Dracula themed Aurora theme

New Theme?
Ok i made a colortheme. For keyboards using aurora.
Its scewed because keyboard LEDs don't emit the same colours as a a pcscreen.
Existing Theme?
They dont exist yet
Theme at https://github.com/NicTanghe/Aurora-Dracula/blob/master/README.md

This is awesome 🤯, I didn't know about this tool!

I just sent you an invitation to join the organization.
I also cloned your repository for Dracula's organization, so you can go ahead and delete or archive yours:

Your repository.
New repository.

Thanks for building this! 🎉

hello,
No idea how to c the invite or join the org.

Hi 👋🏻, are you still interested in the project? 🫡


TSI_INTERNAL_ERROR

Please answer these questions before submitting your issue.
What version of gRPC and what language are you using?
master branch (commit b414268), C++
What operating system (Linux, Windows, …) and version?
Linux (Debian 9.0)
What runtime / compiler are you using (e.g. python version or version of gcc)
g++ 6.3.0
What did you do?
If possible, provide a recipe for reproducing the error. Try being specific and include code snippets if helpful.
Tried sending an authenticated RPC to GoogleGenomics. Channel credentials were set as SSLCredentials and ClientContext had AccessTokenCredentials. Same code was working at commit 139072f of grpc.
What did you expect to see?
Successful RPC response.
What did you see instead?
E0726 06:31:34.623081628    6909 ssl_transport_security.c:822] Sending protected frame to ssl failed with -1
E0726 06:31:34.623131071    6909 secure_endpoint.c:177]      Decryption error: TSI_INTERNAL_ERROR
Make sure you include information that can help us debug (full error message, exception listing, stack trace, logs).
Anything else we should know about your project / environment?

C++ code to initialize the client context is at https://github.com/siddharthab/GoogleGenomics/blob/master/src/client-common.cc

Update: My code runs fine on Ubuntu 17.04.
I suspect the difference is because Ubuntu and Debian come with different openssl versions.

I have two Manjaro Linux (Arch-based) with grpc and googleapis installed, on the first one I installed grpc 1.3.1 (latest at the time) and my speech project worked, recently I installed version 1.5.0-dev (latest git again) and I get these errors:
E0804 09:27:47.119648416    1418 ssl_transport_security.c:822] Sending protected frame to ssl failed with -1
E0804 09:27:47.119802060    1418 secure_endpoint.c:177]      Decryption error: TSI_INTERNAL_ERROR

I tried to downgrade but 1.3.1 does not compile anymore due to openssl bumping to v1.1.0. I didn't succeed in force-using openssl-1.0 instead, maybe someone more knowledgeable will succeed.

This issue is because grpc is not compatible with the latest version of openssl (1.1.0f) released in Debian systems. There are three options:

Wait for grpc to support the latest version of openssl.
Downgrade openssl on your machine to a supported version, e.g. 1.0.2g.
Build grpc with boringssl, like this:

    git clone -b $(curl -L https://grpc.io/release) https://github.com/grpc/grpc
    cd grpc
    git submodule update --init
    [sudo] make HAS_SYSTEM_OPENSSL_NPN=false HAS_SYSTEM_OPENSSL_ALPN=false install


Optimal number of CPU cores

Do you know if there is an optimal number of CPUs to run baybe on, or should I just use the max number of cores available?

Hi @brandon-holt. I see no reason not to use whatever is available. But perhaps I'm missing an important part of the question? 🙃


1Password extension conflicts with navigator.credentials.get

Starting around version 2.14.0 the 1Password extension is capturing all of the get requests and not passing them onto other scripts such as CHAPI. This is likely bad behaviour on their behalf..

We are starting to hear from more people in the field that are hitting this issue. We really need to push a fix to detect and re-patch (or something equivalent). Let's get back in touch w/ the 1Password folks to see what their plans are to ensure this doesn't happen in future releases.

We just started seeing errors related to the Credential Management API: CHAPI polyfill is breaking for us when the browser already has navigator.credentials.get()
https://developer.mozilla.org/en-US/docs/Web/API/CredentialsContainer/get
Have y'all started to run into this?

Yes, #42 is the proposed fix for this -- we just need to do some more testing and then deploy it. cc: @jameseaster

I've tested #42 and it looks good to go!


JSONHTTPClient and JSONAPI return the session

I want to cancel the network request after the view controller dealloc, but the JSONAPI do not return the session.
I hope you can add it.

The HTTP functionality built into JSONModel is very basic and does not offer any advanced features. This is by design.
If you need to have any further control over the requests, you should use another framework, like AFNetworking or NSURLSession. JSONModel can be used with those for the (de)serialization part of the request.

I know it. But I think the return value is a basic feature, the change is simple.

It's not going to happen. You're not meant to be doing anything complex with JSONModel's HTTP support. It does not aim to provide anything comprehensive.
The only reason it exists is as a convenience to people who are just starting out to reduce the barrier to entry of using JSONModel. If that wasn't the case, we wouldn't include the classes at all.


Verify that instance is VRPLIB format

We should verify that an instance is in VRPLIB format. I don't know yet what needs to be checked (is there a minimum requirement?), but that's something we can figure out along the way.

The minimum requirements of a VRPLIB file can be defined by looking at each line:

A line contains a colon, separating the keyword and value, or
A line represents a section name prepended by SECTION, or
A line contains EOF, or
A line contains data, which can for now be anything, but this is only allowed between two consecutive sections OR a section and EOF.


Added the microservice of vLLM

Description
This PR mainly updates the microservice wrapper for the vllm to align with the tgi, rename the ray backend service, and adds the vllm and ray introduction in the readme.
Issues
n/a.
Type of change
List the type of change like below. Please delete options that are not relevant.

[x] New feature (non-breaking change which adds new functionality)

wrapped the vllm with the langchain microservice for aligning with tgi microservice.
updated the llms readme with the vllm and ray introduction.
fixed the vllm readme and docker script with huggingface API token useage.

[x] Breaking change (fix or feature that would break existing design and interface

rename the ray serve from "rayllm" to "ray_serve" to avoid the confusion of the ray implement based on the "ray serve" instead of "ray llm"

Dependencies
No newly introduced 3rd party dependency.
Tests
This PR is tested in the Gaudi2 server with:
2 sockers Intel(R) Xeon(R) Platinum 8368 CPU @ 2.40GHz
8 Gaudi nodes, HL-SMI Version: hl-1.14.0-fw-<IP_ADDRESS> Driver Version: 1.14.0-9e8ecf8
which is tested well in the above env:

vLLM backend serving

Langchain vLLM serving

Please help review, and I expect your invaluable feedback. Thanks. @Jian-Zhang @lvliang-intel @xuechendi

The PR has fixed the above comments and is ready to merge. Please help review. Thanks. @lvliang-intel @hshen14 @Jian-Zhang

from the PR title, only LLM microservice based on vLLM was added. but in the code, you in fact included Ray Serve version, right? and it's better to move 'text-generation/ray_serve/docker' to upper level like what we did in vLLM and other examples.
another question is why there is a requirements.txt in 'text-generation/ray_serve/docker' folder? moving it to dockerfile is feasible?

@ftian1 Thanks for your comments. I exactly renamed the ray serve name instead of changing its version, did not implement the ray serve microservice in this PR, and will implement it in the next PR. The code in "docker" folder of the ray_serve was self-implemented docker image and just aimed to launch the ray serve llm engine unlike that the vLLM/TGI can build the docker from official github.
The requirements.txt of ray serve was the necessary file to build the ray serve engine image instead of the microservice of the ray langchain implementation, so I put it under the docker folder as before.

This PR is ready to merge. Would you please help check this PR? Thanks. @ftian1 @lvliang-intel


Package icons

Adds icons to the details pane and the package table. See screenshot below

Codecov Report

Merging #47 into master will not change coverage.
The diff coverage is 0%.

@@         Coverage Diff          @@
##           master   #47   +/-   ##
====================================
  Coverage      55%   55%
====================================
  Files          26    26
  Lines         720   720
  Branches       35    36    +1
====================================
  Hits          396   396
+ Misses        318   317    -1
- Partials        6     7    +1

Impacted Files
Coverage Δ

...selection/package-table/package-table.component.ts
58.82% <ø> (+1.17%)
:arrow_up:

...c/app/main/nav-menu/nav-menu/nav-menu.component.ts
90.47% <ø> (-0.44%)
:arrow_down:

...ction/package-details/package-details.component.ts
90% <0%> (-4.74%)
:arrow_down:

Continue to review full report at Codecov.

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[CELEBORN-1489] Update Flink support with authentication support

What changes were proposed in this pull request?
Fix authentication support for Apache Flink.
Why are the changes needed?
Without these changes, Apache Flink applications fail when Celeborn cluster has authentication enabled.
Does this PR introduce any user-facing change?
Fixes authentication support for Apache Flink integration
How was this patch tested?
This is forward port + adaptation of changes we did internally (against 0.4) when testing Apache Flink applications against Celeborn cluster with authentication (and TLS) enabled.
Integration test has been updated to additionally test for Flink applications with authentication enabled in Celeborn cluster.

+CC @otterc, @SteNicholas, @RexXiong

+CC @venkata91

+CC @venkata91

Thanks for tagging me here. Will review the PR shortly.

Thanks @venkata91, @RexXiong ... have addressed the comments.

Thanks @venkata91, @RexXiong !

Let me backport this to 0.5 branch as well @RexXiong


purchase list - ability to filter on own vs other purchases  / add details

[ ] should be able to pass a filter for your purchases vs someone purchasing your content
[ ] show more transaction details in output

Per Lex's findings, purchase list only handles outgoing purchases and not incoming. What API do we want to use for incoming ones? If it's txo list, we need details added to the purchase.

Yes, it should be txo_list. Ideally I could pass a claim id of a stream or channel and get the results accordingly.

Also consider https://github.com/lbryio/lbry-sdk/issues/2939 as part of this. Not sure if this should be a new API or just part of resolve - probably the latter with a flag similar to other examples.

Also for supports that are signed

First call to develop is support_xxx, which will:

Take a URL or claim id
Sum the amount staked by identities, as well as amount staked by anonymous users

Second is to develop APIs that would allow the creation of UIs that let me see my supports aggregated by claim and use support_abandon to manage the amounts.

Summing supports historically has some challenges with regards to unlocking and history, @jackrobison will propose specific design. First step will be to get signing information into txo_list

@lyoshenka wants to be involved in this, will discuss with you


Write npm compile github actions job for /Mail, /ProbeAPI,  '/Home, /Licensing`

Please refer to this issue: https://github.com/OneUptime/app/issues/19 <- This should be completed first.
Once you're done with issue #19. We can do the same for /Mail, /ProbeAPI, '/Home, /Licensing` projects in the repo.

@munezerobagira you can also do this for CommonServer. I've fixed all the compiler errors.


cranelift-fuzzgen fuzzbug: libFuzzer: out-of-memory (malloc(3221225472))

👋 Hey, cranelift-fuzzgen reported this today when I rebased some other work on top of main. This is probably also on OSS-Fuzz I would guess.
Reverting 562bb25360a2f366a482e15fc148bab7267a9266 makes it go away, so cc: @adambratschikaye .
Edit: I should clarify, the input below crashes on main

Test case input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`cargo +nightly fuzz fmt` output
Unfortunately this fails at a stage where we can't generate a nice function.
afonso@DESKTOP-VSTS4BC:~/git/wasmtime/fuzz$ cargo fuzz fmt --no-default-features cranelift-fuzzgen artifacts/cranelift-fuzzgen/oom-ed
0e2a716f0af472061144dc347e6ea40156028f
Error: failed to run `cargo fuzz fmt` on input: artifacts/cranelift-fuzzgen/oom-ed0e2a716f0af472061144dc347e6ea40156028f

Caused by:
    Fuzz target 'cranelift-fuzzgen' exited with failure when attemping to debug formatting an interesting input that we discovered!

    Artifact: artifacts/cranelift-fuzzgen/oom-ed0e2a716f0af472061144dc347e6ea40156028f

    Command: "cargo" "run" "--manifest-path" "/home/afonso/git/wasmtime/fuzz/Cargo.toml" "--target" "x86_64-unknown-linux-gnu" "--release" "--no-default-features" "--bin" "cranelift-fuzzgen" "--" "-artifact_prefix=/home/afonso/git/wasmtime/fuzz/artifacts/cranelift-fuzzgen/" "artifacts/cranelift-fuzzgen/oom-ed0e2a716f0af472061144dc347e6ea40156028f"

    Status: exit status: 71

    === stdout ===

    === stderr ===
        Finished release [optimized] target(s) in 0.13s
         Running `/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen -artifact_prefix=/home/afonso/git/wasmtime/fuzz/artifacts/cranelift-fuzzgen/ artifacts/cranelift-fuzzgen/oom-ed0e2a716f0af472061144dc347e6ea40156028f`
    INFO: Running with entropic power schedule (0xFF, 100).
    INFO: Seed:<PHONE_NUMBER>
    INFO: Loaded 1 modules   (834566 inline 8-bit counters): 834566 [0x55cbaf535a10, 0x55cbaf601616),
    INFO: Loaded 1 PC tables (834566 PCs): 834566 [0x55cbaf601618,0x55cbb02bd678),
    /home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen: Running 1 inputs 1 time(s) each.
    Running: artifacts/cranelift-fuzzgen/oom-ed0e2a716f0af472061144dc347e6ea40156028f
    ==28989== ERROR: libFuzzer: out-of-memory (malloc(3221225472))
       To change the out-of-memory limit use -rss_limit_mb=<N>

        #0 0x55cbac692091 in __sanitizer_print_stack_trace /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_stack.cpp:87:3
        #1 0x55cbaecedcf0 in fuzzer::PrintStackTrace() (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3d37cf0) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #2 0x55cbaecac4fb in fuzzer::Fuzzer::HandleMalloc(unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf64fb) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #3 0x55cbaecac565 in fuzzer::MallocHook(void const volatile*, unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf6565) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #4 0x55cbac699517 in __sanitizer::RunMallocHooks(void const*, unsigned long) /rustc/llvm/src/llvm-project/compiler-rt/lib/sanitizer_common/sanitizer_common.cpp:316:5
        #5 0x55cbac608554 in __asan::Allocator::Allocate(unsigned long, unsigned long, __sanitizer::BufferedStackTrace*, __asan::AllocType, bool) /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_allocator.cpp:600:5
        #6 0x55cbac608999 in __asan::Allocator::Reallocate(void*, unsigned long, __sanitizer::BufferedStackTrace*) /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_allocator.cpp:715:21
        #7 0x55cbac6088b5 in __asan::asan_realloc(void*, unsigned long, __sanitizer::BufferedStackTrace*) /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_allocator.cpp:982:34
        #8 0x55cbac688437 in realloc /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_malloc_linux.cpp:86:10
        #9 0x55cbad086aeb in alloc::raw_vec::finish_grow::h6d4553f32daa153e (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x20d0aeb) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #10 0x55cbad090f14 in alloc::raw_vec::RawVec$LT$T$C$A$GT$::reserve_for_push::h499028c3dd286b33 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x20daf14) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #11 0x55cbad0d249a in cranelift_frontend::ssa::SSABuilder::use_var_nonlocal::hee02795ddf603a21 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x211c49a) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #12 0x55cbad0da504 in cranelift_frontend::ssa::SSABuilder::run_state_machine::hd2fb8dde6ae72d84 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x2124504) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #13 0x55cbad0d44a6 in cranelift_frontend::ssa::SSABuilder::seal_one_block::h22f985eda60a38e6 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x211e4a6) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #14 0x55cbad0bc726 in cranelift_frontend::frontend::FunctionBuilder::seal_all_blocks::h1fdc4a95b4009fbd (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x2106726) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #15 0x55cbac85aaa8 in cranelift_fuzzgen::function_generator::FunctionGenerator::generate::h5623324bba84b65d (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18a4aa8) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #16 0x55cbac8644d8 in cranelift_fuzzgen::FuzzGen::generate_func::h08ccf70894f31b47 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18ae4d8) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #17 0x55cbac864abb in cranelift_fuzzgen::FuzzGen::generate_test::h1fe6a758e6526799 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18aeabb) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #18 0x55cbac85f243 in _$LT$cranelift_fuzzgen..TestCase$u20$as$u20$arbitrary..Arbitrary$GT$::arbitrary::h88f8532552f2ecfb (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18a9243) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #19 0x55cbac74f3cf in rust_fuzzer_test_input (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x17993cf) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #20 0x55cbaeca9cd8 in __rust_try (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf3cd8) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #21 0x55cbaeca9078 in LLVMFuzzerTestOneInput (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf3078) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #22 0x55cbaecacc2c in fuzzer::Fuzzer::ExecuteCallback(unsigned char const*, unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf6c2c) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #23 0x55cbaecbd059 in fuzzer::RunOneTest(fuzzer::Fuzzer*, char const*, unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3d07059) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #24 0x55cbaecc6852 in fuzzer::FuzzerDriver(int*, char***, int (*)(unsigned char const*, unsigned long)) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3d10852) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #25 0x55cbac606c16 in main (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x1650c16) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
        #26 0x7fa22e384082 in __libc_start_main /build/glibc-SzIz7B/glibc-2.31/csu/../csu/libc-start.c:308:16
        #27 0x55cbac606d7d in _start (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x1650d7d) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)

    SUMMARY: libFuzzer: out-of-memory

Stack trace or other relevant details
     Running `/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen -artifact_prefix=/home/afonso/git/wasmtime/fuzz/artifacts/cranelift-fuzzgen/ artifacts/cranelift-fuzzgen/oom-ed0e2a716f0af472061144dc347e6ea40156028f`
INFO: Running with entropic power schedule (0xFF, 100).
INFO: Seed:<PHONE_NUMBER>
INFO: Loaded 1 modules   (834566 inline 8-bit counters): 834566 [0x557e2aeaba10, 0x557e2af77616),
INFO: Loaded 1 PC tables (834566 PCs): 834566 [0x557e2af77618,0x557e2bc33678),
/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen: Running 1 inputs 1 time(s) each.
Running: artifacts/cranelift-fuzzgen/oom-ed0e2a716f0af472061144dc347e6ea40156028f
==28975== ERROR: libFuzzer: out-of-memory (malloc(3221225472))
   To change the out-of-memory limit use -rss_limit_mb=<N>

    #0 0x557e28008091 in __sanitizer_print_stack_trace /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_stack.cpp:87:3
    #1 0x557e2a663cf0 in fuzzer::PrintStackTrace() (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3d37cf0) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #2 0x557e2a6224fb in fuzzer::Fuzzer::HandleMalloc(unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf64fb) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #3 0x557e2a622565 in fuzzer::MallocHook(void const volatile*, unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf6565) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #4 0x557e2800f517 in __sanitizer::RunMallocHooks(void const*, unsigned long) /rustc/llvm/src/llvm-project/compiler-rt/lib/sanitizer_common/sanitizer_common.cpp:316:5
    #5 0x557e27f7e554 in __asan::Allocator::Allocate(unsigned long, unsigned long, __sanitizer::BufferedStackTrace*, __asan::AllocType, bool) /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_allocator.cpp:600:5
    #6 0x557e27f7e999 in __asan::Allocator::Reallocate(void*, unsigned long, __sanitizer::BufferedStackTrace*) /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_allocator.cpp:715:21
    #7 0x557e27f7e8b5 in __asan::asan_realloc(void*, unsigned long, __sanitizer::BufferedStackTrace*) /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_allocator.cpp:982:34
    #8 0x557e27ffe437 in realloc /rustc/llvm/src/llvm-project/compiler-rt/lib/asan/asan_malloc_linux.cpp:86:10
    #9 0x557e289fcaeb in alloc::raw_vec::finish_grow::h6d4553f32daa153e (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x20d0aeb) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #10 0x557e28a06f14 in alloc::raw_vec::RawVec$LT$T$C$A$GT$::reserve_for_push::h499028c3dd286b33 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x20daf14) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #11 0x557e28a4849a in cranelift_frontend::ssa::SSABuilder::use_var_nonlocal::hee02795ddf603a21 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x211c49a) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #12 0x557e28a50504 in cranelift_frontend::ssa::SSABuilder::run_state_machine::hd2fb8dde6ae72d84 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x2124504) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #13 0x557e28a4a4a6 in cranelift_frontend::ssa::SSABuilder::seal_one_block::h22f985eda60a38e6 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x211e4a6) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #14 0x557e28a32726 in cranelift_frontend::frontend::FunctionBuilder::seal_all_blocks::h1fdc4a95b4009fbd (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x2106726) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #15 0x557e281d0aa8 in cranelift_fuzzgen::function_generator::FunctionGenerator::generate::h5623324bba84b65d (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18a4aa8) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #16 0x557e281da4d8 in cranelift_fuzzgen::FuzzGen::generate_func::h08ccf70894f31b47 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18ae4d8) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #17 0x557e281daabb in cranelift_fuzzgen::FuzzGen::generate_test::h1fe6a758e6526799 (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18aeabb) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #18 0x557e281d5243 in _$LT$cranelift_fuzzgen..TestCase$u20$as$u20$arbitrary..Arbitrary$GT$::arbitrary::h88f8532552f2ecfb (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x18a9243) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #19 0x557e280c53cf in rust_fuzzer_test_input (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x17993cf) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #20 0x557e2a61fcd8 in __rust_try (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf3cd8) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #21 0x557e2a61f078 in LLVMFuzzerTestOneInput (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf3078) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #22 0x557e2a622c2c in fuzzer::Fuzzer::ExecuteCallback(unsigned char const*, unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3cf6c2c) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #23 0x557e2a633059 in fuzzer::RunOneTest(fuzzer::Fuzzer*, char const*, unsigned long) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3d07059) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #24 0x557e2a63c852 in fuzzer::FuzzerDriver(int*, char***, int (*)(unsigned char const*, unsigned long)) (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x3d10852) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #25 0x557e27f7cc16 in main (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x1650c16) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)
    #26 0x7f3431318082 in __libc_start_main /build/glibc-SzIz7B/glibc-2.31/csu/../csu/libc-start.c:308:16
    #27 0x557e27f7cd7d in _start (/home/afonso/git/wasmtime/target/x86_64-unknown-linux-gnu/release/cranelift-fuzzgen+0x1650d7d) (BuildId: 4a8f4dbcbb26d9ca1ec67ad7b884b6273fa677d7)

SUMMARY: libFuzzer: out-of-memory
────────────────────────────────────────────────────────────────────────────────

Error: Fuzz target exited with exit status: 71

OSS-Fuzz found this eventually. The upstream report is at https://oss-fuzz.com/testcase-detail/5517981379854336.

I think we can close this since #4937 landed.

OSS-Fuzz also reported a second copy of this bug: the first was from the cranelift-icache fuzz target, and https://oss-fuzz.com/testcase-detail/4589725633085440 is from the cranelift-fuzzgen target.
I expect both are fixed by the revert but, for the record, OSS-Fuzz hasn't closed them yet.


NextJs RichText doesn't allow client side routing when content changes

Describe the Bug
The RichText component in sitecore-jss-nextjs includes code to allow internal links embedded within the rich text field to use client side routing (using the next/router). This is done by adding an event handler to the links when the component renders. This issue occurs when the content in the rich text field changes (e.g. load another page with the same page structure but different content in the rich text field). When the content changes, the useEffect() hook isn't re-run (as it has no dependancies) so the initializeLinks() function is never run on the new content. This means clicking on any internal link within the RichText field doesn't use client side routing and causes a full page load.
To Reproduce

Create a component that includes a rich text field and assign the initial content.
Update the content in the rich text field without causing a full page re-load (This could be by using the next/router to nav to another page or assigning new content to the rich text field, by using a button click for example)

Expected Behavior
The initializeLinks() would run on the embedded links within the rich text component when the components first mounts and also when the content is updated
Possible Fix
Add the hasText property to the dependancy array or the useeffect() hook
Provide environment information

Sitecore Version: 10.2 and 10.3
JSS Version: 20.0.1, 20.1.3 and 21.1.5
Browser Name and version: Chrome 113, Firefox 105 and Edge 113
Operating System and version (desktop or mobile): Windows Server 2016, 2019 and Windows 10

Raised PR 1503:
https://github.com/Sitecore/jss/pull/1503
as a proposed fix.


Added no-response bot and new labels

Hey all,
I need a few things from project maintainers to make this go through:

Add no response bot to the repo (https://github.com/apps/no-response)
Add a "pending" and "needs-response" to our labels
Tell the teams to use the "needs-response" for responses on ALL ISSUES, emails, bug reports, feature requests

Add a "pending" and "needs-response" to our labels

Does it only work with these tags?

No, it can be whatever we want!
"pending" would indicate any of the three (feature request, bug, email request that needs triage)
"needs-response" would be what the triager puts if it needs feedback. this is what the bot would look for to close automatically after 3 days right now.
We can adjust any of these things.

No, it can be whatever we want!
"pending" would indicate any of the three (feature request, bug, email request that needs triage)
"needs-response" would be what the triager puts if it needs feedback. this is what the bot would look for to close automatically after 3 days right now.

We are currently using [new-request] for all incoming tags. Can we use this instead of pending? How does the [needs-response] tag work?

So it appeared to me that “new-request” was just for new cities request. I
wanted to generalize to anything new. “new-request” will still exist, and
remain just for new cities
So when a reviewer goes in and determines that the issue needs more work,
they will add the “needs-response” label.
After 3 days, if there is no response from the original author, it will be
closed with a comment. If there is a comment from the orginal author it
will remove the “needs-response” label
On Sun, Jun 7, 2020 at 1:22 PM shortcircuit<EMAIL_ADDRESS>wrote:

No, it can be whatever we want!
"pending" would indicate any of the three (feature request, bug, email
request that needs triage)
"needs-response" would be what the triager puts if it needs feedback. this
is what the bot would look for to close automatically after 3 days right
now.
We are currently using [new-request] for all incoming tags. Can we use
this instead of pending? How does the [needs-response] tag work?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
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.

I added those tags

@bingbongle Thoughts?

@cjappl Thanks so much for setting this up!
That being said, I'm not super sure it addresses some of the core bottlenecks right now. The site has barely even been up for 3 days, so this number feels arbitrary to me. What about readjusting this implementation to automatically close blank issues, or email requests with x lines of content. (probably 1, 2, or 3 not really sure). I mean theoretically would need at least three for subject, body, and a single recipient.
Thoughts?

Yeah really good point.
Sounds good. Let me look into how possible that is.
I was chatting with someone else in the discord about things like that,
will keep you posted.
On Sun, Jun 7, 2020 at 2:03 PM bing bong<EMAIL_ADDRESS>wrote:

@cjappl https://github.com/cjappl Thanks so much for setting this up!
That being said, I'm not super sure it addresses some of the core
bottlenecks right now. The site has barely even been up for 3 days, so this
number feels arbitrary to me. What about readjusting this implementation to
automatically close blank issues, or email requests with x lines of
content. (probably 1, 2, or 3 not really sure). I mean theoretically would
need at least three for subject, body, and a single recipient.
Thoughts?
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https://github.com/defund12/defund12.org/pull/702#issuecomment-640279519,
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Thanks to @skullface for the help with this one!!

can you add a little bit more context here?
I feel like this over-complicates the issue a bit as I mentioned in my last comment.
@skullface, is there no way to immediately close out email template issues with no (or little) content???
"clean up" bots are nice to have, but ideally the response will be immediate. We don't want empty issues building up for 3 days - per the email template itself, we want them closed immediately. in my eyes the bot won't be effective, as we're already pretty much closing them out shortly after with a really minimal SLO.
@shortcircuit3 WDYT?

regardless though, really appreciate all of the work involved here. if we get this right, it will have a HUGE impact on the workflow - so totally worth mentioning that!

No problem @bingbongle. I definitely don't want something non-useful merged to the repo, so glad you're being discerning!
Here's an example of the comment, at least, on my repo:
https://github.com/cjappl/defund12.org/issues/2

Actually, closing this for now. May have found a new route! Sorry for the spam. I'll get this right on the next time around :)


Edit & play projects in browsers

To do this we need:

Setup a server to host assets and projects
Replace database query in projects
Support both touch events and mouse events
Implements tablet interface for browsers

Import and export project in .sjr format

With more than 10 days heavy development, I setup a server and here is a demo: https://scratchjr.drmer.net/project_1_play.html
I transfer all JavaScript codes to typescript, which made development much much easier.
Here is the repo: https://github.com/jndrm/scratchjr with following features:

[x] Full project editing
[x] Audio recording
[x] Take image from camera
[x] Switch camera if user's computer has multiple cameras
[x] Clone other user's project
[x] Export/Download .jsr file
[x] Import .jsr file

Well, since there is not any response for a long time, I'm going to shut the server down. If any one want to see the result, I'll reopen the server for you. Please don't hesitate to contact me!

Hi, I'm a new developer in this project. Our team planned to customize this project, but we don't know how to start it. Could you give me some tips. We sincerely appreciate it!
你好！我是大连理工大学的一名大三学生呢，我们团队想要根据这个开源项目定制出自己的项目，但不知道这个项目用了什么框架，也不知道从什么地方开始呢，能请学长赐教一下吗？如果学长能够帮助我们，真心十分感谢学长！~

Hi @jedlee6 , if you have any question, please open an issue for discussion.


"command-whitelist" config option does not initialize as an array

  if(((msg.member !== null && msg.member.permissions.has("MANAGE_GUILD")) || msg.channel.type === "dm" || getConfigVal("command-whitelist", msg.channel).length > 0) && getConfigVal("disable-admin-commands", msg.channel) !== true) {
                                                                                ^

TypeError: Cannot read property 'length' of undefined
    at parseCommand (/home/server/TriviaBot/triviabot.js:1176:153)
    at Object.Trivia.parse (/home/server/TriviaBot/triviabot.js:1463:5)
    at Client.global.client.on (/home/server/TriviaBot/shard.js:160:19)
    at Client.emit (events.js:193:13)
    at MessageCreateHandler.handle (/home/server/TriviaBot/node_modules/discord.js/src/client/websocket/packets/handlers/MessageCreate.js:9:34)
    at WebSocketPacketManager.handle (/home/server/TriviaBot/node_modules/discord.js/src/client/websocket/packets/WebSocketPacketManager.js:105:65)
    at WebSocketConnection.onPacket (/home/server/TriviaBot/node_modules/discord.js/src/client/websocket/WebSocketConnection.js:333:35)
    at WebSocketConnection.onMessage (/home/server/TriviaBot/node_modules/discord.js/src/client/websocket/WebSocketConnection.js:296:17)
    at WebSocket.onMessage (/home/server/TriviaBot/node_modules/ws/lib/event-target.js:120:16)
    at WebSocket.emit (events.js:193:13)

Workaround for the error: Go into config and add this line: "command-whitelist": []

Test pending


Added new GitIgnore, updated version to BotFramework v4, updated to 2017.4

Working with BotFramework v4.
Corrected GitIgnore and removed unneeded files
Updated unity version to current recommended version of 2017.4

Actually we messed up and this isnt working. Don't merge this yet until we fix.


Improvement on User experience

Purpose
Now user can put the OMElement values using the ballerina connector and JSON path must be used to pass the data.
Goals
Improve the user experience
Approach
Added new parameters for each argument and json files generated for uischema in-order to provide the user interface. New parameter values are taken as OMElement and they are converted BXml in the mediator and conversion can be done.
User stories

Summary of user stories addressed by this change>

Release note

Brief description of the new feature or bug fix as it will appear in the release notes

Documentation

Link(s) to product documentation that addresses the changes of this PR. If no doc impact, enter “N/A” plus brief explanation of why there’s no doc impact

Training

Link to the PR for changes to the training content in https://github.com/wso2/WSO2-Training, if applicable

Certification

Type “Sent” when you have provided new/updated certification questions, plus four answers for each question (correct answer highlighted in bold), based on this change. Certification questions/answers should be sent to<EMAIL_ADDRESS>and NOT pasted in this PR. If there is no impact on certification exams, type “N/A” and explain why.

Marketing

Link to drafts of marketing content that will describe and promote this feature, including product page changes, technical articles, blog posts, videos, etc., if applicable

Automation tests

Unit tests

Code coverage information

Integration tests

Details about the test cases and coverage

Security checks

Followed secure coding standards in http://wso2.com/technical-reports/wso2-secure-engineering-guidelines? no
Ran FindSecurityBugs plugin and verified report? no
Confirmed that this PR doesn't commit any keys, passwords, tokens, usernames, or other secrets? yes

Samples

Provide high-level details about the samples related to this feature

Related PRs

List any other related PRs

Migrations (if applicable)

Describe migration steps and platforms on which migration has been tested

Test environment

List all JDK versions, operating systems, databases, and browser/versions on which this feature/fix was tested

Learning

Describe the research phase and any blog posts, patterns, libraries, or add-ons you used to solve the problem.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.1 out of 2 committers have signed the CLA.:white_check_mark: KavinduZoysa:x: samithkavishkesamithkavishke seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.


Rename "DATICAL_SPERRORLOG" table to "LIQUIBASE__SPERRORLOG" when running Liquibase Pro with SQL Plus

Liquibase Version:
3.10.2
Database Vendor & Version:
Oracle
Description
When running and getting an error with Liquibase Pro with SQL Plus, Liquibase creates a table “DATICAL_SPERRORLOG”.
The naming of the table is inconsistent with our product name.  We can potentially call this table "LIQUIBASE__SPERRORLOG".
Steps To Reproduce
Run a changeSet that has a syntax error with the runWith:sqlplus attribute on an Oracle Database with Liquibase Pro.
List the steps to reproduce the behavior.
Liquibase
Actual Behavior
08:52:59.364 DEBUG [liquibase.executor.jvm.JdbcExecutor]: Executing with the 'jdbc' executor 08:52:59.364 INFO  [liquibase.executor.jvm.JdbcExecutor]: SELECT TABLE_NAME FROM ALL_TABLES WHERE OWNER='API_REPORTS' AND TABLE_NAME='DATICAL_SPERRORLOG' 08:52:59.605 DEBUG [liquibase.executor.jvm.JdbcExecutor]: Executing with the 'jdbc' executor 08:52:59.606 INFO  [liquibase.executor.jvm.JdbcExecutor]: CREATE TABLE API_REPORTS.DATICAL_SPERRORLOG (username VARCHAR(256), timestamp TIMESTAMP, script VARCHAR(256), identifier VARCHAR(256), message CLOB, statement CLOB) 08:52:59.857 DEBUG [liquibase.executor.jvm.JdbcExecutor]: 0 row(s) affected
Expected/Desired Behavior
The table bane should be associated with Liquibase.  For example:
08:52:59.364 DEBUG [liquibase.executor.jvm.JdbcExecutor]: Executing with the 'jdbc' executor 08:52:59.364 INFO  [liquibase.executor.jvm.JdbcExecutor]: SELECT TABLE_NAME FROM ALL_TABLES WHERE OWNER='API_REPORTS' AND TABLE_NAME='LIQUIBASE_SPERRORLOG' 08:52:59.605 DEBUG [liquibase.executor.jvm.JdbcExecutor]: Executing with the 'jdbc' executor 08:52:59.606 INFO  [liquibase.executor.jvm.JdbcExecutor]: CREATE TABLE API_REPORTS.LIQUIBASE_SPERRORLOG (username VARCHAR(256), timestamp TIMESTAMP, script VARCHAR(256), identifier VARCHAR(256), message CLOB, statement CLOB) 08:52:59.857 DEBUG [liquibase.executor.jvm.JdbcExecutor]: 0 row(s) affected
┆Issue is synchronized with this Jira Bug by Unito

Thanks @szandany for writing up this issue.  We will add it to the list of issues that we are processing.


Quick Panel - Black text on black background

When opening the quick panel, some of the text is black on a black background but looks fine when list item is highlighted.
I'm using the Golden theme with the Golden Black color scheme.
Love this theme by the way!

Is this fixed? I have same problem. :(


running h2ogpt on Macbook M1 error

Hello,
I've installed H2O on Macbook M1, when installing the dependencies I'm receiving the error bellow.
Ignoring torch: markers 'sys_platform != "darwin" and platform_machine != "arm64"' don't match your environment
Collecting InstructorEmbedding@ https://h2o-release.s3.amazonaws.com/h2ogpt/InstructorEmbedding-1.0.1-py3-none-any.whl (from -r reqs_optional/requirements_optional_langchain.txt (line 23))
  Using cached https://h2o-release.s3.amazonaws.com/h2ogpt/InstructorEmbedding-1.0.1-py3-none-any.whl (20 kB)
Collecting sentence_transformers_old@ https://h2o-release.s3.amazonaws.com/h2ogpt/sentence_transformers_old-2.2.2-py3-none-any.whl (from -r reqs_optional/requirements_optional_langchain.txt (line 26))
  Using cached https://h2o-release.s3.amazonaws.com/h2ogpt/sentence_transformers_old-2.2.2-py3-none-any.whl (125 kB)
Collecting llava@ https://h2o-release.s3.amazonaws.com/h2ogpt/llava-1.7.0.dev0-py3-none-any.whl (from -r reqs_optional/requirements_optional_langchain.txt (line 41))
  Using cached https://h2o-release.s3.amazonaws.com/h2ogpt/llava-1.7.0.dev0-py3-none-any.whl (87 kB)
Ignoring jq: markers 'platform_machine == "x86_64"' don't match your environment
ERROR: Cannot install torch==2.2.1 because these package versions have conflicting dependencies.

The conflict is caused by:
    The user requested torch==2.2.1
    The user requested (constraint) torch==2.3.1

To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip to attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts

I don't know if this error is impediment to run the application which I'm trying with the command bellow:
python generate.py --base_model=llama --model_path_llama=https://huggingface.co/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct-Q6_K_L.gguf?download=true --tokenizer_base_model=meta-llama/Meta-Llama-3.1-8B-Instruct --max_seq_len=8192
When trying to run I've this error:
soundfile, librosa, and wavio not installed, disabling STT
soundfile, librosa, and wavio not installed, disabling TTS
Using Model llama
Traceback (most recent call last):
  File "/Users/kapenge/Laboratories/_ai/frameworks/h2ogpt/generate.py", line 20, in <module>
    entrypoint_main()
  File "/Users/kapenge/Laboratories/_ai/frameworks/h2ogpt/generate.py", line 16, in entrypoint_main
    H2O_Fire(main)
  File "/Users/kapenge/Laboratories/_ai/frameworks/h2ogpt/src/utils.py", line 77, in H2O_Fire
    fire.Fire(component=component, command=args)
  File "/Users/kapenge/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/fire/core.py", line 141, in Fire
    component_trace = _Fire(component, args, parsed_flag_args, context, name)
  File "/Users/kapenge/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/fire/core.py", line 475, in _Fire
    component, remaining_args = _CallAndUpdateTrace(
  File "/Users/kapenge/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/fire/core.py", line 691, in _CallAndUpdateTrace
    component = fn(*varargs, **kwargs)
  File "/Users/kapenge/Laboratories/_ai/frameworks/h2ogpt/src/gen.py", line 2013, in main
    from gpt_langchain import get_embedding
  File "/Users/kapenge/Laboratories/_ai/frameworks/h2ogpt/src/gpt_langchain.py", line 48, in <module>
    from langchain_core.language_models.llms import aget_prompts, aupdate_cache
ImportError: cannot import name 'aget_prompts' from 'langchain_core.language_models.llms' (/Users/kapenge/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/langchain_core/language_models/llms.py)

Any hint?

I have these constraints:

I'm unclear why the constraint works (says has to be 2.3.1 for MAC) but the requirements.txt (that uses same constraint) thinks it needs to use 2.2.1.
Can you give more complete logs of the install?

I've deleted the env and I'm trying recreate it again... I'll update

I've created a brand-new conda environment, tried to follow the instructions and I got the same error.
Here complete install logs
❯ conda activate h2ogpt
❯ pip uninstall -y pandoc pypandoc pypandoc-binary
WARNING: Skipping pandoc as it is not installed.
WARNING: Skipping pypandoc as it is not installed.
WARNING: Skipping pypandoc-binary as it is not installed.
❯ pip install --upgrade pip
Requirement already satisfied: pip in /Users/kapenge/miniconda3/envs/h2ogpt/lib/python3.10/site-packages (24.0)
Collecting pip
  Using cached pip-24.2-py3-none-any.whl.metadata (3.6 kB)
Using cached pip-24.2-py3-none-any.whl (1.8 MB)
Installing collected packages: pip
  Attempting uninstall: pip
    Found existing installation: pip 24.0
    Uninstalling pip-24.0:
      Successfully uninstalled pip-24.0
Successfully installed pip-24.2
❯ python -m pip install --upgrade setuptools
Requirement already satisfied: setuptools in /Users/kapenge/miniconda3/envs/h2ogpt/lib/python3.10/site-packages (72.1.0)
❯ pip install -r requirements.txt --extra-index https://download.pytorch.org/whl/cpu -c reqs_optional/reqs_constraints.txt
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cpu
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Ignoring torch: markers 'sys_platform != "darwin" and platform_machine != "arm64"' don't match your environment
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Ignoring pypandoc_binary: markers 'platform_machine == "x86_64"' don't match your environment
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Collecting pytz>=2020.1 (from pandas>=2.0.2->-r requirements.txt (line 30))
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Collecting tzdata>=2022.7 (from pandas>=2.0.2->-r requirements.txt (line 30))
  Using cached tzdata-2024.1-py2.py3-none-any.whl.metadata (1.4 kB)
Collecting contourpy>=1.0.1 (from matplotlib>=3.7.1->-r requirements.txt (line 31))
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Collecting cycler>=0.10 (from matplotlib>=3.7.1->-r requirements.txt (line 31))
  Using cached cycler-0.12.1-py3-none-any.whl.metadata (3.8 kB)
Collecting fonttools>=4.22.0 (from matplotlib>=3.7.1->-r requirements.txt (line 31))
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Collecting coloredlogs (from optimum>=1.17.1->-r requirements.txt (line 44))
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Collecting pyarrow>=15.0.0 (from datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting pyarrow-hotfix (from datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting tzlocal!=3.*,>=2.0 (from APScheduler>=3.10.1->-r requirements.txt (line 48))
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Collecting exceptiongroup>=1.0.0rc8 (from pytest>=7.2.2->-r requirements.txt (line 59))
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Collecting pyphen (from textstat>=0.7.3->-r requirements.txt (line 62))
  Downloading pyphen-0.16.0-py3-none-any.whl.metadata (3.2 kB)
Requirement already satisfied: setuptools in /Users/kapenge/miniconda3/envs/h2ogpt/lib/python3.10/site-packages (from textstat>=0.7.3->-r requirements.txt (line 62)) (72.1.0)
Collecting et-xmlfile (from openpyxl>=3.1.2->-r requirements.txt (line 68))
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  Downloading ujson-5.10.0-cp310-cp310-macosx_11_0_arm64.whl.metadata (9.3 kB)
Collecting zstandard (from lm_dataformat>=0.0.20->-r requirements.txt (line 69))
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Collecting docopt (from bioc>=2.0->-r requirements.txt (line 70))
  Downloading docopt-0.6.2.tar.gz (25 kB)
  Preparing metadata (setup.py) ... done
Collecting torchvision (from sentence_transformers_old@ https://h2o-release.s3.amazonaws.com/h2ogpt/sentence_transformers_old-2.2.2-py3-none-any.whl->-r requirements.txt (line 75))
  Using cached https://download.pytorch.org/whl/cpu/torchvision-0.19.0-cp310-cp310-macosx_11_0_arm64.whl (1.7 MB)
Collecting distro<2,>=1.7.0 (from openai>=1.40.1->-r requirements.txt (line 91))
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Collecting jiter<1,>=0.4.0 (from openai>=1.40.1->-r requirements.txt (line 91))
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Collecting sniffio (from openai>=1.40.1->-r requirements.txt (line 91))
  Using cached sniffio-1.3.1-py3-none-any.whl.metadata (3.9 kB)
Collecting charset-normalizer<4,>=2 (from requests>=2.31.0->-r requirements.txt (line 93))
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Collecting idna<4,>=2.5 (from requests>=2.31.0->-r requirements.txt (line 93))
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Collecting certifi>=2017.4.17 (from requests>=2.31.0->-r requirements.txt (line 93))
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Collecting httpcore==1.* (from httpx>=0.24.1->-r requirements.txt (line 94))
  Using cached httpcore-1.0.5-py3-none-any.whl.metadata (20 kB)
Collecting aiohappyeyeballs>=2.3.0 (from aiohttp->datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting aiosignal>=1.1.2 (from aiohttp->datasets>=2.18.0->-r requirements.txt (line 45))
  Using cached aiosignal-1.3.1-py3-none-any.whl.metadata (4.0 kB)
Collecting attrs>=17.3.0 (from aiohttp->datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting frozenlist>=1.1.1 (from aiohttp->datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting multidict<7.0,>=4.5 (from aiohttp->datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting yarl<2.0,>=1.0 (from aiohttp->datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting async-timeout<5.0,>=4.0 (from aiohttp->datasets>=2.18.0->-r requirements.txt (line 45))
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Collecting jsonschema>=3.0 (from altair<6.0,>=4.2.0->gradio@ https://h2o-release.s3.amazonaws.com/h2ogpt/gradio-4.26.0-py3-none-any.whl->-r requirements.txt (line 8))
  Using cached jsonschema-4.23.0-py3-none-any.whl.metadata (7.9 kB)
Collecting toolz (from altair<6.0,>=4.2.0->gradio@ https://h2o-release.s3.amazonaws.com/h2ogpt/gradio-4.26.0-py3-none-any.whl->-r requirements.txt (line 8))
  Using cached toolz-0.12.1-py3-none-any.whl.metadata (5.1 kB)
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Collecting annotated-types>=0.4.0 (from pydantic>=2.0->gradio@ https://h2o-release.s3.amazonaws.com/h2ogpt/gradio-4.26.0-py3-none-any.whl->-r requirements.txt (line 8))
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Collecting pydantic-core==2.18.1 (from pydantic>=2.0->gradio@ https://h2o-release.s3.amazonaws.com/h2ogpt/gradio-4.26.0-py3-none-any.whl->-r requirements.txt (line 8))
  Using cached pydantic_core-2.18.1-cp310-cp310-macosx_11_0_arm64.whl.metadata (6.5 kB)
Collecting protobuf (from transformers[sentencepiece]<4.44.0,>=4.29.0->optimum>=1.17.1->-r requirements.txt (line 44))
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Collecting shellingham>=1.3.0 (from typer<1.0,>=0.9->typer[all]<1.0,>=0.9; sys_platform != "emscripten"->gradio@ https://h2o-release.s3.amazonaws.com/h2ogpt/gradio-4.26.0-py3-none-any.whl->-r requirements.txt (line 8))
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Collecting rich>=10.11.0 (from typer<1.0,>=0.9->typer[all]<1.0,>=0.9; sys_platform != "emscripten"->gradio@ https://h2o-release.s3.amazonaws.com/h2ogpt/gradio-4.26.0-py3-none-any.whl->-r requirements.txt (line 8))
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WARNING: typer 0.12.3 does not provide the extra 'all'
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  Using cached humanfriendly-10.0-py2.py3-none-any.whl.metadata (9.2 kB)
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Collecting mpmath<1.4,>=1.1.0 (from sympy->torch==2.3.1->-r requirements.txt (line 21))
  Using cached https://download.pytorch.org/whl/mpmath-1.3.0-py3-none-any.whl (536 kB)
INFO: pip is looking at multiple versions of torchvision to determine which version is compatible with other requirements. This could take a while.

The conflict is caused by:
    The user requested torch==2.2.1
    The user requested (constraint) torch==2.3.1

To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip to attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts

Tried the container option with no luck at all, at this moment.
changed this part of the build as the document suggest.
# if building for CPU, would remove CMAKE_ARGS and avoid GPU image as base image
# Choose llama_cpp_python ARGS for your system according to [llama_cpp_python backend documentation](https://github.com/abetlen/llama-cpp-python?tab=readme-ov-file#supported-backends), e.g. for CUDA:
# export GGML_CUDA=1
# export CMAKE_ARGS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=all"
# for Metal MAC M1/M2 comment out above two lines and uncomment out the below line
export CMAKE_ARGS="-DLLAMA_METAL=on"
export FORCE_CMAKE=1

Build Error
❯ docker build -t h2ogpt .
[+] Building 2.4s (9/13)                                                                                docker:desktop-linux
 => [internal] load build definition from Dockerfile                                                                                0.0s
 => => transferring dockerfile: 1.15kB                                                                                0.0s
 => [internal] load metadata for docker.io/nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04                                                                               2.3s
 => [internal] load .dockerignore                                                                                0.0s
 => => transferring context: 236B                                                                                0.0s
 => CANCELED [1/9] FROM docker.io/nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04@sha256:db71d4ff90d59028b6d364df7400ea65601d673b96a49cf81e7cda85cf7cbc31                0.0s
 => => resolve docker.io/nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04@sha256:db71d4ff90d59028b6d364df7400ea65601d673b96a49cf81e7cda85cf7cbc31                         0.0s
 => => sha256:f68369b047ebfe2343393aae2a6996206e0bacf574c543685bebd92f55f59267 16.34kB / 16.34kB                                                                     0.0s
 => => sha256:db71d4ff90d59028b6d364df7400ea65601d673b96a49cf81e7cda85cf7cbc31 743B / 743B                                                                           0.0s
 => => sha256:9f8fb265f5a9d3188a0d3ad13288b06edaf7e89a7dc2aaa89b732a1e57071627 2.84kB / 2.84kB                                                                       0.0s
 => [internal] load build context                                                                                0.0s
 => => transferring context: 38.15kB                                                                                0.0s
 => CACHED [2/9] WORKDIR /workspace                                                                                0.0s
 => CACHED [3/9] COPY . /workspace/                                                                                0.0s
 => CACHED [4/9] COPY build_info.txt /workspace/                                                                                0.0s
 => ERROR [5/9] COPY git_hash.txt /workspace/                                                                                0.0s
------
 > [5/9] COPY git_hash.txt /workspace/:
------
Dockerfile:21
--------------------
  19 |     COPY build_info.txt /workspace/
  20 |
  21 | >>> COPY git_hash.txt /workspace/
  22 |
  23 |     RUN cd /workspace && ./docker_build_script_ubuntu.sh
--------------------
ERROR: failed to solve: failed to compute cache key: failed to calculate checksum of ref 238fd63f-a388-4d60-8789-00a308c0d7e5::wla783xpjl7r6j5p8rnu2xnmi: "/git_hash.txt": not found

View build details: docker-desktop://dashboard/build/desktop-linux/desktop-linux/v6r8wk5ry197rqvzd39h4hh4y

git_hash.txt comes from the Makefile step.
make git_hash.txt build_info.txt

i.e. one would do:
make docker_build

But I agree needing Makefile is bad.  @achraf-mer can we avoid so Dockerfile builds on its own?

I removed it's need here: 282aec97e9a8f3dc4b513f33afb00e187ae857ec

The Docker Build ends with this error. Should I change the Miniconda image?
266.6 2024-08-10 14:26:56 (2.84 MB/s) - 'Miniconda3-latest-Linux-x86_64.sh' saved [146836934/146836934]
266.6
266.6 + mkdir -p /h2ogpt_conda
266.6 + bash ./Miniconda3-latest-Linux-x86_64.sh -b -u -p /h2ogpt_conda
266.6 PREFIX=/h2ogpt_conda
267.0 Unpacking payload ...
267.0 rosetta error: failed to open elf at /lib64/ld-linux-x86-64.so.2
267.0  ./Miniconda3-latest-Linux-x86_64.sh: line 442:  8661 Exit 141                extract_range $boundary1 $boundary2
267.0       8662 Trace/breakpoint trap   | CONDA_QUIET="$BATCH" "$CONDA_EXEC" constructor --extract-tarball --prefix "$PREFIX"
267.0 + export CMAKE_ARGS=-DLLAMA_METAL=on
267.0 + CMAKE_ARGS=-DLLAMA_METAL=on
267.0 + export FORCE_CMAKE=1
267.0 + FORCE_CMAKE=1
267.0 + bash docs/linux_install.sh
267.0 + shopt -s expand_aliases
267.0 + test -f /usr/bin/sudo
267.0 + echo 'No sudo'
267.0 + alias 'sudo= '
267.0 No sudo
267.0 + [[ -z '' ]]
267.0 + conda install weasyprint pygobject -c conda-forge -y
267.0 docs/linux_install.sh: line 15: conda: command not found
------
Dockerfile:21
--------------------
  19 |     COPY build_info.txt /workspace/
  20 |
  21 | >>> RUN cd /workspace && ./docker_build_script_ubuntu.sh
  22 |
  23 |     RUN chmod -R a+rwx /workspace
--------------------
ERROR: failed to solve: process "/bin/sh -c cd /workspace && ./docker_build_script_ubuntu.sh" did not complete successfully: exit code: 127

To build the docker image for MAC, I expect some changes may be required, I'm unsure.  Thanks for the feedback.

I was abe to get it successfully installed. Instead of running the line bellow:
pip install -r reqs_optional/requirements_optional_langchain.txt -c reqs_optional/reqs_constraints.txt
I installed the langchain requirements by running the reqs_optional/requirements_optional_langchain.txt


对 kubeadm 进行故障排查

kubeadm init --kubernetes-version=1.19.1 --apiserver-advertise-address=<IP_ADDRESS> --image-repository registry.aliyuncs.com/google_containers --service-cidr=<IP_ADDRESS>/16 --pod-network-cidr=<IP_ADDRESS>/16
result is:
[ERROR Port-10250]: Port 10250 is in use
use kubeadm reset command
it is not working

Maybe you should check the usage of port 10250 on your host using netstat.
BTW, issues here are aimed for documentation, and you can go kubeadm for more technical help.

This port is because the systemctl enable kubelet command is used. This process takes up four ports 10255 10250 10248 40062

@hejun126 The command kubeadm reset didn't worked out for you?

/triage needs-information

@RA489 YES,it is not working。

why don't you kubectl stop kubelet and retry?

kubeadm init --pod-network-cidr=<IP_ADDRESS>/16 --apiserver-advertise-address=<IP_ADDRESS> --image-repository registry.aliyuncs.com/google_containers

result is:
[wait-control-plane] Waiting for the kubelet to boot up the control plane as static Pods from directory "/etc/kubernetes/manifests". This can take up to 4m0s
[kubelet-check] Initial timeout of 40s passed.
Unfortunately, an error has occurred:
	timed out waiting for the condition

This error is likely caused by:
	- The kubelet is not running
	- The kubelet is unhealthy due to a misconfiguration of the node in some way (required cgroups disabled)

If you are on a systemd-powered system, you can try to troubleshoot the error with the following commands:
	- 'systemctl status kubelet'
	- 'journalctl -xeu kubelet'

Additionally, a control plane component may have crashed or exited when started by the container runtime.
To troubleshoot, list all containers using your preferred container runtimes CLI.

Here is one example how you may list all Kubernetes containers running in docker:
	- 'docker ps -a | grep kube | grep -v pause'
	Once you have found the failing container, you can inspect its logs with:
	- 'docker logs CONTAINERID'

error execution phase wait-control-plane: couldn't initialize a Kubernetes cluster

kubeadm version
kubeadm version: &version.Info{Major:"1", Minor:"19", GitVersion:"v1.19.4", GitCommit:"d360454c9bcd1634cf4cc52d1867af5491dc9c5f", GitTreeState:"clean", BuildDate:"2020-11-11T13:15:05Z", GoVersion:"go1.15.2", Compiler:"gc", Platform:"linux/amd64"}

kubelet --version
Kubernetes v1.19.4

docker version
Client:
Version:         1.13.1
API version:     1.26
Package version: docker-1.13.1-162.git64e9980.el7.centos.x86_64
Go version:      go1.10.3
Git commit:      64e9980/1.13.1
Built:           Wed Jul  1 14:56:42 2020
OS/Arch:         linux/amd64
Server:
Version:         1.13.1
API version:     1.26 (minimum version 1.12)
Package version: docker-1.13.1-162.git64e9980.el7.centos.x86_64
Go version:      go1.10.3
Git commit:      64e9980/1.13.1
Built:           Wed Jul  1 14:56:42 2020
OS/Arch:         linux/amd64
Experimental:    false

@hejun126 Not sure if your docker version is supported. You may try ask questions on stackoverflow.com or on #kubernetes-users channel, because this doesn't look like a documentation error. If you find something to improve on the doc side (e.g. https://kubernetes.io/docs/setup/production-environment/container-runtimes/#docker) please file another issue.
/close

add  --v=6   to command
kubeadm init --pod-network-cidr=<IP_ADDRESS>/16 --image-repository registry.aliyuncs.com/google_containers --v=6
result is:
I1118 10:13:22.541992   88868 round_trippers.go:443] GET https://<IP_ADDRESS>:6443/healthz?timeout=10s  in 0 milliseconds

netstat -tlunp
Active Internet connections (only servers)
Proto Recv-Q Send-Q Local Address           Foreign Address         State       PID/Program name
tcp        0      0 <IP_ADDRESS>:10248         <IP_ADDRESS>:*               LISTEN      89368/kubelet
tcp        0      0 <IP_ADDRESS>:9200            <IP_ADDRESS>:*               LISTEN      36212/java
tcp        0      0 <IP_ADDRESS>:9300            <IP_ADDRESS>:*               LISTEN      36212/java
tcp        0      0 <IP_ADDRESS>:38882         <IP_ADDRESS>:*               LISTEN      89368/kubelet
tcp        0      0 <IP_ADDRESS>:10050    <IP_ADDRESS>:*               LISTEN      28461/zabbix_agentd
tcp        0      0 <IP_ADDRESS>:12358    <IP_ADDRESS>:*               LISTEN      19990/sshd
tcp6       0      0 :::10250                :::*                    LISTEN      89368/kubelet


Include file name in references search history quick pick

Feature request
When running References: View History, include the search file name in the quick pick:

Not a fan of that either (takes up too much space). Can we append the file name in the description?
{file} • {string}

Yeah, looking good. I will go with that. Thanks


[SYSTEMML-1793] Support right indexing on GPU

This PR supports right indexing without requiring sparse to dense conversion of inputs. Note: this PR only supports dense output.
Also, added RightIndexingTests in gpu package.

@nakul02 can you please review this PR ?

Refer to this link for build results (access rights to CI server needed):
https://sparktc.ibmcloud.com/jenkins/job/SystemML-PullRequestBuilder/1999/

Refer to this link for build results (access rights to CI server needed):
https://sparktc.ibmcloud.com/jenkins/job/SystemML-PullRequestBuilder/2004/


[FLOC-3964] Update release process instructions to include Jenkins instructions

This PR updates the release process documents to describe the additional steps that are currently required to perform a release using Jenkins and Buildbot. These were issues that were encountered during the previous release.

Sphinx is complaining:
gettinginvolved/infrastructure/release-process.rst:148:multijob:process                                                                                gettinginvolved/infrastructure/release-process.rst:222:basebox: writing output... [100%] version                                                                                Spelling checker messages written to /home/pilar/code/extra_flocker/flocker/docs/_build/spelling/output.txt build finished with problems. Makefile:156: recipe for target 'spelling' failed make: *** [spelling] Error 1 (extra_flocker)pilar@eva02:~/code/extra_flocker/flocker/docs$ cat /home/pilar/code/extra_flocker/flocker/docs/_build/spelling/output.txt gettinginvolved/infrastructure/release-process.rst:148: (multijob)  gettinginvolved/infrastructure/release-process.rst:222: (basebox)

Thanks for the review :) I've just updated the spelling list so hopefully the sphinx build should pass on the next run. I'll check to see if it needs another review.

Thanks @zubron . A few more comments to address, and then please merge. And thanks @mpgomez .


Suggestions to make library more useful

In its current state, this library is missing some key features to make it useful in my projects.

I need to be able to change route parameters, query parameters, and meta based on story arguments.
I need to be able to specify a different route and/or routes for each story within a single story file.

Any ideas on how to tackle these?

Hi @misha, thanks for the feedback.
Point 1: Do you mean through Storybook controller args? or just through setup (static values)? - It won't currently work through args, but I think there is no reason this couldn't be added - though I think it will require a page reload in order to apply.
Point 2: this is possible if you're using the latest v2+ version of the package (have a look at README - its more detailed than previous version) - it possible in v1.
Do you have any code you can share so I can see examples of how you're trying to use it?

Basically, I want to be able to:

Specify a control in argTypes.
Compute something in setup using the current arguments.
Pass that value to the current route s.t. calls to useRoute and useRouter from vueuse can read it.

A page reload would be totally acceptable - I believe Storybook already refreshes the story whenever a controlled argument changes, anyway.

@misha, I've created a new PR with new example, can you let me know if this is the kind of thing you're trying to do? (Apologies not sure I've fully understood)
you can also preview my example Storybook demo site.
If I've misunderstood, please provide a code example so I can better understand your use-case.

@misha any update on this? I'll close issue if I don't hear back from you.

(Sorry for the delay, had a different task for a while.)

In the example code, router data is passed using a prop - but components generally want to access $router and $route for information, and this is indeed what useRoute and useRouter do. What I'm really looking for is to set $router and/or $route for a particular story.
The solution is probably not a component - it's a utility function or a hook that instruments the router context for that story alone.
Here's the ideal usage:
<template>
  <div>
    <template v-if="$route.meta.new">
      Welcome!
    <template v-else>
      Welcome back!
    </template>
  </div>
</template>

export default {
  title: 'Greeter',
  component: Greeter,
  argTypes: {
    new: {
      control: 'boolean',
    },
  },
};

export const story = (args) => defineComponent({
  components: {
    Greeter, // The component above ^.
  },
  setup() {
    useMockRoute({
      meta: {
        new: args.new,
      },
    });
  },
  template: `
    <Greeter />
  `,
});

Notably, for nearly all components setting up an entire router is overkill. I only want to insert the little bit that the component actually uses.
There are some components that use the router, and for those I would request a useMockRouter hook that doesn't so much set the routes for the story as it intercepts and logs the parameters to any of the methods.
The use case this library currently implements is extremely useful for the case where you want to boot up the whole app with a subset of routes, but those components are actually quite rare. Small apps would only have just one such story, specifically the one that boots up the entire app in Storybook.
Does that help at all?

Yes thats great thanks, will provide update ASAP.

@misha I've created a new PR, with this I had added a new decorator mockRouter which allows for simple mocked $route and $router, you can see preview storybook build here: https://deploy-preview-18--storybook-vue3-router.netlify.app/?path=/story/mock-router--default (have a look at the dynamic template story as this replicates your suggestion)
I don't think i'm going to be able to mock useRoute or useRouter as within your components these would be imported from vue-router and require the vue-router is initalised.
I'll keep looking into this though and see if I can find a way.
Thanks for your feedback this has been a good addition to the package and you're completely correct that many people may not require the full router setup so the mocked version is a nice alternative.

@misha I've completed the PR linked above - adding a mockRouter to the package.
Closing issue


General performance optimizations

Tasks
For the past couple weeks I've been investigating datashader's performance and how we can improve upon it. I'm now documenting my remaining tasks, in case I get pulled away on a different project. Below is a list of tasks/issues that I'm currently addressing:

[x] Extend the filetimes.py and filetimes.yml benchmarking environment to find the optimal file format for datashader/dask (Issue #129)
[x] Benchmark numba compared to handwritten ufuncs in vaex (Issue #310)
[x] Gather perf information about dask locking behavior (Issue #314)
[ ] Investigate why Cachey leads to better runtime performance for repeat datashader aggregations
[x] Document memory usage findings (Issue #305)
[x] Investigate how datashader's performance changes with data types (doubles vs floats, etc) (Issue #305)
[x] Verify that repeat aggregations no longer depend on file format (Issue #129)
[x] Investigate distributed scheduler vs threaded scheduler for single-machine use case (#331, #332, #334)

Performance takeaways
Below are some performance-related takeaways that fell out of my experiments and optimizations with datashader and dask:
General

Use the latest version of numba (>=0.33). This includes bugfixes providing ~3-5x speedups for many cases (numba/numba#2345, numba/numba#2349, numba/numba#2350)

When interacting with data on the filesystem, store it in the Apache Parquet format when possible. Snappy compression should be used when writing out parq files, and the data should rely on categorical dtypes (when possible) before writing the parq files, as parquet supports categoricals in its binary format (#129)

Use the categorical dtype for columns with data that takes on a limited, fixed number of possible values. Categorical columns use a more memory-efficient data representation and are optimized for common operations such as sorting and finding uniques. Example of how to convert a column to the categorical dtype:
df[colname] = df[colname].astype('category')

There is promise with enhancing datashader's performance even further by using single-precision floats (np.float32) instead of double-precision floats (np.float64). In past experiments this cut down the time to load data off of disk (assuming the data was written out in single-precision float) as well as datashader's aggregation times. Care should be taken using this approach, as using single-precision (in any software application, not just datashader) leads to different numerical results than double-precision (#305)

Single machine

A rule-of-thumb for the number of partitions to use while converting pandas dataframes into dask dataframes is multiprocessing.cpu_count(). This allows dask to use one thread per CPU for parallelizing computations (#129)

When the entire dataset fits into memory at once, persist the dataframe as a Dask dataframe prior to passing it into datashader (#129). One example of how to do this:
from dask import dataframe as dd
import multiprocessing
dask_df = dd.from_pandas(df, npartitions=multiprocessing.cpu_count()).persist()
...
cvs = datashader.Canvas(...)
agg = cvs.points(dask_df, ...)

When the entire dataset doesn't fit into memory at once, use the distributed scheduler (#331) without persisting (there is an outstanding issue #332 that illustrates the problem with the distributed scheduler + persist). Example:
from dask import distributed
import multiprocessing
cluster = distributed.LocalCluster(n_workers=multiprocessing.cpu_count(), threads_per_worker=1)
dask_client = distributed.Client(cluster)
dask_df = dd.from_pandas(df, npartitions=multiprocessing.cpu_count()) # Note no "persist"
...
cvs = datashader.Canvas(...)
agg = cvs.points(dask_df, ...)

Multiple machines
TBD
This comment will be updated as I make more observations.

Benchmarking with numba exposed a refcount bug. Once it is fixed, there should be a significant performance increase to datashader (at least 3x in many cases). Linking to numba issue for reference: https://github.com/numba/numba/issues/2345

More performance improvements to come once this numba PR is merged: https://github.com/numba/numba/pull/2349

There's one outstanding numba issue that, when resolved, should unlock additional performance for datashader (particularly for sum and mean): https://github.com/numba/numba/issues/2350

Preliminary memory usage measurements and calculations were added to Issue #305.

os.cpu_count()

That function didn't appear until Python 3.4, so we should probably recommend multiprocessing.cpu_count() instead.  On my machine that returns 8, same as os.cpu_count(); not sure if 4 or 8 is the better answer for this particular machine (i.e., using hyperthreading or not)...

Thanks @jbednar , I've updated the filetimes.py code and the suggestions at the top of the thread.

Ok, great; that keeps it simple!

Thanks for all the great work, @gbrener!  Reflecting these recommendations into our documentation is now on our to-do list.


TypeError: 'GSFont' object has no attribute 'getitem'

Just tried to run
gftools fix-glyphs WorkSans-Upright.glyphs
Traceback (most recent call last):
  File "/usr/local/bin/gftools-fix-glyphs.py", line 55, in <module>
    main()
  File "/usr/local/bin/gftools-fix-glyphs.py", line 39, in main
    print('Copyright: "{}"'.format(data["copyright"]))
TypeError: 'GSFont' object has no attribute '__getitem__'

Returned this error?

This script is misleading and still appears to be a wip. It doesn't fix anything, https://github.com/googlefonts/gftools/blob/master/bin/gftools-fix-glyphs.py#L38-L43
There's a fix QA and fix script here (specific to GF), https://github.com/googlefonts/gf-glyphs-scripts.

I'm gonna remove it. -> #710


[S3 Compatible] - Fix

We need to fix S3 mentions according to AWS communication.
I've modified Stephane's guides to include S3 details.
Needs to be done before 30th December.

Thanks :)


feat(embedding.py): add size_in_GB information for each model

For usage in CI filtering by model size, can now filter by size_in_GB < 1 or similar

In the merge conflict resolution, I've made it conditional on the model size, instead of the model name/desc. I hope this is more general than what we've right now.