3D-Improved-UNet pull request Yitian Guo s4706162

Overview: This Pull Request implements the 3D Improved UNet model for segmenting prostate MRI image data, and provides comprehensive improvements and documentation for model training, validation, and testing.
Main Changes:

Model implementation: an implementation of the 3D Improved UNet model has been added to the modules.py, including residual linking and attention mechanisms to improve model training efficiency and segmentation accuracy.

Data loader: A data loading and preprocessing module has been implemented in the dataset.py file to support the processing of 3D prostate MRI datasets.

Training script: Logic for training, validating and testing the model is added in the train.py file, and losses and metrics during training are plotted.

Prediction Scripts: Examples of model predictions are provided in the predict.py file, including model inference and visualization of results.

Documentation update: The README.md file has been updated to describe in detail the project's goals, model architecture, usage, and dependencies.

Purpose: These changes are intended to enable a reliable automated segmentation tool to aid in the processing of 3D prostate MRI data and to achieve dice coefficients above 0.7 in each category.

This is an initial inspection, no action is required at this point
Recognition problem:
Problem Solving:
•	Algorithm solves the problem and achieves a Dice score of above 0.8 for all labels.
Algorithm implementation:
•	Algorithm implemented in PyTorch for the UNet3D model and functions.
•	Test set is split in predict.py for model testing instead of using the same split used in train.py. Same settings used for data splitting from initial inspection but add risk for overlapping between train and test set.
Design:
•	Modularised and reusable code.
Commenting:
•	Some comments throughout the code.
Difficulty:
•	3D UNet with residual blocks and attention gate included for each layer.

Cant merge because of conflicting changes to main repo files (gitignore). Please update for merge, doesn't affect grade.
Segmentations not one hot encoded -2 additionally

Hi @shakes76,
I have resolved the conflict in .gitignore and updated the branch. Please review and merge when convenient. Thank you!


feat(vault): add operations and development mode support

closes PLT-242

so my suggestion for the authentication part is:
type Authenticator interface {
  func authenticate(vc *VaultClient) error
}

type K8sAuthenticator struct {
    configuration Configuration // if any for this authenticator
}

func (a *K8sAuthenticator) authenticate(vc *VaultClient) error {
	vc.logger.Info("performing vault k8s login.")
	// reads jwt from service account
	jwt, err := os.ReadFile("/var/run/secrets/kubernetes.io/serviceaccount/token")
	if err != nil {
		return fmt.Errorf("unable to read file containing service account token: %v 😱", err)
	}
	params := map[string]interface{}{
		"jwt":  string(jwt),
		"role": vc.role, // the name of the role in Vault that was created with this app's Kubernetes service account bound to it
	}
	// perform login
	secret, err := vc.client.Logical().Write("auth/kubernetes/login", params)
	if err != nil {
		return fmt.Errorf("unable to log in with Kubernetes auth: %v 😱", err)
	}
	if secret == nil || secret.Auth == nil || secret.Auth.ClientToken == "" {
		return errors.New("login response did not return client token 😱")
	}
	// client update with the access token
	vc.logger.Info("login: client logged in successfully 🔑")
	token := strings.TrimSuffix(secret.Auth.ClientToken, "\n")
	vc.client.SetToken(token)
	// stores login response secret
	vc.secret = secret

	// do the token renewal cycle
	go vc.renew()

	return nil
}

type LocalAuthenticator struct {
    configuration Configuration // if any for this authenticator
}

func (a *K8sAuthenticator) authenticate(vc *VaultClient) error {
	// Make sure it's development mode
	if vc.configuration.VaultDevMode {
		vc.logger.Info("[development mode] performing vault login.")
		if vc.configuration.VaultToken == "" {
			return errors.New("unable to get token as env var ('VAULT_TOKEN') 😱")
		}
		vc.client.SetToken(vc.configuration.VaultToken)
		return nil
	}
}

the VaultClient constructor for example:
func NewVaultClient(role string, configuration VaultClientConfiguration, logger logging.Logger, authenticator Authenticator) (*VaultClient, error) {
        config := &api.Config{Address: configuration.VaultURL}

        if authenticator == nil {
              authenticator = NewK8sAuthenticator() // for example or we can throw an error, for example.
        }

	client, err := api.NewClient(config)
	if err != nil {
		return nil, err
	}

	vc := &VaultClient{
		configuration: configuration,
		role:          role,
		logger:        logger,
		client:        client,
	}

	if err = authenticator.authenticate(vc); err != nil {
		return nil, err
	}

	return vc, nil
}

there is no login any more, all that logic goes into the authenticator.
@wsalles this is what i was saying about the authentication part

so my suggestion for the authentication part is:
type Authenticator interface {
  func Authenticate(vc *VaultClient) error
}

type K8sAuthenticator struct {
    configuration Configuration // if any for this authenticator
}

func (a *K8sAuthenticator) Authenticate(vc *VaultClient) error {
	vc.logger.Info("performing vault k8s login.")
	// reads jwt from service account
	jwt, err := os.ReadFile("/var/run/secrets/kubernetes.io/serviceaccount/token")
	if err != nil {
		return fmt.Errorf("unable to read file containing service account token: %v 😱", err)
	}
	params := map[string]interface{}{
		"jwt":  string(jwt),
		"role": vc.role, // the name of the role in Vault that was created with this app's Kubernetes service account bound to it
	}
	// perform login
	secret, err := vc.client.Logical().Write("auth/kubernetes/login", params)
	if err != nil {
		return fmt.Errorf("unable to log in with Kubernetes auth: %v 😱", err)
	}
	if secret == nil || secret.Auth == nil || secret.Auth.ClientToken == "" {
		return errors.New("login response did not return client token 😱")
	}
	// client update with the access token
	vc.logger.Info("login: client logged in successfully 🔑")
	token := strings.TrimSuffix(secret.Auth.ClientToken, "\n")
	vc.client.SetToken(token)
	// stores login response secret
	vc.secret = secret

	// do the token renewal cycle
	go vc.renew()

	return nil
}

type LocalAuthenticator struct {
    configuration Configuration // if any for this authenticator
}

func (a *K8sAuthenticator) Authenticate(vc *VaultClient) error {
	// Make sure it's development mode
	if vc.configuration.VaultDevMode {
		vc.logger.Info("[development mode] performing vault login.")
		if vc.configuration.VaultToken == "" {
			return errors.New("unable to get token as env var ('VAULT_TOKEN') 😱")
		}
		vc.client.SetToken(vc.configuration.VaultToken)
		return nil
	}
}

the VaultClient constructor for example:
func NewVaultClient(role string, configuration VaultClientConfiguration, logger logging.Logger, authenticator Authenticator) (*VaultClient, error) {
        config := &api.Config{Address: configuration.VaultURL}

        if authenticator == nil {
              authenticator = NewK8sAuthenticator() // for example or we can throw an error, for example.
        }

	client, err := api.NewClient(config)
	if err != nil {
		return nil, err
	}

	vc := &VaultClient{
		configuration: configuration,
		role:          role,
		logger:        logger,
		client:        client,
	}

	if err = authenticator.Authenticate(vc); err != nil {
		return nil, err
	}

	return vc, nil
}

there is no login any more, all that logic goes into the authenticator.
@wsalles this is what i was saying about the authentication part

In this way we don't need the development mode configuration any more. The user just need to instantiate the right authenticator.

@wsalles please split the file authenticator into multiple files 🙏


Update 6.mdx fix typo

Fixed a typo @lewtun

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.


thanos katacoda course: Error fetching stores/flags list in Thanos UI

https://www.katacoda.com/thanos/courses/thanos/7-multi-tenancy
step 2
Verification part
Let's check if our read isolation works:

    Query for Fruit Team through Caddy 39091 port
    Query for Veggie Team through Caddy 39092 port

click any link, will see errors
Warning: Error fetching stores list: Unexpected response status when fetching stores:
Warning: Error fetching flags list: Unexpected response status when fetching flags:
see the picture from: https://pasteboard.co/K52vBct.png
Browser:
Chrome Version 86.0.4240.111 (Official Build) (64-bit)
FireFox 60.0 (64-bit)

I can reproduce this. Help wanted!

@yeya24 happy to take this on and investigate :+1:

The problem is that prom-label-proxy can only proxy a subset of the Querier endpoints. This is by design as this component is used to enforce multi-tenancy so will not leak global information to a single tenant.
The solution here is to update the tutorial to replace the links to the Querier UI that do not work, with curl commands or similar.

@ianbillett Thanks for the investigation. I saw that prom-label-proxy has a flag to pass through some APIs using https://github.com/prometheus-community/prom-label-proxy/blob/38b1382d7368e994e39c0cb853f3f3c9300f5045/main.go#L48 flag. Is it better to use this?

Aha - good spot! I would expect that it is indeed possible given that flag. Let me experiment with that now...

TL;DR - it is possible to fix with the new flags in prom-label-proxy but it is not very nice for a new user to look at.

@yeya24 reverted to curls and CI is now green - I think we're ready to merge :muscle:


Add sort_descending attribute and break out sort into own function

A reverse option was already built in to sorted(), the separate function makes extending it easier.
New to Django (just hacking on an existing project) and I honestly couldn't get the test suite to run so I didn't bother writing one. If you're willing to accept this PR you may want to at least quickly confirm all tests still pass. (Not sure if a new one is needed since again reverse was built-in.)
Thanks!

Thanks for implementing this!  I liked your approach but I made a few changes for the sake of consistency with other parts of django:

instead of using a new option (sort_descending), I add the ability to add a '-' to the beginning of the sorting_field to specify reverse sorting.  This is in line with how django handles ordering fields in other situations.  Now, to reverse order by the field pub_date you would set sorting_field='-pub_date'
naming the function sort made me nervous (since it's also the name of a built-in python function), so I renamed it queryList_sort
implemented a test to make sure everything ran properly

I've merged those changes into master.  Let me know if you have any questions/concerns!


openldap: disable parallel build

Description of changes
The build failed on our 48-core machine, so it seems like it doesn't support it anymore.
libtool: link: cc -g -O2 -o .libs/ldif-filter ldif-filter.o slapd-common.o  ../../libraries/liblutil/liblutil.a ../../libraries/libldap/.libs/libldap.so /build/openldap-2.6.2/libraries/liblber/.libs/liblber.so ../../libraries/liblber/.libs/liblber.so /nix/store/zkw493raash35m4al6bhrzvvwm2f0bdi-cyrus-sasl-2.1.28/lib/libsasl2.so -lssl -lcrypto -lcrypt -Wl,-rpath -Wl,/nix/store/wj7pax447418mk0h0iv7kl8ybb8z1qsd-openldap-2.6.2/lib -Wl,-rpath -Wl,/nix/store/zkw493raash35m4al6bhrzvvwm2f0bdi-cyrus-sasl-2.1.28/lib
checking how to run the C preprocessor... gcc -E
/nix/store/cz52w8xf3i1d3xvzpzd9abf7rvpl9017-binutils-2.38/bin/ld: cannot find slapd-common.o: No such file or directory
...
collect2: error: ld returned 1 exit status

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.11 Release Notes (or backporting 22.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

This needs to go to staging where a fix for the parallel build should already be: #176290

I've build this multiple times on 12/24/64 thread machines and the build was fine for me. Seems to be spurious then.
Also needs to go into staging.

Also for context, this is already a fixed issue: https://github.com/NixOS/nixpkgs/issues/175626

@dasJ That's awesome, thanks! I guess, we should rebase our dev branch on master more often.


[Bug]: agentchat_graph_rag_neo4j/ Notebook: program keeps trying to connect to api.openai.com, even though I have set my endpoint to azure

Describe the bug
I am following the notebook here:
https://docs.ag2.ai/notebooks/agentchat_graph_rag_neo4j#using-neo4js-graph-database-with-ag2-agents-for-question-and-answering
I modified the example code to use Azure OpenAI instead of Openai, but the code is still trying to connect to OpenAI.
Steps to reproduce
Run everything in the notebook before the cell that says "instead of creating a new property graph..."
Then use the following, with your own Azure OpenAI credentials:
llm = AzureOpenAI(
model="gpt-4",
deployment_name="gpt-4", #I also tried this with engine=, it did not work
api_key=os.environ.get("OPENAI_API_KEY_1"),
azure_endpoint=os.environ.get("OPENAI_ENDPOINT_1"),
api_base = azure_endpoint,
api_version="2024-02-01",
)
embed_model = AzureOpenAIEmbedding(
model="text-embedding-3-small",
deployment_name="text-embedding-3-small",
api_key=os.environ.get("OPENAI_EMBEDDINGS_KEY"),
azure_endpoint=os.environ.get("OPENAI_EMBEDDINGS_ENDPOINT"),
api_version="2024-02-01",
)
query_engine = Neo4jGraphQueryEngine(
username="neo4j",
password="password",
host="host_url",
port=1111,
database="neo4j",
llm=llm,
embedding=embed_model,
)
query_engine.connect_db()
from autogen.agentchat.contrib.graph_rag.neo4j_graph_rag_capability import Neo4jGraphCapability
from autogen_llm_config import llm_config_no_functions  #this is my own config that points to Azure OpenAI
graph_rag_agent = ConversableAgent(
name="rag_agent",
human_input_mode="NEVER",
)
graph_rag_capability = Neo4jGraphCapability(query_engine)
graph_rag_capability.add_to_agent(graph_rag_agent)
user_proxy = UserProxyAgent(name="user_proxy", human_input_mode="ALWAYS", code_execution_config=False, llm_config=llm_config_no_functions)
user_proxy.initiate_chat(graph_rag_agent, message="How are orders for customer 904504 compared to this time last year?")
OUTPUT:
INFO:httpx:HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.0 302 Moved Temporarily"
HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.0 302 Moved Temporarily"
Even though I have set my LLM to call azure, it still won't do that.  It still keeps calling api.openai.com/v1/chat/completions.
Model Used
gpt-4o
Expected Behavior
The module should have called Azure OpenAI
Screenshots and logs
No response
Additional Information
v0.6.0

@Eric-Shang @sonichi @qingyun-wu

Hi @tyler-suard-parker. Sorry for late reply. I just got back from my trip yesterday. And I didn't use Azure before and it took me some time to set it up.
It seems the notebook instructions are working for me, although my 1k/m rate limit is too low  (I'm using the free version):
Retrying llama_index.llms.openai.base.OpenAI._chat in 0.686371750517236 seconds as it raised RateLimitError: Error code: 429 - {'error': {'code': '429', 'message': 'Requests to the ChatCompletions_Create Operation under Azure OpenAI API version 2024-08-01-preview have exceeded call rate limit of your current OpenAI S0 pricing tier. Please retry after 8 seconds. Please go here: https://aka.ms/oai/quotaincrease if you would like to further increase the default rate limit.'}}.

And I verified it didn't hit my openai endpoint.
Here are my guesses:

Are you using the correct Azure api keys and models (which needs to be deployed first)?
Are you sure the llm_config_no_functions is set properly? Could you give a shot by setting it to false?

Hey @tyler-suard-parker,  I've been able to test successfully with this code block in place in the notebook where noted.
Two Azure model deployments (names as noted):
"gpt-4o-mini"
"text-embedding-3-small"
from llama_index.llms.azure_openai import AzureOpenAI
from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding

llm = AzureOpenAI(
model="gpt-4o-mini",
deployment_name="gpt-4o-mini",
api_key=azure_api_key,
azure_endpoint=azure_endpoint,
api_base = azure_endpoint,
api_version="2024-08-01-preview",
)

embed_model = AzureOpenAIEmbedding(
model="text-embedding-3-small",
deployment_name="text-embedding-3-small",
api_key=azure_api_key,
azure_endpoint=azure_endpoint,
api_version="2023-05-15",
)

query_engine = Neo4jGraphQueryEngine(
username="neo4j",
password="<mypassword>",
host="bolt://<myneo4jip>",
port=7687,
database="neo4j",
llm=llm,
embedding=embed_model,
)
query_engine.connect_db()

from autogen.agentchat.contrib.graph_rag.neo4j_graph_rag_capability import Neo4jGraphCapability
# from autogen_llm_config import llm_config_no_functions #this is my own config that points to Azure OpenAI

llm_config_no_functions = {
    "config_list":
    [
        {
            "api_type": "azure",
            "api_version": "2024-08-01-preview",
            "model": "gpt-4o-mini",
            "base_url": azure_endpoint,
            "api_key": azure_api_key,
            "cache_seed": None
        }
    ]
}

graph_rag_agent = ConversableAgent(
name="rag_agent",
human_input_mode="NEVER",
)

graph_rag_capability = Neo4jGraphCapability(query_engine)
graph_rag_capability.add_to_agent(graph_rag_agent)

user_proxy = UserProxyAgent(name="user_proxy", human_input_mode="ALWAYS", code_execution_config=False, llm_config=llm_config_no_functions)

user_proxy.initiate_chat(graph_rag_agent, message="Which company is the employer?")

In relation to what @Eric-Shang asked, if you're able to share your llm_config_no_functions that may help diagnose it.

Hi @tyler-suard-parker. Sorry for late reply. I just got back from my trip yesterday. And I didn't use Azure before and it took me some time to set it up.
It seems the notebook instructions are working for me, although my 1k/m rate limit is too low (I'm using the free version):
Retrying llama_index.llms.openai.base.OpenAI._chat in 0.686371750517236 seconds as it raised RateLimitError: Error code: 429 - {'error': {'code': '429', 'message': 'Requests to the ChatCompletions_Create Operation under Azure OpenAI API version 2024-08-01-preview have exceeded call rate limit of your current OpenAI S0 pricing tier. Please retry after 8 seconds. Please go here: https://aka.ms/oai/quotaincrease if you would like to further increase the default rate limit.'}}.

And I verified it didn't hit my openai endpoint.
Here are my guesses:

Are you using the correct Azure api keys and models (which needs to be deployed first)?
Are you sure the llm_config_no_functions is set properly? Could you give a shot by setting it to false?

@Eric-Shang Thank you so much for your hard work on this.  I appreciate you setting up Azure to try it out.
I tried setting my llm_config_no_functions to false, and it had no effect.  That same config works with Autogen in other scripts.
I tested my llm = AzureOpenAI() code by running llm.chat with some example messages, and that worked fine.  Then I tested my embed_model = AzureOpenAIEmbedding() code, and that worked fine too.
However, when I try to run the .initiate_chat line in your notebook, I am still getting:
[venv/Lib/site-packages/llama_index/llms/openai/utils.py:507)     raise ValueError(MISSING_API_KEY_ERROR_MESSAGE)
ValueError: No API key found for OpenAI.
Please set either the OPENAI_API_KEY environment variable or openai.api_key prior to initialization.
API keys can be found or created at https://platform.openai.com/account/api-keys
Even though I have set my api keys for azure it looks like Llamaindex is still looking for the API key for openai.com?

@marklysze Thank you for your help.  I ran the exact code you showed, just inputting my credentials, and I am still getting this error:
[44](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:44)         raise ImportError(
     [45](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:45)             "`llama-index-llms-openai` package not found, "
     [46](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:46)             "please run `pip install llama-index-llms-openai`"
     [47](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:47)         )
     [48](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:48)     except ValueError as e:
---> [49](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:49)         raise ValueError(
     [50](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:50)             "\n******\n"
     [51](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:51)             "Could not load OpenAI model. "
     [52](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:52)             "If you intended to use OpenAI, please check your OPENAI_API_KEY.\n"
     [53](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:53)             "Original error:\n"
     [54](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:54)             f"{e!s}"
     [55](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:55)             "\nTo disable the LLM entirely, set llm=None."
     [56](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:56)             "\n******"
     [57](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:57)         )
     [59](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:59) if isinstance(llm, str):
     [60](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:60)     splits = llm.split(":", 1)

ValueError:
******
Could not load OpenAI model. If you intended to use OpenAI, please check your OPENAI_API_KEY.
Original error:
No API key found for OpenAI.
Please set either the OPENAI_API_KEY environment variable or openai.api_key prior to initialization.
API keys can be found or created at https://platform.openai.com/account/api-keys

To disable the LLM entirely, set llm=None.
******

As I mentioned to Eric, I have tried bot the llm and the embedding model separately and they both work using those same credentials.

@marklysze   Here is the code you sent me with some tests in between:
from llama_index.llms.azure_openai import AzureOpenAI
from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding

api_key=""
azure_endpoint=""
api_version="2024-06-01"
temperature=0.0

llm = AzureOpenAI(
model="",
deployment_name="",
api_key="",
azure_endpoint="https://.openai.azure.com/",
api_base = "https://.openai.azure.com/",
api_version="2024-08-01-preview",
)

from llama_index.core.llms import ChatMessage
messages = [
    ChatMessage(role="system", content="You are a pirate with colorful personality."),
    ChatMessage(role="user", content="Hello"),
]

response = llm.chat(messages)
print(response)

Output: Ahoy there, matey! How be the winds fairin' for ye today? What adventure or treasure be ye seekin' on the vast seas of conversation?
embed_model = AzureOpenAIEmbedding(
model="text-embedding-3-small",
deployment_name="text-embedding-3-small",
api_key=api_key,
azure_endpoint=azure_endpoint,
api_version="2024-02-01",
)

embedding = embed_model.get_text_embedding("Sample text for embedding")
print(embedding)

Output: [0.021276075392961502, 0.009070326574146748, 0.02229788526892662, ... ]
query_engine = Neo4jGraphQueryEngine(
username="neo4j",
password="parker1234",
host="neo4j://cor089ya166",
port=7687,
database="neo4j",
llm=llm,
embedding=embed_model,
)
query_engine.connect_db()

from autogen.agentchat.contrib.graph_rag.neo4j_graph_rag_capability import Neo4jGraphCapability

llm_config_no_functions = {
    "config_list":
    [
        {
            "api_type": "azure",
            "api_version": "2024-06-01",
            "model": "gpt-4",
            "base_url": azure_endpoint,
            "api_key": api_key,
            "cache_seed": None
        }
    ]
}

graph_rag_agent = ConversableAgent(
name="rag_agent",
human_input_mode="NEVER",
)

graph_rag_capability = Neo4jGraphCapability(query_engine)
graph_rag_capability.add_to_agent(graph_rag_agent)

user_proxy = UserProxyAgent(name="user_proxy", human_input_mode="ALWAYS", code_execution_config=False, llm_config=llm_config_no_functions)

user_proxy.initiate_chat(graph_rag_agent, message="Please give me any order.")

Output:
ValueError                                Traceback (most recent call last)
File c:\Users\945764\OneDrive - parkercorp\Desktop\productgpt_diagnose.venv\Lib\site-packages\llama_index\core\llms\utils.py:42, in resolve_llm(llm, callback_manager)
[41](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:41)     llm = OpenAI()
---> [42](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:42)     validate_openai_api_key(llm.api_key)  # type: ignore
[43](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/core/llms/utils.py:43) except ImportError:
File c:\Users\945764\OneDrive - parkercorp\Desktop\productgpt_diagnose.venv\Lib\site-packages\llama_index\llms\openai\utils.py:507, in validate_openai_api_key(api_key)
[506](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/llms/openai/utils.py:506) if not openai_api_key:
--> [507](file:///C:/Users/945764/OneDrive%20-%20parkercorp/Desktop/productgpt_diagnose/.venv/Lib/site-packages/llama_index/llms/openai/utils.py:507)     raise ValueError(MISSING_API_KEY_ERROR_MESSAGE)
ValueError: No API key found for OpenAI.
Please set either the OPENAI_API_KEY environment variable or openai.api_key prior to initialization.
API keys can be found or created at https://platform.openai.com/account/api-keys

I was able to solve the issue by doing this:
from llama_index.core import Settings

Settings.llm =llm
Settings.embed_model = embed_model

Right before declaring the query engine.

Glad that you have solved the problems. I was able to reproduce the error after removing open ai key from my environment. Sorry I didn't realize the key pre-existed (I guess @marklysze may have same setting).
I also found the root cause of the problem. I'll fix it right now and you should be able to use Azure without using Settings.


Should sync event target a specific server?

From @imintz on February 18, 2015 14:32
Considering that most use cases will want to communicate with a specific server once they become online, should SyncRegistrationOptions also allow the user to specify a server to ensure connectivity to that specific target?
Copied from original issue: slightlyoff/BackgroundSync#46

From @jkarlin on February 18, 2015 14:51
This could be a nice optimization. By default, I could imagine the UA verifying connectivity to the SW's origin. Do you think a dev-specified server is necessary above and beyond that?

From @annevk on February 18, 2015 16:0
If we want certain DNS entries to be recent that seems like something that's reasonable to have for the service worker as a whole.

From @jkarlin on February 27, 2015 14:6
Is there a need for a dev-specified server in any use cases?

From @imintz on February 28, 2015 18:8
The main use case that I think this applies to is with packaged apps and Cordova implementations of service worker. In those cases, we'd want the spec to be identical, but the service worker's origin is local and so you can't really use it as a target for checking connectivity.

From @annevk on February 28, 2015 9:15
Well I would imagine your importScripts() stuff could be on a CDN. As well as large video resources and such your service worker might deal with. Or perhaps the external Flickr API domain in the Trained to Thrill application. But as I said in my comment, those use cases are for service workers in general.

Oh, should we move this to the Service worker github issue tracker?

Would having the UA learn about connection patterns be enough? Or would we gain a lot more by having a dev-specified list of servers to prewarm for?

From @jkarlin on March 2, 2015 16:49
annevk@ I see, so perhaps the UA might try to do some DNS resolving while spinning up the ServiceWorker. Or, in the case of a sync event that requires connectivity, it would actually preconnect before starting the SW.

From @annevk on March 4, 2015 8:44
Moving this seems fine. Analysis would probably be a good first step for implementations actually. (That gives you the cache with DNS entries and such... Letting it be populated by the site can then come later.)

Assessment tracked in blink via https://code.google.com/p/chromium/issues/detail?id=464258


feat: bitcoin

Example bitcoin implementation using p2wpkh type transactions

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I'm seeing the below when trying to connect to the wallet.
Seeing a mismatch in the console, expected chains on wallet side seem to have longer hashes than what is defined for CAIP-2:

supportedNamespaces {eip155: {…}, cosmos: {…}, kadena: {…}, mvx: {…}, near: {…}, …}bip122: accounts: ['bip122:000000000933ea01ad0ee984209779baaec3ced90fa…7f4943:tb1qxf89r0s70ezxxmcywea300lrjcfxjtwty7w0k4']chains: Array(1)0: "bip122:000000000933ea01ad0ee984209779baaec3ced90fa3f408719526f8d77f4943"length: 1[[Prototype]]: Array(0)events: []methods: (2) ['btc_signMessage', 'btc_sendTransaction']...
requestedChains ['bip122:000000000933ea01ad0ee984209779ba']

Can we give passing the response for getAccountAddresses through via sessionProperties a go here so we can understand how this could work in detail e2e? 🙏


Problem fresh build...

I'm trying to build a fresh build inside a docker container...   However, I keep running into a dependency problem:
[briemers@briemers2 ~]$ sudo docker run -t -i fedora /bin/bash -i
[root@b3d8c3964229 ~]# dnf install git go godep
[root@b3d8c3964229 ~]# cat <<\+ > ~/.profile
export GOPATH="$HOME/work-go"
if [ -n "${PATH#*/work-go*}" ]
then
  export PATH="$PATH:$HOME/work-go"
fi
+
[root@b3d8c3964229 ~]# . ~/.profile
[root@b3d8c3964229 ~]# go get github.com/tools/godep
[root@b3d8c3964229 ~]# go install github.com/tools/godep
[root@b3d8c3964229 ~]# go get github.com/odeke-em/drive/drive-gen
[root@b3d8c3964229 ~]# cd work-go/src/github.com/odeke-em/drive/drive-gen/
[root@b3d8c3964229 drive-gen]# godep save
godep: cannot save google.golang.org/api/drive/v2 at revision 43c645d4bcf9251ced36c823a93b6d198764aae4: already have google.golang.org/api/googleapi at revision 0a735f7ec81c85ce7ec31bf7a67e125ef62266ec.
Run `godep update google.golang.org/api/googleapi' first.
[root@b3d8c3964229 drive-gen]# godep update google.golang.org/api/googleapi
godep: cannot find package "github.com/google/google-api-go-client/drive/v2" in any of:
	/usr/lib/golang/src/github.com/google/google-api-go-client/drive/v2 (from $GOROOT)
	/root/work-go/src/github.com/google/google-api-go-client/drive/v2 (from $GOPATH)
godep: cannot find package "github.com/odeke-em/xon/pkger/src" in any of:
	/usr/lib/golang/src/github.com/odeke-em/xon/pkger/src (from $GOROOT)
	/root/work-go/src/github.com/odeke-em/xon/pkger/src (from $GOPATH)
godep: error loading dependencies
[root@b3d8c3964229 ~]# go get github.com/google/google-api-go-client/drive/v2
package github.com/google/google-api-go-client/drive/v2: code in directory /root/work-go/src/github.com/google/google-api-go-client/drive/v2 expects import "google.golang.org/api/drive/v2"

I'm stuck here...
I could probably copy the installation I already have in my real fedora installation, but that does not seem like a very good idea.

Hello @docbill, sorry about that. I think I may not have updated godeps in a very long time. Would it be possible for you to remove drive-gen/Godeps?    It is strange needing to commit changes before testing they work.   But it works.

Success:  https://hub.docker.com/r/docbill/docker-drive/
Thanks,
Bill

Solid! That's cool. Please feel free to list your steps and or docker build in the wiki :)


fix: AntD select dropdown scroll issue

SUMMARY

There is an issue with AntD select https://github.com/ant-design/ant-design/issues/3438.  The select popover doesn't move with scrolling.
AntD has provided a fix with getPopupContainer
BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF

BEFORE:
https://www.loom.com/share/fe9f3933852840859620d92a84a44926
AFTER:
https://www.loom.com/share/47aeef38b3bc44d7a1343e368558a411
TEST PLAN

ADDITIONAL INFORMATION

[ ] Has associated issue:
[x] Changes UI
[ ] Requires DB Migration.
[ ] Confirm DB Migration upgrade and downgrade tested.
[ ] Introduces new feature or API
[ ] Removes existing feature or API

/testenv up

/testenv up

@junlincc Ephemeral environment spinning up at http://<IP_ADDRESS>:8080. Credentials are admin/admin. Please allow several minutes for bootstrapping and startup.

@robdiciuccio work like a charm. thank you again!!!

Thanks for the pr @lilykuang! I wonder if there's a fix for popover on scroll? if so, we can take it on.
https://user-images.githubusercontent.com/67837651/111060878-f2c44380-8454-11eb-95f5-d9500cd59909.mov

Thanks for the pr @lilykuang! I wonder if there's a fix for popover on scroll? if so, we can take it on.
Screen.Recording.2021-03-13.at.11.30.32.PM.mov
@junlincc  I believed  getPopupContainer will also fix popover on scroll base on ant-design/ant-design#3438

@junlincc yup, this same logic should apply to other popups
https://github.com/apache/superset/pull/13585/files#diff-46790d612a7ba54f39c522c7359eba11e45e724e5efe695527c1f96ed45cb8adR107-R111
It's a known issue with antd, and this is their suggested fix. We can probably apply the logic to all "apps" and that should cover all other cases going forward.

Thank you both for clarifying, so we still need separate PRs that apply this logic to other components, right? i looked master, popover is still disconnected on scroll. @nytai 🙏

Yes, that's correct @junlincc


--system flag no longer working as documented

I have been using uv in virtual environments managed by pyenv virtualenv. The --system flag worked great with uv 0.1.45 but does not work with 0.2.5, and the docs still suggest that it should still work:

For convenience, uv pip install --system will install into the system Python environment, as an approximate shorthand for, e.g., uv pip install --python=$(which python3).

I understand that, currently, there are two work-arounds:

uv pip ... --python=$(which python)
python -m uv ...

But --system was more convenient, and it wasn't clear to me that it was intentional for it to have stopped working as previously.
Successful usage of --system flag with 0.1.45:
$ venv_name=uv-0.1.x
$ pyenv uninstall --force ${venv_name}
$ pyenv virtualenv ${venv_name}
$ pyenv shell ${venv_name}
$ pip install uv==0.1.45

[details omitted]

$ uv --version
uv 0.1.45 (a33a05e2d 2024-05-20)
$ pyenv version
uv-0.1.x (set by PYENV_VERSION environment variable)
$ python -c 'import sys; print(f"{(sys.prefix==sys.base_prefix)=}")'
(sys.prefix==sys.base_prefix)=False
$ uv pip install --system --upgrade pip setuptools wheel
Resolved 3 packages in 299ms
Installed 3 packages in 34ms
 - pip==22.3.1
 + pip==24.0
 - setuptools==65.5.0
 + setuptools==70.0.0
 + wheel==0.43.0
$ pyenv shell --unset

Unsuccessful usage of --system flag with 0.2.5:
$ venv_name=uv-0.2.x
$ pyenv uninstall --force ${venv_name}
$ pyenv virtualenv ${venv_name}
$ pyenv shell ${venv_name}
$ pip install uv

[details omitted]

$ uv --version
uv 0.2.5 (47db418ba 2024-05-28)
$ pyenv version
uv-0.2.x (set by PYENV_VERSION environment variable)
$ python -c 'import sys; print(f"{(sys.prefix==sys.base_prefix)=}")'
(sys.prefix==sys.base_prefix)=False
$ uv pip install --system --upgrade pip setuptools wheel --verbose
DEBUG Searching for Python interpreter in search path
DEBUG Found CPython 3.11.3 at `/Users/dpoznik/.pyenv/versions/uv-0.2.x/bin/python3` (search path)
DEBUG Ignoring Python interpreter at `/Users/dpoznik/.pyenv/versions/uv-0.2.x/bin/python3`: system interpreter required
DEBUG Found CPython 3.11.3 at `/Users/dpoznik/.pyenv/versions/uv-0.2.x/bin/python` (search path)
DEBUG Ignoring Python interpreter at `/Users/dpoznik/.pyenv/versions/uv-0.2.x/bin/python`: system interpreter required
DEBUG Found CPython 3.11.3 at `/Users/dpoznik/.pyenv/shims/python3` (search path)
DEBUG Ignoring Python interpreter at `/Users/dpoznik/.pyenv/versions/uv-0.2.x/bin/python3`: system interpreter required
DEBUG Found CPython 3.11.3 at `/Users/dpoznik/.pyenv/shims/python` (search path)
DEBUG Ignoring Python interpreter at `/Users/dpoznik/.pyenv/versions/uv-0.2.x/bin/python`: system interpreter required
DEBUG Found CPython 3.12.3 at `/usr/local/bin/python3` (search path)
DEBUG Using Python 3.12.3 environment at<EMAIL_ADDRESS>error: The interpreter at<EMAIL_ADDRESS>is externally managed, and indicates the following:

[additional details omitted]

$ uv pip install --python=$(which python) --upgrade pip setuptools wheel
Resolved 3 packages in 562ms
Uninstalled 2 packages in 654ms
Installed 3 packages in 29ms
 - pip==22.3.1
 + pip==24.0
 - setuptools==65.5.0
 + setuptools==70.0.0
 + wheel==0.43.0
$ python -m uv pip install --upgrade pip setuptools wheel
Resolved 3 packages in 1.08s
Audited 3 packages in 0.22ms
$ pyenv shell --unset

Thanks for your help with this issue and for developing this wonderful tool!

Thanks for the clear issue. I suspect the issue here is that the Python you're using appears to be that of a virtual environment, but --system now ignores any virtualenv Pythons. I will defer to @zanieb though who is the expert here and is on vacation this week.

Thanks for the quick reply! It sounds like the new behavior is intended, perhaps to better reflect the flag's name (i.e., "system"). That being the case, may I suggest the following solution?

Clarify the README.md discussion of --system to reflect the recent behavior changes
Add a new flag (e.g., --current-python) as shorthand for --python=$(which python3)

Ultimately, the issue is that uv doesn't recognize a pyenv virtualenv as being a virtual environment:
$ uv pip install --upgrade pip setuptools wheel --verbose
DEBUG Searching for Python interpreter in virtual environments
error: No Python interpreters found in virtual environments

I had been using --system to work around this, but --current-python, or something like that, would equally well and less klunky than --python=$(which python3).
Thanks!

I had been using --system to work around this, but if uv were to recognize a pyenv-virtualenv as a virtual environment, then no flag would be necessary. So that may be the best solution, if possible. I'd be happy to create a new issue if so.

Since this issue may just reduce to a request to update the documentation around --system, I went ahead and created a new issue specific to the pyenv-virtualenv issue: #4009.

Does #4031 help?

Does #4031 help?

Hmm, I'm not sure. I think the primary issue is in the previous paragraph, specifically the phrase:

as an approximate shorthand for, e.g., uv pip install --python=$(which python3)

In uv 0.1.x, I believe --system was more or less equivalent to --python=$(which python3), whereas this is not the case in uv 0.2.x, rendering the phrase misleading. I get that it includes the fuzzing term "approximate", but it's not currently clear in that paragraph under which conditions the equivalence holds.
Since, AFAICT, --python=$(which python3) will install for the current interpreter, and --system will do something different, I recommend removing the phrase and commenting separately on how to install for the current interpreter.
#4034 includes some suggestions. Feel free to use pieces of it or to ignore it completely.


Responsive Rubik Cube

i made the Rubik Cube Project Responsive .
Description
HTML Structure: We have a separate div element with the class ui__background for the background. This div will cover the entire viewport and serve as the background layer.
CSS Styles: In the CSS file, we set the background color of .ui__background to the desired color (#f0f0f0 in this example). Adjust the color code to your preference.
Responsive Design: This setup will automatically make the background responsive since it covers the entire viewport. You can further adjust the CSS to handle specific responsiveness requirements.
Fixes:  #219

[x ] I have made this from my own
[x ] I have taken help from some online resourses
[x ] My code follows the style guidelines of this project
[x ] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[x ] My changes generate no new warnings

ATTACH SCREEN-SHOTS / DEPLOYMENT LINK (if applicable)

@Dev-tanay please assign me

@Dev-tanay please review my pr


Not support macOS Sequoia 15.1

Workflow version
v2024.3
Alfred version
5.5.1 [2273]
macOS version
15.1
Debugger output
[15:04:11.258] Banner Be Gone[Keyword] Processing complete
[15:04:11.263] Banner Be Gone[Keyword] Passing output '' to Run Script
[15:04:11.314] Banner Be Gone[Run Script] Processing complete
[15:04:11.320] Banner Be Gone[Run Script] Passing output '15
' to Conditional
[15:04:11.321] Banner Be Gone[Conditional] Processing complete
[15:04:11.321] Banner Be Gone[Conditional] Passing output '15
' to Run Script

More details
No response

Done in 2024.4.


Check fails with "Graph ... is not a composition variant"

Thanks for making this handy action. I had it working fine for a several months, but sometime in the past week the checks have begun to fail on every run with an error that looks like the following. (My last successful run was on 3 Jan 2023.) I haven't changed anything in my GitHub workflow or in the project config in Apollo Studio.
Maybe something has changed on the Apollo side that is breaking this action?
{
  "response": {
    "errors": [
      {
        "message": "Graph my-graph@prod is not a composition variant.",
        "extensions": {
          "code": "INTERNAL_SERVER_ERROR",
          "serviceName": "registry"
        }
      }
    ],
    "data": {
      "service": null
    },
    "status": 200,
    "headers": {}
  },
  "request": {
    "query": "\n    mutation SubgraphCheckMutation(\n      $graph: ID!\n      $variant: String!\n      $serviceName: String!\n      $proposedSchema: PartialSchemaInput!\n      $gitContext: GitContextInput!\n      $queryParameters: HistoricQueryParameters!\n    ) {\n      service(id: $graph) {\n        checkPartialSchema(\n          graphVariant: $variant\n          implementingServiceName: $serviceName\n          partialSchema: $proposedSchema\n          gitContext: $gitContext\n          historicParameters: $queryParameters\n        ) {\n          compositionValidationResult {\n            compositionSuccess\n            errors {\n              message\n              code\n              locations {\n                line\n                column\n              }\n            }\n          }\n          checkSchemaResult {\n            diffToPrevious {\n              severity\n              numberOfCheckedOperations\n              numberOfAffectedOperations\n              changes {\n                severity\n                code\n                description\n              }\n            }\n            targetUrl\n          }\n        }\n      }\n    }\n  ",
    "variables": {
      "config": "",
      "graph": "my-graph",
      "variant": "prod",
      "endpoint": "",
      "headers": "",
      "apolloKey": "***",
      "localSchemaFile": "./schema.graphql",
      "queryCountThreshold": "",
      "queryCountThresholdPercentage": "",
      "serviceName": "api",
      "validationPeriod": "P1W",
      "queryParameters": {
        "from": "604800"
      },
      "proposedSchema": {
        "sdl": "...SNIPPED..."
      },
      "gitContext": {
        "branch": "my-branch",
        "commit": "f023dc73242f4783d686732cdac666824bdd81b3",
        "committer": "sgarner",
        "message": "Merge 34f1e656ede5d3b56c291d93f4b38cbdae53e730 into 212b0831269d1098486146328eb03aa9718a126c",
        "remoteUrl": "https://github.com/sgarner/my-graph/commit/f023dc73242f4783d686732cdac666824bdd81b3"
      }
    }
  }
}

I am facing the same issue... Did you find a solution @sgarner ?


Harvesting screen. The tabs aligment issue

Current behaviour
Tabs are scrolled with the page

Expected behaviour
Tabs are fixed at the top

Version
1.0.2

Fixed on branch gh1430-fees-selector-ordering

Fixed in integration branch.


Code of NYUD2

Is the code of noise experiments on NYUD2 the same as text-image datasets?
I conducted the noise experiments on the NYUD2 dataset; however, the accuracy is lower than the paper's.

Hi, we randomly and independently add noise to RGB and Depth modality for NYUD2 experiments. That is, we apply torchvision.transforms.RandomApply(add_noise, p＝0.5) for each modality individually. Thus we should expect 25% samples with both modalities corrupted, 25% samples with RGB modality corrupted only, 25% samples with Depth modality corrupted only and 25% clean samples. Due to my current busy schedule, I will update the test code to GitHub later. Sorry for any inconvenience.

. Thus we should expect 25% samples with both modalities corrupted, 25% samples with RGB modality corrupted only, 25% samples with Depth modality corrupted only and 25% clean samples.

Thank you for your response. I would greatly appreciate it if you could share your code on GitHub.

. Thus we should expect 25% samples with both modalities corrupted, 25% samples with RGB modality corrupted only, 25% samples with Depth modality corrupted only and 25% clean samples.

Thank you for your response. I would greatly appreciate it if you could share your code on GitHub.

Hi, I have updated the repo and add test.py in the RGBD-scene-recognition folder. The results are the same with I reported in the manuscript. Free feel to contact me if you still have trouble in reproducing.

. Thus we should expect 25% samples with both modalities corrupted, 25% samples with RGB modality corrupted only, 25% samples with Depth modality corrupted only and 25% clean samples.

Thank you for your response. I would greatly appreciate it if you could share your code on GitHub.

Hi, I have updated the repo and add test.py in the RGBD-scene-recognition folder. The results are the same with I reported in the manuscript. Free feel to let me informed whether you still have troubles in reproducing. Thus I can continue help you to debug or close this issue.

Thank you for your generous sharing. But I noticed your adding noise code is same as text-image datasets. The package named the additional_transform.AddGaussianNoise is the same as the dataset.AddGaussianNoise, right? I conduct your experiment on this nyud2 dataset from scratch, but can't reach your accuracy.

That sounds weired. I also downloaded the datasets and trained from scratch myself. Here is my results:

$\epsilon=0.0$, acc=70.33
$\epsilon=5.0$, acc=61.47
$\epsilon=10.0$, acc=54.89

Due to time limits, I only trained and tested once with random seed=1. The result is slightly different with that in the manuscript. Would you mind to share your code and accuracy?


SPLAT-1440: prevent rollout due to irrelevant path artifacts

changes:

prevent the control plane machineset from rolling out if irrelevant path artifacts are in the resource pool path
fixed the casing of the resource pool path
increased unit test coverage
bumped the API(and cpms CRD) to api#1759

/test unit

/hold

/retest-required

/retest-required

/test unit

/test unit

/test e2e-vsphere-operator

/payload-job	periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn	periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn-techpreview

/payload-job periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn-techpreview

/retest-required

/payload-job periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn-techpreview periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-zones

/payload-job periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn-techpreview periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-zones

/test lint

/test unit

/test e2e-vsphere-multi-zone-operator

/payload-job periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn-techpreview periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-zones

/assign @damdo

e2e-vsphere-multi-zone-operator looks like it nearly passed, it just ran out of time.  things seemed to be progressing.  payload tests are looking good.  im going to re-run tech preview as it seemed to flake.

/payload-job periodic-ci-openshift-release-master-nightly-4.16-e2e-vsphere-ovn-techpreview

tech preview payload looks good

/retest-required

/test unit

/assign @jcpowermac

/lgtm

/assign @JoelSpeed

/assign @damdo

@JoelSpeed said he's happy with this.
CI failures:

most/all GCP CI jobs have issue due to unknown bug
aws, vsphere etcd-scaling issues look unrelated
azure and openstack have issues installing, but passed in previous runs
All these are optional ☝

Based on this
/approve

Will it back port to 4.15? IIRC https://issues.redhat.com/browse/OCPBUGS-29236 need to get verified after it back port to 4.15.


Feature - linkerd addon.

This feature allows enabling linkerd from microk8s.  Linkerd version is 2.2.0

Since fluentd is for amd64 arch, you probably should remove the enable/disable scripts from the actions in the case of arm64, this is done for example with istio at https://github.com/ubuntu/microk8s/blob/master/snapcraft.yaml#L189

Also would be useful to configure the LINKERD_VERSION with an env var. Have it default to 2.2.0 but let it be configurable, here is an example with istio: https://github.com/ubuntu/microk8s/blob/master/build-scripts/prepare-env.sh#L16, and also print it here: https://github.com/ubuntu/microk8s/blob/master/build-scripts/prepare-env.sh#L38

Suddenly i get this error at the end of travis build
Download snap "microk8s" (455) from channel "edge" (received an unexpected http response code (503) when trying to download https://fastly.cdn.snapcraft.io/download-origin/fastly/EaXqgt1lyCaxKaQCU349mlodBkDCXRcg_455.snap?token=1552197600_54dbb3e4cc3838fa6f4fc07e812ec7113e35d15e)

That was a transient error @balchua. Seems ok now.

Thanks!

Thank you for the PR @balchua. Looks great, solid work! There is only one comment I would like addressed before accepting it.
@waquidvp thank you for the review.

Thanks.  @ktsakalozos good idea.  I will move the downloading of linkerd binary at the time of enabling the addon.
I have some question though, current version of linkerd allows the user to auto inject the proxy very much like what istio does today.
I was thinking of providing some user option to enable the auto proxy inject.
What do you think?

Thanks @balchua, the enable command sounds fine for grabbing the linkerd binary.
How would the user experience look like in the case of this extra option. For istio we ask the user during the microk8s.enable istio action. The drawback with this approach is that you cannot include microk8s.enable istio easily in scripts. We are considering the option of adding configuration parameters (https://github.com/ubuntu/microk8s/issues/157#issuecomment-437310716) but we are open to any suggestions.

I was thinking of adding arguments to enable command.  But at the same time not too many knobs to turn on/off.

Arguments on the enable command may not work well as the users are able to queue the enabling of more than one addons, eg microk8s.enable dns dashboard linkerd. How would these arguments look like in this context?

Just realized that users can enable multiple addons in one go.
In this context it would look like microk8s.enable linkerd --auto-inject-on dns dashboard. But then the user experience will be strange..

Was just thinking out loud.  What if the args are specified microk8s.enable linkerd:auto-inject=on;other-opts=xx dns dashboard.

microk8s.enable linkerd:auto-inject=on;other-opts=xx dns dashboard

This look good. Please put the arguments parsing in utils.sh (https://github.com/ubuntu/microk8s/blob/master/microk8s-resources/actions/common/utils.sh) so we can use it in both the enable and disable wrappers. Thank you.

Linkerd addon with optional argument to pass during enable.  it looks like this now microk8s.enable linkerd:--proxy-auto-inject  On reset, $SNAP_DATA/bin is deleted.  In the future, addon binaries will automatically be cleaned up upon reset.  When disabling the addon, the linkerd binary is also deleted.

@ktsakalozos, i am trying to work out the items you highlighted especially the one limiting the arguments passed to linkerd.  I would like to allow the user to have as much as possible similar experience as using the native linkerd install command during linkerd enable..  that's why i didn't try to limit the args passed during enable.  Still some work to do here by removing -- on the args and implicitly add them inside the wrapper.  This will force linkerd  to disallow arguments unknown to it. What do you think? Thanks.

Another thing i noticed is that when using $SNAP_DATA the user needs to have permission to it, hence it requires sudo.  What about using $SNAP_USER_DATA/bin to keep user binaries?

This will force linkerd to disallow arguments unknown to it. What do you think?

Sounds good to me.

What about using $SNAP_USER_DATA/bin to keep addon binaries?

I do not know about that. What if there are many users on the machine?

The documentation wasn't very clear about multiple users.
From the documentation
SNAP_USER_DATA
Directory for user data.
This directory is backed up and restored across snap refresh and snap revert operations.
Typical value: /home/zyga/snap/hello-world/27
The final number there is $SNAP_REVISION
I guess it wouldn't work for other users in the same system.

Thank you for this PR @balchua and for your patience!


missing symbols in components

Across a number of versions are different platforms some users are experiencing all symbols missing in components view. All functions are listed as sub_* for example instead of their actual name. Saving a BNDB and opening on another machine may result in all symbols being visible. See Josh for a repro, also reported by a customer on Ubuntu 22.04 and 23.10 but didn't reproduce on Jordan's 22.04 Stream VM so it's unclear what might be the root cause.

Should be resolved in builds >= 3.4.4230


ZTF photometry not the same as ATLAS - and ATLAS is correct

This is very odd :
this ZTF object
https://lasair.roe.ac.uk/object/ZTF18abhqeds
is  the same object as ATLAS
https://star.pst.qub.ac.uk/sne/atlas4/candidate_bs/1222824041134943200/
But the ZTF lightcurve is totally different  - it is bright and flat 120 days ! But that is not believable. Don't understand what is going on here. The ATLAS data show no bright object after the first detection

Odd indeed.  But the issue goes back to ZTF I think. Same lightcurve on MARS.
https://mars.lco.global/20501975/

As Ken sees the same in MARS, we need to alert ZTF. Presume this repo is public - we can point Matthew to it.

From: Eric C. Bellm<EMAIL_ADDRESS>Sent: 20 November 2018 7:07 PM
To: Roy Williams
Cc: Graham, Matthew J.
Subject: Re: wacko object in ZTF
Hi Roy,
It looks like the object has an underlying counterpart in the reference image:
distnr	0.155174
magnr	17.062
So the difference image photometry (magpsf) needs to be corrected to add the flux from the reference counterpart to get the appropriate DC magnitude.  Note that the reference flux will be different in different fields (or even different readout quadrants of the same CCD) which accounts for the offset you see between the two fields--the magnr value is 15.742 in the other field.
Best regards,
Eric
On Tue, Nov 20, 2018 at 8:50 AM Roy Williams<EMAIL_ADDRESS>wrote:
Hi Matthew and Eric
Here is a strange object
https://lasair.roe.ac.uk/object/ZTF18abhqeds/
The magnitudes bounce up and down in a slightly unbelievable way. For example these two candidates belong to this object, the r magnitude changes by 1.5 in 2 minutes.
2458400.728     2018-10-09 05:27:53     r       16.109 ± 0.041<PHONE_NUMBER>15010014
2458400.726     2018-10-09 05:25:53     r       17.676 ± 0.110<PHONE_NUMBER>15010000
One is on field 546 and the other on field 547.
Roy

Ah, of course ! The stamps are  REF - TARGET - DIFF (from left to right; I missed that, we usually have TARGET - REF - DIFF).
And this flux is negative - which is of course correct. The negative object flag is set :
isdiffpos = f
So, we need a way to flag these as -ve detections. We can treat them the same, but just plot them as negative.
All OK - I understand now. I think we can keep the plots the same, all we do is plot in the isdiffpos=f points in a different symbol.  But we need to make all the symbols a little larger to see it.
For example, we plot the -ve values in ATLAS as large transparent diamonds.


Possible BUG in TwoQubit-VQE.ipynb

In the last ChainBlock in Out[370], the 2 MeasureBlocks are printed as:
   ├─ Measure{2,1,AbstractBlock}
   └─ Measure{2,1,AbstractBlock}

Should one be Measure{2,2,AbstractBlock} for it should be put on the 2nd line of the circuit? Maybe you should fix the function twoqubit_circuit in Out[369].

This is not a bug, the second type parameter means "how many qubits" got measured. So, it is the printing should be improved. :sorry

@GiggleLiu Shall we close this if you already improved print?


Created cart get, post and put routes

Assignee Tasks

[ ] added unit tests (or none needed)
[ ] written relevant docs (or none needed)
[ ] referenced any relevant issues (or none exist)

Guidelines
Please add a description of this Pull Request's motivation, scope, outstanding issues or potential alternatives, reasoning behind the current solution, and any other relevant information for posterity.

Your PR Notes Here

merged updates into master


Testing failed

Hi
I tried this repository but failed for training.
Throwing error - SyntaxError: Non-ASCII character '\xe4' in file main.py on line 34,  but no encoding declared; see http://python.org/dev/peps/pep-0263/ for details
screenshot is attached.

Resolved the problem.

Hey while testing, I am not getting visual results. The checkpoints are loaded successfully but testing images are not getting generated. See screenshot

Hey while testing, I am not getting visual results. The checkpoints are loaded successfully but testing images are not getting generated. See screenshot

According to your screenshoot, everything went well.
Just wait for generating 100 images.

Thanks for reply. But after that it is not generating images. Why so?.. I
have checked the folder. No image is generated.
Kindly do help.
On Thu, 8 Aug 2019, 12:19 SunRuikang<EMAIL_ADDRESS>wrote:

Hey while testing, I am not getting visual results. The checkpoints are
loaded successfully but testing images are not getting generated. See
screenshot
[image: error-2]
https://user-images.githubusercontent.com/22466907/62676023-f6fdc480-b9c6-11e9-85d8-680e7abfb276.png
According to your screenshoot, everything went well.
Just wait for generating 100 images.
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Thanks for reply. But after that it is not generating images. Why so?.. I have checked the folder. No image is generated. Kindly do help.
…
On Thu, 8 Aug 2019, 12:19 SunRuikang, @.***> wrote: Hey while testing, I am not getting visual results. The checkpoints are loaded successfully but testing images are not getting generated. See screenshot [image: error-2] https://user-images.githubusercontent.com/22466907/62676023-f6fdc480-b9c6-11e9-85d8-680e7abfb276.png According to your screenshoot, everything went well. Just wait for generating 100 images. — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#3?email_source=notifications&email_token=AFLNCW4EDQA5BLAN5N4W4Y3QDO6WVA5CNFSM4IKGFHL2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD32UMWY#issuecomment-519390811>, or mute the thread https://github.com/notifications/unsubscribe-auth/AFLNCWZGGFV2CJQJ6WJ5CWDQDO6WVANCNFSM4IKGFHLQ .

check here: YOUR_PATH\out\KaiFaZheZuiShuai\samples

Thanks it works for my dataset but results are not good. I also trained
with 90 images as you did.  Does it require more data to work better. This
implementation is for unconditional GAN right??
On Fri, 9 Aug 2019, 09:11 SunRuikang<EMAIL_ADDRESS>wrote:

Thanks for reply. But after that it is not generating images. Why so?.. I
have checked the folder. No image is generated. Kindly do help.
… <#m_5789887752544898574_>
On Thu, 8 Aug 2019, 12:19 SunRuikang, @.***> wrote: Hey while testing,
I am not getting visual results. The checkpoints are loaded successfully
but testing images are not getting generated. See screenshot [image:
error-2]
https://user-images.githubusercontent.com/22466907/62676023-f6fdc480-b9c6-11e9-85d8-680e7abfb276.png
According to your screenshoot, everything went well. Just wait for
generating 100 images. — You are receiving this because you authored the
thread. Reply to this email directly, view it on GitHub <#3
https://github.com/RuikangSun/teen-girl-generator/issues/3?email_source=notifications&email_token=AFLNCW4EDQA5BLAN5N4W4Y3QDO6WVA5CNFSM4IKGFHL2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD32UMWY#issuecomment-519390811>,
or mute the thread
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check here: YOUR_PATH\out\KaiFaZheZuiShuai\samples
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I trained the model with pnb images, could it be a problem or not for good
results.?
On Fri, 9 Aug 2019, 11:30 anishi gupta<EMAIL_ADDRESS>wrote:

Thanks it works for my dataset but results are not good. I also trained
with 90 images as you did.  Does it require more data to work better. This
implementation is for unconditional GAN right??
On Fri, 9 Aug 2019, 09:11 SunRuikang<EMAIL_ADDRESS>wrote:

Thanks for reply. But after that it is not generating images. Why so?.. I
have checked the folder. No image is generated. Kindly do help.
… <#m_3033850344420101567_m_5789887752544898574_>
On Thu, 8 Aug 2019, 12:19 SunRuikang, @.***> wrote: Hey while testing,
I am not getting visual results. The checkpoints are loaded successfully
but testing images are not getting generated. See screenshot [image:
error-2]
https://user-images.githubusercontent.com/22466907/62676023-f6fdc480-b9c6-11e9-85d8-680e7abfb276.png
According to your screenshoot, everything went well. Just wait for
generating 100 images. — You are receiving this because you authored the
thread. Reply to this email directly, view it on GitHub <#3
https://github.com/RuikangSun/teen-girl-generator/issues/3?email_source=notifications&email_token=AFLNCW4EDQA5BLAN5N4W4Y3QDO6WVA5CNFSM4IKGFHL2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD32UMWY#issuecomment-519390811>,
or mute the thread
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check here: YOUR_PATH\out\KaiFaZheZuiShuai\samples
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Sorry it was png images. But I am not getting satisfactory result with few
images.
On Fri, 9 Aug 2019, 11:34 anishi gupta<EMAIL_ADDRESS>wrote:

I trained the model with pnb images, could it be a problem or not for
good  results.?
On Fri, 9 Aug 2019, 11:30 anishi gupta<EMAIL_ADDRESS>wrote:

Thanks it works for my dataset but results are not good. I also trained
with 90 images as you did.  Does it require more data to work better. This
implementation is for unconditional GAN right??
On Fri, 9 Aug 2019, 09:11 SunRuikang<EMAIL_ADDRESS>wrote:

Thanks for reply. But after that it is not generating images. Why so?..
I have checked the folder. No image is generated. Kindly do help.
… <#m_8440621871423766029_m_3033850344420101567_m_5789887752544898574_>
On Thu, 8 Aug 2019, 12:19 SunRuikang, @.***> wrote: Hey while
testing, I am not getting visual results. The checkpoints are loaded
successfully but testing images are not getting generated. See screenshot
[image: error-2]
https://user-images.githubusercontent.com/22466907/62676023-f6fdc480-b9c6-11e9-85d8-680e7abfb276.png
According to your screenshoot, everything went well. Just wait for
generating 100 images. — You are receiving this because you authored the
thread. Reply to this email directly, view it on GitHub <#3
https://github.com/RuikangSun/teen-girl-generator/issues/3?email_source=notifications&email_token=AFLNCW4EDQA5BLAN5N4W4Y3QDO6WVA5CNFSM4IKGFHL2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD32UMWY#issuecomment-519390811>,
or mute the thread
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check here: YOUR_PATH\out\KaiFaZheZuiShuai\samples
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I also had the same problem：
The checkpoints are loaded successfully but testing images are not getting generated.


@conda-forge-admin, please rerender

Additional comment:
No response

to rebuild for this build failure: https://dev.azure.com/conda-forge/feedstock-builds/_build/results?buildId=1051012&view=logs&j=010ccbe2-65a2-511e-4dd5-d2897d667254&t=ee960301-6956-5aba-e0e0-771e35e4981b


Add main as a wrapper for story content

Closes
https://github.com/adobe/react-spectrum/issues/1268
This seems to be a real quick fix -- simply adding a main wrapper in .storybook/custom-addons/provider/index.js would do the trick.
Before:

After:

✅ Pull Request Checklist:

[x] Included link to corresponding React Spectrum GitHub Issue.
[ ] Added/updated unit tests and storybook for this change (for new code or code which already has tests).
[x] Filled out test instructions.
[ ] Updated documentation (if it already exists for this component).
[x] Looked at the Accessibility Practices for this feature - Aria Practices

📝 Test Instructions:

add the aXe devtools to your chrome extension
choose a story arbitrarily and open it in a new tab
run aXe against the entire page, check if the warning is still there

🧢 Your Project:

Did you confirm that opening this in another tab via the button Danni mentioned did or didn't work for aXe and landmark?

Yes, i checked the "no main landmark" error is gone (see the second screenshot above)

GET_BUILD


fix: Reduce README complexity

Fixes #

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache-2.0 license

Testing less-complex README


2nd test fails

Challenge add-a-boxshadow-to-a-cardlike-element has an issue.
User Agent is: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36.
Please describe how to reproduce this issue, and include links to screenshots if possible.
2nd test does not work when the given CSS is used

Alphabet

Google was founded by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University.

      Larry Page

      Sergey Brin

You only supplied the color value for offset-x and not offset-y, rgba(0,0,0,0.23).

yep, i realized that as soon as i submitted.  Window is cropped and it makes it look like that's all needed.


Free for Open Source Application

I developed a mmr search site as a toy project.
However, 429 errors appear because the API request amount is limited.
github: https://github.com/ymh0951/My-LOL-MMR

Hey. Thank you for your submission. I'll take a look and get back to you within few days. Before we continue, can you kindly answer below questions?

Is the site currently online? If so, please provide the address to it.
Are you getting 429 from your live website or from local dev environment?
-Is your project using the legacy cors.bridged.cc ? (It recently migrated to Cors.sh)
How many users do you have and what is the estimated requests per month? (Not per user, but throughout the entire site)

Thank you. :)
지원해 주셔서 감사합니다.

Is the site currently online? If so, please provide the address to it.

github: https://github.com/ymh0951/My-LOL-MMR
website: https://ymh0951.github.io/My-LOL-MMR

Are you getting 429 from your live website or from local dev environment?
-Is your project using the legacy cors.bridged.cc ? (It recently migrated to Cors.sh)

I'm communicating with Axios.
The api is used by 'What is my mmr?'

How many users do you have and what is the estimated requests per month? (Not per user, but throughout the entire site)

It's just been developed, so there aren't many users.
The amount of api requests provided by 'LOL' is limited to 60 per minute


Add additional mapbox maps

Add ability to replace the mapbox map with grayscale, political or potentially other maps

@lee-orr I found a few examples of the types of map layers that we'd like to have:

Hillshading
Hillshading
Political boundaries

@brendanjmeade, @jploveless & @Emilycm-97 - I've implemented this feature so that it includes a few default maps, but also has the ability to let you add custom maps as you wish. You can generate those maps using mapbox studio, or by finding a link. Here is an example where I'm using a custom blueprint-style map:

@lee-orr Works great now.  Thanks!


Expose Object metadata property

This is useful when setting or getting the whole metadata.

I'm not sure it is a good idea. For example, each plugin might need its specific set of metadata while another need another set. Allowing a global set might erase data from another plugins.
Also, I don't see any usecase for that.

@groud For the use case: Currently on my project I have a data.gd that stores game data on a Dictionary variable, when loading/saving I need to get/set the whole Dictionary data on that variable. I've found out that I can use metadata for this instead and on GDNative its faster calling data->get_meta than doing a data->call.

Well, what you could do is simply use a Dictionary as a metadata variable, instead of using the metadata as your dictionary.
Something like:
var save_dict= {
    health = 10,
    level = 2
}
my_object.set_metadata("_save_dict", save_dict);

That is a cleaner way to solve your problem, and keeps the metadata structure available for other uses (including plugins).

Alright, thanks for the solution.


Would you like to contribute some features back to wong2/chat-gpt-google-extension ?

Hey Wong, I have a somewhat different vision for how I wanted to make this extension function, so some features may not make sense/work correctly in “ChatGPT for Google”.  But yea, if you see features from here that do make sense to add in, I'd be happy to contribute/make PR to get them in.


Rav1dTaskContext::a: Make into offset and give BlockContext interior mutability

Once a was made into an offset, accesses to f.a[t.a] ran into borrowing issues because we need to mutate that data through an immutable reference to f. To fix this I wrapped the fields of BlockContext in DisjointMut, as the fields are being accessed concurrently from multiple threads, with different threads accessing disjoint parts of the arrays. I also added support for using CaseSet with DisjointMut via a new CaseSetter::set_disjoint method, since all of the fields of BlockContext are used with CaseSet at some point.
I also broke up the t argument to decode_coefs in order to address borrow issues: The l argument to decode_coefs is always a reference to t.l, and t is also passed mutably into the function, which causes borrow errors. Only a few fields of t are used within decode_coefs, so passing the fields in individually addresses the borrow issues. This also makes the arguments safe, since previously t was being passed in as a raw pointer. This then in turn required that the get and set methods on CfSelect take a &mut BitDepthUnion<Cf> directly, rather than being passed the entire Rav1dTaskContext.
A few of these fields (e.g. partition and uvmode) could probably be made atomic instead of using DisjointMut, since only individual elements are read, rather than a full slice being taken, but I opted to use DisjointMut for all of them for simplicity. I think the only requirement to use atomics for some of these fields would be atomic support in CaseSet.

Note to self: Squash this on merge because not all of the intermediate commits compile/pass tests.


Extensions scope

I want to solve this crucial question before start: Is it possible to create an extension to implement at Organization level?
What I want to do is to create a new tab in the Organization panel, so you can have the following tabs:
Projects / My Work Items / My Pull Requests / [MY EXTENSION]
In my extension I want to show all active pull request for all projects.
Thank you.

@ohmybeer -- Pachidev, thanks for your feedback; we appreciate it. To make sure we have all the information needed to triage your issue, please let us know which topic you’re referencing, or provide more context around the general task.

@pachidev -- thank you for clarifying.  You may find answers here:

Azure DevOps on Stack Overflow
Azure DevOps Support Bot

If you have in mind a specific article in our documentation, please let me know.
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Support custom sorting function

Add the migrationSorting argument to support custom sorting. (resolve #153)

Hello! Thanks for the PR!
I have merged & published a huge rewrite so your PR is now outdated from the codebase :sweat_smile: can you please rebase?
In short, you will have to re-implement what you did into umzug.ts now.
Thank you!

It's really a huge change. I have re-implemented with typescript. Thanks!

@rockers7414 Thanks for rebasing! May I ask you to please create a test for this feature, in test/test.ts?
Hint: for quicker testing you can run npx ava test/test.ts instead of npm test.

@papb Hey, I've created the test for PR. Please help to review it. Thanks!

Released at v3.0.0-beta.4!


fix: Improve detection of degraded APIConnectCluster in Cloud Pak for…

Improve detection of degraded APIConnectCluster in Cloud Pak for
closes: #253
Description of changes:

Apply Platform Navigator first, and only then MQ and API Connect (those two can go in parallel)

Output of argocd app list command or screenshot of the ArgoCD Application synchronization window showing successful application of changes in this branch.
argocd app list
NAME                 CLUSTER                         NAMESPACE         PROJECT               STATUS  HEALTH   SYNCPOLICY  CONDITIONS  REPO                                    PATH                                    TARGET
argo-app             https://kubernetes.default.svc  openshift-gitops  argocd-control-plane  Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/argocd                           253-apic-status
cp-shared-app        https://kubernetes.default.svc  ibm-cloudpaks     default               Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/argocd-cloudpaks/cp-shared       253-apic-status
cp-shared-operators  https://kubernetes.default.svc  ibm-cloudpaks     default               Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/cloudpaks/cp-shared/operators    253-apic-status
cp4i-apic            https://kubernetes.default.svc  cp4i              default               Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/cloudpaks/cp4i/install-apic      253-apic-status
cp4i-app             https://kubernetes.default.svc  cp4i              default               Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/argocd-cloudpaks/cp4i            253-apic-status
cp4i-mq              https://kubernetes.default.svc  cp4i              default               Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/cloudpaks/cp4i/install-mq        253-apic-status
cp4i-platform        https://kubernetes.default.svc  cp4i              default               Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/cloudpaks/cp4i/install-platform  253-apic-status
cp4i-prereqs         https://kubernetes.default.svc  cp4i              default               Synced  Healthy  Auto-Prune  <none>      https://github.com/IBM/cloudpak-gitops  config/cloudpaks/cp4i/install-prereqs   253-apic-status

:tada: This PR is included in version 0.24.2 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Incompatibility with jwt > 0.1.11

Hi,
you should consider to update your gemspec as your gem is likely to break with jwt 1.0 due to the following commit: https://github.com/progrium/ruby-jwt/blob/master/lib/jwt.rb#L106
The decode method now returns an Array with the payload body and header instead of  the body as a hash.
Thanks,
Tobias

Is there any updates or similar libs?

@lappi-lynx I rewrote this gem and modernized it!
https://github.com/pboling/omniauth-jwt2


[ode:x64-windows] build failure

Host Environment

OS: windows 10
Compiler: vs 2019 (latest)

To Reproduce
Steps to reproduce the behavior:
c:\src\vcpkg>vcpkg install --recurse --triplet x64-windows dartsim
config-x64-windows-out.log
Failure logs
Package: ode:x64-windows
Vcpkg version: 2020.11.12-nohash
Additional context
Add any other context about the problem here, such as what you have already tried to resolve the issue.

@editing00 ,What is the exact version of GCC that you are using?

Dear JonLiu
I'm using visual studio 2019, CMAKE and vcpkg on the windos 10.
from namkyung Yoon
-----Original Message-----
From<EMAIL_ADDRESS>To<EMAIL_ADDRESS>Cc<EMAIL_ADDRESS><EMAIL_ADDRESS>Sent: 2020-12-23 (수) 11:25:01 (GMT+09:00)
Subject: Re: [microsoft/vcpkg] [ode:x64-windows] build failure (#15250)
@editing00 ,What is the exact version of GCC that you are using?
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cmake 3.19.1   visual studio 2019     Qt 5.12.1     vcpkg 2020-11-12-nohash

@editing00 ,I can successfully build ode on my computer,I investigated some related issues and found that the version of Cmake does affect the construction of the port. My cmake version is cmake-3.18.4-win32-x86, you can try to build with the old version

@editing00 ,I can successfully build ode on my computer,I investigated some related issues and found that the version of Cmake does affect the construction of the port. My cmake version is cmake-3.18.4-win32-x86, you can try to build with the old version

Yes It works with cmake, but I mean, it doesn't work with vcpkg command

By inspecting the log, the error seems to be:

CMake Error: install(EXPORT "ODE" ...) includes target "ODE" more than once in the export set.

I guess this is due to this bug in CMake 3.19.0 and 3.19.1 : https://gitlab.kitware.com/cmake/cmake/-/issues/21529 . I did not checked, but I guessed probably it should be fixed by using CMake 3.19.2 .

By inspecting the log, the error seems to be:

CMake Error: install(EXPORT "ODE" ...) includes target "ODE" more than once in the export set.

I guess this is due to this bug in CMake 3.19.0 and 3.19.1 : https://gitlab.kitware.com/cmake/cmake/-/issues/21529 . I did not checked, but I guessed probably it should be fixed by using CMake 3.19.2 .

@editing00 ,Thanks for posting this issuse, please use CMake 3.19.2, Please reopen this issue if it still be a problem for you


Support pages in subdirectories

I know this is indicated in the known limitations:

The repository is "flat" (no directories or namespaces)

Would it be complex to add the support for putting pages in subdirectories? (Gollum supports this already.)
I tried pickling with the code but I have to admit that this touches too much parts and I break everything trying to do it.

Hi Robin,
I didn't implemented that feature because it can create some edge cases and I didn't have a valid use case for that. What kind of problem are you trying to solve?

Hi Claudio,
I plan to migrate an existing plone cms with a lot of content to a more modern and faster wiki.
In our cms we have a lot of pages with the same name but in different directories.
Also, when editing/browsing the source files after a git clone having subdirectories helps a lot categorizing pages.
What are the edge cases you are talking about?
By the way, I have been using jingo for a few days and it rocks! Congratulations for such a good job!

@robin-jarry Could you point out some documentation or code from Gollum where this feature is betalked? I am unable to find any reference.
In experiences with http://django-wiki.org, I can only tell having a flat namespace helps a lot not to confuse layers of abstraction. An edge case would for example be to move a page from one folder to the other and update all related links. Or would you also want to keep redirect rules? There is a lot to consider.
This is not to be confused with :link: Subpages in Gollum, which are despite the Header one, already implemented in Jingo.
Even with a flat namespace you can create virtual navigation layers with those. http://realms.io doesn't do any different. Neither does the http://federated.wiki.

@almereyda on the link about subpages you posted, it is specifically mentioned:

Subpages affect all pages in their directory and any subdirectories that do not have a subpage of their own.

Here is another example from gollum source code that pages in subdirectories are supported: https://github.com/gollum/gollum/blob/master/lib/gollum/public/gollum/javascript/gollum.js#L213
Another git-based wiki: Gitit also supports this.
As for the necessity of this feature, it depends on what you use the wiki for. My thinking is that organizing is easier when you can put pages in sub folders. Like for a file-system, you don't store every file of a Linux installation in /, do you? :-)

I would also like directories (use case: migrating a large MojoMojo wiki), and/or even better, tags for pages.

@almereyda
You write:

Even with a flat namespace you can create virtual navigation layers with those. http://realms.io doesn't do any different. Neither does the http://federated.wiki.

Does that mean that the restriction of a flat hierarchy is only with the actual file system? Can I have namespaces (or categories or whatever you want to call it) within the wiki after all?

Well, you can always build your own (nested) navigation within _sidebar.md
or _footer.md .
On 13 September 2016 at 20:33, MatthiasKauer<EMAIL_ADDRESS>wrote:

@almereyda https://github.com/almereyda
You write:
Even with a flat namespace you can create virtual navigation layers with
those. http://realms.io doesn't do any different. Neither does the
http://federated.wiki.
Does that mean that the restriction of a flat hierarchy is only with the
actual file system? Can I have namespaces (or categories or whatever you
want to call it) within the wiki after all?
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We already have a git repository which has a folder-based structure. I would gladly use jingo for that repo, but I don't want to miss the folder structure...

In fact, what http://progrium.viewdocs.io/viewdocs/ does.
On 11 January 2017 at 21:52, leo90skk<EMAIL_ADDRESS>wrote:

We already have a git repository which has a folder-based structure. I
would gladly use jingo for that repo, but I don't want to miss the folder
structure...
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Is there any plan on this?

I am thinking about it now, since there is apparently a lot of interest on the topic


Human readable data appears below field

@kthorat-prog @adamgibs so with this change I would suggest breaking this out into separate components. There is really no point in have one component and then having separate logic for each case. Just make 6 different components and keep the logic all internal to the component.

For instance if you were to have a <SubjectAdditionalData subject="data.subject"/>  Then this can be reused anywhere that we want to see "Additional Data" for the subject field.

@oblodgett @kthorat-prog makes sense to me. Also, I think the UI build is failing because of the breaks after the returns in the switch. I don't think they are needed if you are already returning.

Created another PR for same


adding nginx proxy

biggest changes w/ this PR are the following:

moving server.py to port 8080
added puppet modules (bulk of new files) to configure nginx
setup node to serve nginx at port 80 and proxy chaosthebot.com requests to localhost:8080

This will allow us to serve different content from different servers without any issue.
i.e.
If you wanted to create a standalone restful api at chaosthebot.com/XYZapi but wanted to do it w/ node versus python, you could easily do so and nginx would handle the proxy bits.

Relevant changes are site.pp, setup_nginx.pp, server.py.
The rest is mostly puppet module files/dependencies for managing nginx (taken off of the puppet forge).

It's just hard to review when so much content is added at once

I'm not biased at all, but seriously let's do this in a few lines of ansible rather than 45000 lines of puppet.

@g19fanatic can you consider simplifying this?  700 files and 48k lines of code is absurd for the intended outcome

Those lines of puppet are libraries. How is this any different than including libraries for any other process.
Its including 'base' libraries used for almost every other puppet module on the forge.

It would be wise to use a library manager that would be run before booting chaosbot to install this kind of libraries. IMHO, 700+ files for the intended outcome is just too much.

@healiha  ok. working this commit to do just that...

@pchauncey @healiha @rudehn
better now?

Looks good to me with the last commit. I would just squash the last commit to keep a clean history.

and now squashed

@FooBarQuaxx @pchauncey @edgebal @ECrownofFire @fouxarn @skeltoac
What are you current concerns w/ this PR?
I'd like to address them if possible and make this PR better...
Is it that you don't think chaosbot should have nginx as a proxy?

With the libraries out, I don't see any problem with it.

@g19fanatic After the change i'm happy!

Could maybe be improved in a later stage with https://github.com/voxpupuli/librarian-puppet!

I'm in favor of using Nginx in combination with Python, but for other languages, like Go, I think it would be better to just use Go.
Here's my attempt at a pros&cons list for this pull request:
Pros:

Nginx is fast and stable.
Nginx is probably more secure (but also has more people actively looking for vulnerabilities).
Nginx has been tested a lot out in "the real world".
Python as a language does not scale that well when the codebase grows too large, so having functionality in external dependencies that are well maintained is an advantage.

Cons:

Why introduce Nginx, when it's possible to do the exact same things in Python? (Allthough slower, possibly more insecure and with a long way to go in terms of testing)
Adding another component increases the complexity of the codebase. For newcomers, it's yet another thing to know about, configure and learn.
If Nginx should ever depend on something that conflicts with another dependency of chaosbot, that would be problematic. (It's unrealistic for this specific case, but if there should ever be many dependencies, adding more dependencies to chaosbot would increase the chances of this happening).
Fixing a problem in a dependency can be much harder than fixing a problem in your own codebase.

Enemy #1 of the codebases I have seen has been problems with managing increased complexity, either in terms of unstructured code or in terms of dependencies.

Nginx has already been set up by the server owner. Might as well use it


added appropriate social media icons and linked them

I have changed the code for the social media icons section in footer and the i have changed/added appropriate social media handles as suggested

I have added LinkedIn,github, portfolio website and Instagram respectively
please review the changes that I have done and give suggestions if any
thank you for giving me this opportunity to work upon this project

[x] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[x] I have updated the documentation accordingly.

@nagamukesh great work , don't forget to give a 🌟


Loading, please wait...

I now used login via google and after allow I have white window: Loading, please wait...
how fix? thanks.

Oh now have error:
Error: connect ECONNREFUSED <IP_ADDRESS>:8000
at Object.exports._errnoException (util.js:949:11)
at exports._exceptionWithHostPort (util.js:972:20)
at TCPConnectWrap.afterConnect [as oncomplete] (net.js:1080:14)


CVE-2020-8565 for k8s.io/client-go v0.17.17

vulnerability scanner report CVE-2020-8565 on NPD for k8s.io v0.17.17
any plan to update this module?

client-go is bumped to 1.28.1

@yoliangyoliang can we close this issue?


make blast door StrongMetallic

Could probably get upstreamed? I know we have different structural damage stuff but should be wanted there also. I'll have Almond look at it after this gets merged.
:cl: Rane

fix: Blast doors have been made stronger.

Blast doors are specifically designed to contain explosions though, aren't they?

Making the blast door StrongMetallic on SS14 while all the walls are Metallic would introduce an inconsistency. Walls are StrongMetallic here, among other differences such as minimumDamageToDamage.

We can see what they think. Blast doors were to my recollection, in most SS13 servers, made for toxins (the explosive testing rooms)

I upstreamed this here


Add info to README.md on how to download Spice dataset?

@pavankum and @dotsdl have provided some information on how to retrieve the Spice dataset from QCPortal---perhaps we could toss those in the README.md until we get the HDF5 files generated and uploaded to the MolSSI ML dashboard or Zenodo?

This is now provided in the data downloader script.


Remove shortName before ABI retrieval

What it solves
Resolves #3148
How this PR fixes it
QR codes containing EIP-3770 formatted addresses are parsed and the shortName is removed from the contract address, to use the address.
How to test it

Upload the following (Rinkeby-based) QR code in the "Contract Interaction" modal and expect the contract ABI to be loaded successfully.

Contract Interaction input is using the same input as the Send Funds modal. Since Send Funds works correctly, we should look into what is missing.

Tested, works correctly now. ✅
With a rin prefix on Rinkeby:

With a matic prefix on Rinkeby:

It works fine. It can be merged into the RC as well

Done, @francovenica 👍


update README

It should be .rb script, should it not?

Rubocop has failed. But it seems not to be my fault, does it?

Hey @ivanovaleksey, thanks for the pull request! This is just an example of how you can use the dotenv command to run other scripts with the loaded environment, even if they're not in ruby.

Hi, Brandon.
I have known about this gem just a week ago.
And I found it extremely useful in plain old ruby projects.
I have no idea that it can be used even with no ruby projects.
It makes dotenv even more awesome!
Thank you!
-----Original Message-----
From: "Brandon Keepers"<EMAIL_ADDRESS>Sent: 6/6/2016 20:25
To: "bkeepers/dotenv"<EMAIL_ADDRESS>Cc: "Aleksey Ivanov"<EMAIL_ADDRESS>"Mention"<EMAIL_ADDRESS>Subject: Re: [bkeepers/dotenv] update README (#253)
Hey @ivanovaleksey, thanks for the pull request! This is just an example of how you can use the dotenv command to run other scripts with the loaded environment, even if they're not in ruby.
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Catch failures; Fix simulation mode tests

This will do the following:

Failures when building with the bat script will now be caught by Jenkins as failures
In simulation mode, there are samples that should be skipped. See items appended to SAMPLES_LIST under the IF statement with OE_SIMULATION in https://github.com/openenclave/openenclave/blob/master/samples/test-samples.cmake#L54
In simulation mode, samples should use target simulate instead of run when available.

Signed-off-by: Chris Yan<EMAIL_ADDRESS>

/lgtm

/lgtm

/merge


Ternary operator with assignment on the same line as the declaration doesn't work

https://deck.net/050e112eb605a610b7abfe75841978ad
Apparently that's actually valid C# code:
http://rextester.com/MMWV49398
Don't make this task Premium.

Running like a charm now! Fixed with the issue this duplicates and will make it to the next Bridge release! (see attached version milestone).


Discount Code/No Code issues

OK
Trying to push this product group discount to its limits.
So I set up a Cyber Monday Pump sale, selling our pumps for 10% off (this one applies when matching restrictions on Product Groups) and we are running a floats sale 25% off (this one is when a valid code is used on Product Groups). So I add 1 of each product to the cart and it immediately takes to 10% of the pump, like it should. But then if I add the 25% off floats code, it then takes the 25% off the pumps group too.
There are not any Products in Both Groups.  All Floats are separate from all Pump.

Found this issue. Try updating to the latest master, or applying the changes to the two files in this commit:
https://github.com/concrete5-community-store/community_store/commit/46fc53fdf19992c9ba4dd7e5b78c0a33fd28d289

Perfect fix!