iansu, looking forward to this being merged

Waiting for this also 🤞

Looking forward to having this PR resolved and merged :1st_place_medal: