Need support for delay between steps

For some operations to complete before checking for a value in the response, a delay is required between the execution of 2 steps in a scenario.
Example: Waiting for 3 minutes to check the status of a job (goes to SUCCESS or FAILURE which needs to be asserted)

It's very easy.
Just execute a java function for how much delay you need in which unit. e.g. in secs, or minutes or milliseconds etc.
e.g.
public class Delay {

    public void minutes(int min) throws InterruptedException {
        Thread.sleep(min*60*1000);
    }

    // But you can add your own flavoured delay function if you want
    // and just call the same function as below
}

The step looks like below calling the above delay-

Gives us 5 seconds delay.

        {
            "name": "delay_in_seconds",
            "url": "org.jsmart.utils.Delay", //<---- Put your class name basically
            "operation": "seconds", //<--- function name
            "request": 5,  //<--- function parameter
            "assertions": {
            }
        }

That's it, done.

You see or verify the result like below in your console as well as log file.
--------- TEST-STEP-CORRELATION-ID: 1f1ddf49-ad13-41e3-a90e-b55d18a7320c ---------
*requestTimeStamp:2019-03-21T07:06:08.317
step:delay_seconds
url:org.jsmart.utils.Delay
method:seconds
request:
5
--------- TEST-STEP-CORRELATION-ID: 1f1ddf49-ad13-41e3-a90e-b55d18a7320c ---------
Response:
null
*responseTimeStamp:2019-03-21T07:06:13.322
*Response delay:5005.0 milli-secs
---------> Assertion: <----------
{ }
-done-

Let's verify as matter of evidence we got 5 second delay or not.
Observe in the pretty print step as below.
*requestTimeStamp:2019-03-21T07:06:08.317
*responseTimeStamp:2019-03-21T07:06:13.322
*Response delay:5005.0 milli-secs <------- We got it. Happy days !

Now to get 3mins delay, you can do this way
       {
            "name": "delay_minutes",
            "url": "org.jsmart.utils.Delay",
            "operation": "minutes",  <----- calling the minutes function now.
            "request": 3,
            "assertions": {
            }
        }

Thanks a lot!

@authorjapps  details helpful.
It would be nice if we have this delay support as part of framework so consumer don't have to create a class.  yeah?

This doesn't work for kafka tests : ( It would be great to add the same think for event tests

This doesn't work for kafka tests : ( It would be great to add the same think for event tests


360 Degree Collision Prevention

Hey PX4 Team!
I was wondering if there's any plug-and-play options for using multi-directional distance sensors. I found this multi-directional distance sensor that uses 4/8 TeraRanger Evo 60m (PX4 Compatible Range Finders) https://www.terabee.com/shop/lidar-tof-multi-directional-arrays/teraranger-tower-evo/ and was hoping to use this to perform 360 degrees collision prevention
If this isn't an option, I was wondering if multiple sensors could be plugged into a companion computer running https://github.com/PX4/avoidance ? Or if we could configure multiple sensors without using the PX4/avoidance repo, since all we really need is Collision Prevention and not Obstacle Avoidance?
I am confused on how the companion computer is supposed to send OBSTACLE_DISTANCE messages for multiple sensors to PX4, and if PX4 is able to interpret these messages. Is PX4 able to get sensor data from 4 cameras facing N,E,S,W and merge that data to perform collision prevention for all sides?

@KarlEaves

I am confused on how the companion computer is supposed to send OBSTACLE_DISTANCE messages for multiple sensors to PX4, and if PX4 is able to interpret these messages. Is PX4 able to get sensor data from 4 cameras facing N,E,S,W and merge that data to perform collision prevention for all sides?

The answer to this part is here: http://docs.px4.io/master/en/computer_vision/collision_prevention.html#algorithm
Essentially the message needs to map the data from sensors around the vehicle into 36 sectors.
There is no plug'n'play solution for plugging such a sensor into the flight stack - wouldn't it be nice if the sensor had a mavlink interface that produced the data as we require :-). the plug'n'play solution currently only supports one sensor in one direction (as per link above).
Yes it should be possible for a collision prevention system to do away with PX4/avoidance and have a simplified mechanism for producing the OBSTACLE_DISTANCE on a companion, but I don't know of such work.
FYI @jkflying

@hamishwillee  Thanks for the info!  I will try creating the program on the companion to send OBSTACLE_DISTANCE data. I am currently running v1.8, but it appears this also supports collision prevention from a companion.
Thank you for the help!


Mis-spelled argument name

tw_crps_for_ensemble takes an argument called chainging_func_kwargs
I think this should be chaining_func_kwargs

Please do an audit of related functions to make sure all the typos have been caught

Fixed by #780


Running llama-2-13b resulted in Killed

System Info
This is my run.py code:

    import torch
    import transformers
    import requests
    print(torch.cuda.is_available())
    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
    # Load model and adapter weights from local directory
    model = transformers.AutoModelForCausalLM.from_pretrained("/home/maxloo/src/pastoring/llama/llama-2-13b")
    model.to(device)
    adapter = transformers.AutoModelForCausalLM.from_pretrained("/home/maxloo/src/pastoring/adapter", config=transformers.configuration.AdapterConfig.from_json_file("adapter_config.json"))
    model.load_state_dict(adapter.state_dict())
    adapter.load_state_dict(model.state_dict())
    # Define prompt
    prompt = "Hello, I am a chatbot."
    # Perform inference
    response = model.generate(prompt, max_length=50)
    # Print response
    print(response)

This is my adapter_config.json code:

    {
      "base_model_name_or_path": "../llama/llama-2-13b/",
      "bias": "none",
      "enable_lora": null,
      "fan_in_fan_out": false,
      "inference_mode": true,
      "init_lora_weights": true,
      "lora_alpha": 16,
      "lora_dropout": 0.05,
      "merge_weights": false,
      "modules_to_save": null,
      "peft_type": "LORA",
      "r": 16,
      "target_modules": [
        "q_proj",
        "k_proj",
        "v_proj",
        "o_proj"
      ],
      "task_type": "CAUSAL_LM",
      "task": "question_answering",
      "domain": "general"
    }

These are my hardware specs:

    Intel Core i7-13700HX, NVIDIA RTX 4060, 32GB DDR5, 1TB SSD

I'm using Windows 11 WSL2 Bash to run this command:

    python3 run.py

I have set my .wslconfig file as follows:

    [wsl2]
    memory=24GB
    processors=24

I expect a chat message to be displayed and a prompt for my chat input, but this is the actual output:

    Killed

How do I resolve this?  Should I be testing llama-13b first before llama-2-13b?

Who can help?
@echarlaix,
@philschmid
Information

[ ] The official example scripts
[X] My own modified scripts

Tasks

[ ] An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
[X] My own task or dataset (give details below)

Reproduction (minimal, reproducible, runnable)
python3 run.py

Expected behavior
I expect a chat message to be displayed and a prompt for my chat input, but this is the actual output:
Killed

How do I resolve this?  Should I be testing llama-13b first before llama-2-13b?

Hi @maxloosmu, your script seem not to use Optimum, I suggest you to open an issue in Transformers repository instead.
Things you could try:

load your model in fp16 (torch_dtype=torch.float16)
Use quantization in int8 or int4 (bitsandbytes, GPTQ, etc.) to lower down the weights memory requirements
Offload weights to RAM with accelerate (very slow)


Power-Density Spectra and Radial Average

Fixes #224
I've retaken the ideas of the closed #227 and #230.
This time I've written two new functions in gravmag.transform: a simple one that calculates the Power-Density Spectra (PDS) of regular gridded data and the other one radially averages this PDS (or any real 2D-array in the wavenumber domain).
As discussed in #230, this new functions has the following characteristics:

The power_density_spectra() function makes use of the _fftfreq() function.
The inputs for the radial_average() function are the wavenumbers array (kx and ky) and the pds (or any wavenumber-domain array). The outputs of the power_density_spectra() function are suitable to use as inputs of this one.
The are no restrictions of squared x, y grids or equally spaced.
All the calculations are made with the kx and ky distances instead of using indexes.
The code is more numpy-ish, making the calculation even faster.
It allows to optionally change the rings' width (making the averages more or less populated) and changing the radius of the biggest ring (in order to leave highest wavenumbers out of the averaging, or in case that our ky, ky grid isn't square to introduce those points that are left outside by default).

Now the schematic draw looks like this:

I leave an example with its outputs:
import numpy as np
import matplotlib.pyplot as plt
from fatiando.datasets import fetch_bouguer_alps_egm
from fatiando.gridder import load_surfer
from fatiando.gravmag import transform

# Fetch Alps Bouguer Anomaly Data
fetch_bouguer_alps_egm(fname="alps-bouguer.grd")
x, y, bg, shape = load_surfer("alps-bouguer.grd")

plt.contourf(y.reshape(shape), x.reshape(shape), bg.reshape(shape), 150)
plt.axes().set_aspect('equal')
plt.title("Bouguer Anomaly of the Alps Region")
plt.colorbar()
plt.savefig("bouguer.png")
plt.show()

# Calculate the Power Density Spectra
kx, ky, pds = transform.power_density_spectra(x, y, bg, shape)

plt.contourf(ky.reshape(shape), kx.reshape(shape), np.log(pds.reshape(shape)),
             150)
plt.axes().set_aspect('equal')
plt.title("Power Density Spectra of the Bouguer Anomaly")
plt.colorbar()
plt.savefig("pds.png")
plt.show()

# Radially Average the Power Density Spectra
default_width = max(kx[1, 0], ky[0, 1])
default_radius = min(kx.max(), ky.max())

# Default
k_radial, pds_radial = transform.radial_average(kx, ky, pds)
plt.plot(k_radial, np.log(pds_radial), 'o-')
plt.title("Radially Averaged PDS")
plt.savefig("default.png")
plt.show()

# Wider Rings
k_radial, pds_radial = transform.radial_average(kx, ky, pds,
                                                ring_width=4*default_width)

plt.plot(k_radial, np.log(pds_radial), 'o-')
plt.title("Radially Averaged PDS (wider rings)")
plt.savefig("wider_rings.png")
plt.show()

# Bigger Max Radius
k_radial, pds_radial = transform.radial_average(kx, ky, pds,
                                                max_radius=0.5*default_radius)

plt.plot(k_radial, np.log(pds_radial), 'o-')
plt.title("Radially Averaged PDS (max radius reduced to half)")
plt.savefig("max_radius.png")
plt.show()

Checklist:

[ ] Make tests for new code (at least 80% coverage)
[ ] Create/update docstrings
[ ] Include relevant equations and citations in docstrings
[ ] Docstrings follow the style conventions
[ ] Code follows PEP8 style conventions
[ ] Code and docs have been spellchecked
[ ] Include new dependencies in doc/install.rst, requirements.txt, environment.yml, ci/requirements-conda.txt and ci/requirements-pip.txt.
[ ] Documentation builds properly (run cd doc; make locally)
[ ] Changelog entry (leave for last to avoid conflicts)
[ ] Firt-time contributor? Add yourself to doc/contributors.rst (leave for last to avoid conflicts)

@santis19 thank you for opening this again!
I've taken a quick look at the code and it's very nice and clean! There isn't much to add to the code. I'll leave some comments inline with some suggestions to improve the interface and docstrings. Great job!
A nice thing about the separation is that we can now test the radial_average function on simpler input. I'd suggest testing by creating some data that is made up of rings of integers. Then, if we specify the correct ring_width, we should get the actual integer values as output.
Another test could then be to create a data array that is the distance from the center of the grid. The radial average should be the distance returned to us.
These two test cases should cover most of the code and usage of this function.
I'm having a harder time thinking how we could test the power_density_spectra function. Maybe we could test it on a sin or cos oscillating in one dimension only? Then go and test it on the other dimension? The tests should also check is kx and ky are reasonable. This kind of thing is much harder to test (when you don't really know the output).
Sidetrack
Another point I'm considering is if it would be better to make a sane_fft2d function instead of a power spectra function (or maybe both). The sane_fft2d function would calculate the FFT and return it and the wavenumber arrays.  It should also pad the data using the gridder padding functions by @drandykass (optionally), since this is done in most FFT applications anyway.  We can offer the power spectra function function as well that takes the space-domain data and uses the sane_fft2d function,  much like tga does for the derivatives.
I like this approach better because it gets rid of repeated code in the transform module and would help people develop other functions for FFT processing. But this should be kept for another PR :smile: I'll open an issue for this so that we can keep track.
End sidetrack
For this PR, I think you should focus now on implementing the tests discussed above. They should go in the fatiando/gravmag/tests/test_transform.py file.
Let me know if you need help with these. I recently updated the reduction to the pole tests and the tilt tests are brand new so you should use those as inspiration.

@mtb-za and @drandykass would you care to weight in on this as well?

I've just finished the radial_average tests: one with integers and another one with distances (as @leouieda proposed).
I have a problem with the last one: the first ring (not the one related to k=0, but the next one) has more than 0.1 relative error. I think that may be related to the fact that this ring is the least populated, so the values are not so randomly spread in the ring. But for the rest of the array the test doesn't fail.
I leave the codes here. I don't know if I should start another PR for this test or just push the edited test_transform.py into my branch...please give this github newbie a hand! haha
from __future__ import division
import numpy as np
import numpy.testing as npt
from fatiando.gravmag import transform
from fatiando import gridder

def test_radial_average_distances():
    shape = (101, 101)
    area = (-100, 100, -100, 100)
    x, y = gridder.regular(area, shape)
    x, y = x.reshape(shape), y.reshape(shape)
    x, y = np.fft.ifftshift(x), np.fft.ifftshift(y)
    distances = np.sqrt(x**2 + y**2)
    k, radial_distances = transform.radial_average(x, y, distances)
    npt.assert_allclose(k, radial_distances, rtol=0.1)  # this fails
    npt.assert_allclose(k[2:], radial_distances[2:], rtol=0.1)  # this doesn't

def test_radial_average_integers():
    x = np.arange(-10, 11, 1)
    y = np.arange(-10, 11, 1)
    y, x = np.meshgrid(y, x)
    x, y = np.fft.ifftshift(x), np.fft.ifftshift(y)
    r = np.sqrt(x**2 + y**2)
    z = np.zeros(x.shape)
    integers = np.arange(0, x.max() + 1, 1)
    for i in integers:
        if i == 0:
            inside = r <= 0.5
        else:
            inside = np.logical_and(r > i - 0.5, r <= i + 0.5)
        z[inside] = i
    k, radial_z = transform.radial_average(x, y, z)
    npt.assert_allclose(integers, radial_z, rtol=0.1)

I've edited the description of the radial_average function following @leouieda suggestions.

@santis19 you can push the test here as well. A PR will only be merged when tests are implemented and passing, that's a way to guarantee that all new code works properly. You'll notice that one of the reasons why "All checks have failed" is that the code test coverage decreased (meaning that you added untested code). Just avoid pushing things that do have anything to do with these two functions (typo fixes elsewhere, bugs in other functions, etc). Those should be submitted as separate PRs.

Once you push the tests to this branch we can take a look at the TravisCI output and I'll comment on the code.

Great work on the tests by the way!

I've just pushed a few more commits: the tests have been added and I've renamed the radial_average function to radial_average_spectrum as @leouieda proposed. Now all checks have passed!

@santis19 perfect! Sorry for the delay, I was away on vacation :beach_umbrella:
I've sent you a pull request to add the changelog entry. You can merge that and add yourself to doc/contributors.rst and we're done! Let me know as soon as you do this and I'll merge this right away.
Thank you so much for taking the time to implement this! I'm working on ways of making the PR processes faster and less of a burden.

@santis19 great work! I'm merging this now. Sorry it took so long. I'm rethinking the contribution process to try to make things faster.
Thanks for putting time into this!


create from string

but need to settle on format:

json like a: "xyz", b: "123", escaping for quote: a: "xyz is \"ABC\"", b: "123\\a"
simplified a=xyz, b=123 (pro: simpler/readability, con: will not support commas and = or will need escaping) - a=xy\=z, b=123\,56, c=\\

need a real life case. gravitating to "simplified"

implemented in #6 - simplified version without escaping (most simplified :)


Global Container Lifecycle

We are looking at refactoring a ton of legacy integration tests to use Docker containers as the database to test against. Currently, many of these old tests expect the database they run against to be permanent between tests,  and unfortunately, not all tests are in the same class (or we would be able to simply use a class rule).
While long term we aim to decouple these tests, short term we are looking for a way to say "Fire this Docker container up once per total run of jUnit/mvn test (and clean up once)". Is this at all possible with Testcontainers, and if not, is it a functionality that may be implemented in the future ?

@Gaibhne if the database is SQL, you may want to use the JDBC URL support with the daemon flag set:
https://www.testcontainers.org/modules/databases/#running-container-in-daemon-mode
For other types of containers, we recommend the singleton container approach:
https://www.testcontainers.org/test_framework_integration/manual_lifecycle_control/#singleton-containers

Thanks, I did not come across that during my Google research. It seems a combination of the two would solve our problems and allow us to slowly untangle our tests one by one.


fix(search): return EmptyState/Progress bar/Alert depending on result of api call

Hey, I just made a Pull Request!
Fixes #3342

On Search Result page, depending on the result of the api call display different component.
When loading, Progress component is shown

When call to api fails with an error, Alert component is shown

When call is finished with empty result, EmptyState component is shown

:heavy_check_mark: Checklist

[ ] A changeset describing the change and affected packages. (more info)
[ ] Added or updated documentation
[ ] Tests for new functionality and regression tests for bug fixes
[x] Screenshots attached (for UI changes)

@magneticz LGTM, will merge when the checks pass! Thank you so much for the contribution 🎉 💯


Param pulsar_manager.admin.user/pulsar_manager.admin.password used in the wrong place

Describe the bug
I am try to set pulsar_manager.admin.user/pulsar_manager.admin.password for login pulsar-manager ui, But it's actually used as the account/password for outside PostgreSQL instance.
To Reproduce
helm upgrade --install pulsar charts/pulsar --set pulsar_manager.admin.user=pulsarpulsar --set pulsar_manager.admin.password=pulsarpulsar  -n pulsar
org.postgresql.util.PSQLException: FATAL: role "pulsarpulsar" does not exist
	at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2440) ~[postgresql-42.2.5.jar:42.2.5]
	at org.postgresql.core.v3.QueryExecutorImpl.readStartupMessages(QueryExecutorImpl.java:2559) ~[postgresql-42.2.5.jar:42.2.5]
	at org.postgresql.core.v3.QueryExecutorImpl.<init>(QueryExecutorImpl.java:133) ~[postgresql-42.2.5.jar:42.2.5]
	at org.postgresql.core.v3.ConnectionFactoryImpl.openConnectionImpl(ConnectionFactoryImpl.java:250) ~[postgresql-42.2.5.jar:42.2.5]
	at org.postgresql.core.ConnectionFactory.openConnection(ConnectionFactory.java:49) ~[postgresql-42.2.5.jar:42.2.5]
	at org.postgresql.jdbc.PgConnection.<init>(PgConnection.java:195) ~[postgresql-42.2.5.jar:42.2.5]
	at org.postgresql.Driver.makeConnection(Driver.java:454) ~[postgresql-42.2.5.jar:42.2.5]

@tabalt I think the current pulsar-manager version doesn't support changing the login user and password very well. We are releasing pulsar-manager v0.2.0. It will support setting user and password.

/cc @tuteng

I notice v0.2.0 of pulsar-manager was released, and I tried it a couple of weeks ago. I don't think it supports this yet. The issue appears to be tracked here: https://github.com/apache/pulsar-manager/issues/297 . They do mention a workaround (which I haven't tried).

Please review PR #212, it should fix this issue.

Issue should be resolved by #457


[Feature Request]: Add function calling capability to LiteLLM

Feature Description
LiteLLM is a wrapper over LLMs from non-OpenAI providers to harmonize their APIs to OpenAI's APIs. This ensures harmonization and ease of LLM switchability.
Most LLMs (like Bedrock) have function-calling capabilities, and LiteLLM already handles this on their end. Would it be too difficult to add function-calling capabilities to LlamaIndex's LiteLLM class?
Here's an example of function calling failure once we wrap any LLM into LlamaIndex's LiteLLM class (including OpenAI)
from dotenv import load_dotenv, find_dotenv
from llama_index.llms.litellm import LiteLLM
from llama_index.core.agent import FunctionCallingAgentWorker
from llama_index.core.tools import FunctionTool

_=load_dotenv(find_dotenv()) #load OpenAI API key
llm = LiteLLM(model="gpt-4o-mini")
def add(a: int, b: int) -> int:
    """Returns the sum of 2 integers"""
    return a + b

def multiply(a: int, b: int) -> int:
    """Returns the product of 2 integers"""
    return a * b

add_tool = FunctionTool.from_defaults(fn=add)
multiply_tool = FunctionTool.from_defaults(fn=multiply)
agent_worker = FunctionCallingAgentWorker.from_tools(
    tools = [add_tool, multiply_tool],
    llm = llm,
    verbose = True
)

This throws the error:
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
Cell In[19], line 1
----> 1 agent_worker = FunctionCallingAgentWorker.from_tools(
      2     tools = [add_tool, multiply_tool],
      3     llm = llm,
      4     verbose = True
      5 )

File /opt/anaconda3/envs/llamaindex/lib/python3.12/site-packages/llama_index/core/agent/function_calling/step.py:147, in FunctionCallingAgentWorker.from_tools(cls, tools, tool_retriever, llm, verbose, max_function_calls, allow_parallel_tool_calls, callback_manager, system_prompt, prefix_messages, **kwargs)
    144 tools = tools or []
    146 llm = llm or Settings.llm  # type: ignore
--> 147 assert isinstance(
    148     llm, FunctionCallingLLM
    149 ), "llm must be an instance of FunctionCallingLLM"
    151 if callback_manager is not None:
    152     llm.callback_manager = callback_manager

AssertionError: llm must be an instance of FunctionCallingLLM

Funnily enough LlamaIndex has code to identify that this LLM within LiteLLM is a function calling LLM in lines 160-169 of llama_index/llama
 @property
    def metadata(self) -> LLMMetadata:
        return LLMMetadata(
            context_window=openai_modelname_to_contextsize(self._get_model_name()),
            num_output=self.max_tokens or -1,
            is_chat_model=True,
            is_function_calling_model=is_function_calling_model(self._get_model_name()),
            model_name=self.model,
        )

printing llm.metadata returns:
LLMMetadata(context_window=16384, num_output=-1, is_chat_model=True, is_function_calling_model=True, model_name='gpt-4o-mini', system_role=<MessageRole.SYSTEM: 'system'>)

As we can see, is_function_calling_model = True. But the reason LiteLLM function calling still returns an error is because the LiteLLM class inherits from "LLM" instead of "FunctionCallingLLM". I sense that this is not a trivial fix.
Reason
I could use LiteLLM's library directly but it would be great to use LlamaIndex's capabilities!
Value of Feature
LiteLLM is one of the commonly used libraries to harmonize LLM provider APIs to the OpenAI API, and the library continues to be used despite more libraries being harmonized to OpenAI APIs. LiteLLM continues to update their offerings to remain current across LLM providers.

@tituslhy it would just have to extend the FunctionCallingLLM base class and implement a few extra functions --  I welcome a PR to add this :)

Oops I cheated. I just used LlamaIndex's ReAct workflow cookbook recipe (https://docs.llamaindex.ai/en/stable/examples/workflow/react_agent/) and used LiteLLM as my llm of interest HAHA!
I did experiment a little with inheriting from FunctionCallingLLM but I found this way harder - when I called Gemini from LIteLLM it also had tool calling json errors though it fit LiteLLM's schema perfectly. argh.


Loading error: Error creating SSL context () (99)

What steps will reproduce the problem?
Any search through New Tab or New Tab Pool using danbooru or gelbooru will not return any results. Examples are "rating:safe" and "blonde_hair". Searches using behoimi will crash the program.
What is the expected behavior? What do you get instead?
Instead of regular search results, no images appear and the error "Loading error: Error creating SSL context () (99)" reoccurs in the log. A log file is attached.
main.log
How often does this problem occur? On which sources?
It occurs on every search with the above sources.
What version of the program are you using? On what operating system?
I am using v5.5.1 on Windows 10.
Please provide any additional information below
All settings aside from default location are at default values. I tried updating OpenSSL as detailed in https://github.com/Bionus/imgbrd-grabber/issues/767.
Any help you can provide would be appreciated.

http://slproweb.com/products/Win32OpenSSL.html
Which version did you install from there? 1.1.0 or 1.0.2?
Grabber targets 1.0.2 so using the 1.1.0 might not work.
Also, during the installation, which option did you chose in this screen:

If you chose the Windows directory, you have to delete the 3 DLLs from Grabber installation directory (else they'll have priority). If you chose the /bin directory, you have to replace the ones in the Grabber installation directory by the ones in "C:\OpenSSL-Win32\bin".

You could also try the DLLs from there if the previous don't work:
https://indy.fulgan.com/SSL/

Switching to 1.0.2 and deleting the 3 DLLs in the Grabber folder worked, don't get results from dan/gelbooru but the others are good enough for me. Thanks for the helpful response and this wonderful program, no longer have to save things one by one!

I see. May I ask which version did you use? I guess v1.0.2L Light? Win32 or Win64? (because the one bundled with Grabber is already 1.0.2k, so it's weird that it wouldn't work)

I guess that the problem was that I originally installed 1.1.0 Win32 when I'm running Win64.


Allow aggregates to @React on events

This PR teaches aggregates to react on events using method annotated with @React.
Summary of changes:

@React annotation is introduced, which is used by AggregateRepository for delivering events to aggregates.
external attribute is added to @Subscribe and @React.
id-function interfaces were renamed to Routes
Routing configuration is improved using CommandRouting and EventRouting classes.
Spine version was advanced to 0.9.38-SNAPSHOT.

@armiol, PTAL.

Improvements to be done in a following PR:

checking ”completeness” of the routing schema
reporting wrong output or arguments for annotated methods as IllegalStateException instead of ignoring them in method predicates.

@alexander-yevsyukov I have approved the PR, however some tests failed to pass.


Initialize Typescript

This PR initializes Typescript by turning a page component to tsx file to trigger Next.js 9's automated Typescript setup.

[x] *.tsx in rumors-site can be typechecked correctly
[x] website can build and execute
[ ] CI works
[ ] Can generate type & specific useQuery using codegen
[ ] Can type individual fragments

Note: if you encounter issue regarding "JSX flag" in VS Code, please select Typescript with "workspace version".

Coverage: 76.333% (+0.1%) from 76.235% when pulling d294164abf8f0e482b8c718a7205746365f2284e on typescript into bf0362a6f41dbed8331fafa20bbb1002bf55a029 on master.

It's now ready for review!


CheatSheet Template

Project title
CheatSheet Template
Project Description
-This cheat sheet provides a quick reference guide for [Topic Name]. It includes key concepts, syntax, and examples to help you quickly recall important information related to [Topic Name].
Doc Domain

[] Solidity , Html, Css , JavaScript , Web3.js / Ether.js
[] Solidity , ReactJs /NextJs , Web3.js /Ether.js
[] Solidity , Python3 , Web3.py
[] Other , feel free to mention below

Are you contributing under any open-source program ?
YES SSOC 2.0

Please assign me this @Vikash-8090-Yadav


awake trey icon context menu

Microsoft PowerToys version
0.84.1
Installation method
PowerToys auto-update
Running as admin
Yes
Area(s) with issue?
Awake
Steps to reproduce
No steps but either the Awake context menu or even the Awake icon is
sometimes neither visible nor accessible through the tray icons
✔ Expected Behavior
I see the icon and with click/right-click it
I c context menu stripI
❌ Actual Behavior
either icon missing from Trey or clicks go bogus
Other Software
No response

Hey, so I might have a solution for your issue which you may check.
Troubleshooting steps:

Restart PowerToys - close and reopen for refreshing the system tray icons.
Check taskbar settings - ensure that the taskbar is set to show all the icons. You may right click on the taskbar to go to "Taskbar settings", to check the notification area settings.
Run as admin - for preventing permission related issues.
Temporarily disable any third party software (such as antivirus)

These steps should solve the issue.

/dup https://github.com/microsoft/PowerToys/issues/34148
fixed via https://github.com/microsoft/PowerToys/pull/34717
Will ship in 0.85


Formal jupyter_kernel_mgmt support

https://github.com/takluyver/jupyter_kernel_mgmt/issues/32
The CondaKernelProvider support we added to nb_conda_kernels is unfortunately obsolete, but can be remedied! When jupyter_kernel_mgmt 0.5 is complete, we should work to implement this. This issue will organize the plan.
cc: @kevin-bates @echarles @takluyver

JKM 0.5 is already out :-)

Great!

In taking a brief look and applying various code changes, I'm seeing a number of issues that my python skills don't know how to handle.

Now that providers are no longer in jupyter_client (JC) and jupyter_kernel_mgmt (JKM) doesn't support traitlets, the derivation of CondaKernelSpecManager from KernelSpecManager gets messed up.  JKM's KernelSpecManager has a specific set of parameters, but they aren't mapped to traitlets.  As a result, CondaKernelSpecManager's call to super.__init__ generates an invalid parameter exception - when the base class comes from JKM.

Today, nb_conda_kernels simply looks for the discovery module via import and, if not present (in jupyter_client), derives the CondaKernelProvider from object in order to satisfy loads knowing the find_kernels() and launch() methods won't be called.  Since both JC and JKM can co-exist, how should that be handled?

JKM requires asyncio, which doesn't exist in 2.7 and JKM doesn't currently run on 3.5 (we can change that, but its nearly EOL).  How would conditional requirements be handled?

Given these issues, would it make sense to remove discovery from nb_conda_kernels and, instead, develop a separate package - dependent on nb_conda_kernels (for the conda-speficic code) - that is provider-specific (e.g., nb_conda_provider or nb_conda_kernel_provider)?  I believe this would allow for future changes down the road (e.g., parameterized kernel launch) that would be difficult to make work in a shared module.
Thoughts?
cc: @Zsailer

Today, nb_conda_kernels simply looks for the discovery module via import and, if not present (in jupyter_client), derives the CondaKernelProvider from object in order to satisfy loads knowing the find_kernels() and launch() methods won't be called. Since both JC and JKM can co-exist, how should that be handled?

This is only being done in order to facilitate testing while we didn't have a real opportunity to exercise it.

JKM requires asyncio, which doesn't exist in 2.7 and JKM doesn't currently run on 3.5 (we can change that, but its nearly EOL). How would conditional requirements be handled?

My thought is that jupyter_kernel_manager will be an optional dependency of nb_conda_kernels. If a conditional import of JKM succeeds, it will behave accordingly; otherwise it will fall back to older behavior. This will likely solve issue #1 too.

Thanks for the responses.  I'm realizing that I may have gotten wrapped around the axle a bit.  Since the purpose of providers is to allow custom implementations of BOTH KernelSpecManager and KernelManager, there's nothing that prevents CondaKernelSpecManager from deriving from jupyter_client's KernelSpecManager.
Also, the launch method will return back an instance of KernelManager from jupyter_kernel_mgmt, not jupyter_client, but again, that should be fine.
So installation of nb_conda_kernels will wind up introducing jupyter_client as a dependency that wouldn't be necessary otherwise - but that's no different than some other provider depending on another module.
Any hints on how to solve item 3?  Could py 2.7 be dropped via a new release (2.3 or 3.0)?

I'm not concerned at all about 3. We will be able to support Python 2.7 with less functionality. Remember, if nb_conda_kernels is in Python 2.7 environment, it won't be able to load JKM. So we will fall back to the existing code path, and there will be no undue dependency on asyncio.

ok, I thought the new declarations would generate syntax errors.  I apparently don't understand how/when python "compiles" its code.
discovery.py would look something like this.  Aren't the function decorators (async.coroutine and async) and await still an issue?
try:
    import asyncio
    from jupyter_kernel_mgmt.discovery import KernelProviderBase
    from jupyter_kernel_mgmt.subproc import SubprocessKernelLauncher
except ImportError:
    # Silently fail for version of jupyter_client that do not
    # yet have the discovery module. This allows us to do some
    # simple testing of this code even with jupyter_client<6
    KernelProviderBase = object

from .manager import CondaKernelSpecManager

class CondaKernelProvider(KernelProviderBase):
    id = 'conda'

    def __init__(self):
        self.cksm = CondaKernelSpecManager(conda_only=True)

    @asyncio.coroutine
    def find_kernels(self):
        for name, data in self.cksm.get_all_specs().items():
            yield name, data['spec']

    async def launch(self, name, cwd=None, launch_params=None):
        spec = self.cksm.get_kernel_spec(name)
        return await SubprocessKernelLauncher(
            kernel_cmd=spec.argv, extra_env=spec.env, cwd=cwd, launch_params=launch_params).launch()

Ah, yes, you're write, they would indeed cause errors. We'll have to have separate async and non-async submodules.

@mcg1969 - Your comment implies that there's a different "load pattern" that takes place when a module is in a sub-directory (which is what I assume a 'submodule' is).  If that's the case, then do we need discovery.py at all if the entry_points' stanza in setup.py is updated to simply hit nb_conda_kernels.subproc.provider directly - where CondaKernelProvider is defined?
    entry_points={
        "jupyter_kernel_mgmt.kernel_type_providers": [
            # The name before the '=' should match the id attribute
            'conda = nb_conda_kernels.subproc.provider:CondaKernelProvider',
        ]}

If both an async and a dummy version (dummy because it will never be executed) are necessary, don't we wind up pushing the problem down a level because there's really nothing other than import statements in discovery.py at that point.  Not following the purpose of discovery.py or non-async at this point.
I apologize for being behind here, but we're getting into python idiosyncrasies that I haven't had to really deal with before. :smile: thank you for your patience.

This issue should be close in favor of https://github.com/Anaconda-Platform/nb_conda_kernels/issues/228


Fixing calicoctl manifest for KDD RBAC installs

Description

Fixes #1276
We need to use our service account for the calicoctl manifests to work with RBAC enabled.
I've backported this to v3.0 and v2.6, but it looks to be missing further back as well, if we feel it is beneficial I can add it as far back as we supported RBAC.
Todos

[ ] Tests
[ ] Documentation
[ ] Release note

Release Note

None required

I've updated the manifest for master with RBAC roles and a calicoctl service account. I ran over some basic tests with most resources and it seems to be in order. @gunjan5 @caseydavenport if those rules look right to you two I'll backport them to the v3.0 and v2.6 versions.

Is there a way to retrigger the CLA, I can't merge until it is green.


Suggestion: Alternate design without separate cursors

A common reason to use intrusive data-structures is to be able to look up an element via one data-structure, and then perform some operation on the same element in a different data-structure.
AIUI, this cannot be done safely with this crate, as it requires the unsafe cursor_mut_from_ptr method to be called.
I think a safe interface could be made by having this crate own the allocator that produces elements. For example, a basic allocator could store elements in a Vec<T>, and then use Vec indices as the "pointers" used to identify elements. Safety would be ensured by checking indices against the length of the internal Vec.
This would not prevent logic errors (if you mixed elements from different allocators, you'd get garbage results) but it should all be safe.
An arena allocator could work similarly, but using real pointers and range checks instead.

I think this is probably outside the scope of intrusive-collections and should be done in a separate crate.


Empty dimension check

Motivation and Context
If the input sample is of empty dimension, hangar won't handle it currently and throws an error from the parser. Issue is described in here #47
Description
A auick fix a simple validation whether the shape is saved as empty or not.
Types of changes
What types of changes does your code introduce? Put an x in all the boxes that apply:

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Is this PR ready for review, or a work in progress?

[x] Ready for review
[ ] Work in progress

How Has This Been Tested?
Put an x in the boxes that apply:

[ ] Current tests cover modifications made
[x] New tests have been added to the test suite
[ ] Modifications were made to existing tests to support these changes
[ ] Tests may be needed, but they are not included when the PR was proposed
[ ] I don't know. Help!

Checklist:

[x] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[x] I have read the CONTRIBUTING document.
[x] I have signed (or will sign when prompted) the tensorwork CLA.
[x] I have added tests to cover my changes.
[x] All new and existing tests passed.

after tests are fixed this is good to go!


[IOTDB-3186] Support DeleteStorageGroups API for new cluster

This PR also fixes some incorrect OperateType in exception massage.

Coverage decreased (-0.01%) to 45.699% when pulling 58d5a2f3eb1f03a3b14a219f63c8eba240155245 on deleteStorageGroups into 3857fab2b13f0af282032b8f28cc2035c3f50a27 on master.


System Voltage and Current

v4.4.6 - Voltage and Current

Add data points for system current and voltages (solar, home, grid and powerwall).
Includes continuous queries and dashboard.json update.
Currently only viable for local mode, non-PW3, systems. Cloud mode and TEDAPI-only (PW3) setups do not include this data (still under investigation).

See https://github.com/jasonacox/Powerwall-Dashboard/discussions/109#discussioncomment-10103516

Renamed "Powerwall Vitals" section to "System Vitals" to more accurately describe the metrics.

Tested with jasonacox/pypowerwall:0.10.9t63

I only installed it a few minutes ago, so maybe the data will normalize later, but this is what I see for the last 30 minutes:

It's showing -37 amps of powerwall @ about 250 volts, or  9.2 KW. that doesn't match the power flow which shows I'm pulling about 1.7 KW from my powerwall right now. I have 3x powerwalls... does that matter?
It's showing about 15 amps of grid at about 215 volts. I'm not using any grid right now.
Solar volts * amps is about double the solar showing in the power flow animation.
Home volts * amps seems to match the power flow animation.
Am I reading this wrong?

Thanks @youzer-name - Yes it is wrong. I'm not sure why. Here is the data we are using:
SELECT load_instant_total_current AS home, solar_instant_total_current AS solar, battery_instant_total_current AS pw, site_instant_total_current AS grid

It pulls that data directly from the Powerall API (/api/meters/aggregates) - You can check, http://localhost:8675/aggregates and see if it aligns to what you see in the graph.
I suspect a negative value on Powerwall means that power is flowing out of the Powerwall but it doesn't match what we would expect to see (like 4x off). Like you, I noticed that the "grid" data which comes in as "site_instant_total_current" also doesn't match the power flow. And yes, same with solar, but home seems to be right. Odd! Since we use this API for power metrics (wattage) I assumed the current would align. However, now I wonder what these "instant_total_current" values really mean. The voltages may also be off as well.
Anyone have any ideas?


option to force languages to be live by default

Adding the live suffix to every code section that one wants to make live is not fun.
It would be preferable if all vue example could all turn live.

The best would probably be a white-list of languages


compare performance to cchardet

currently the readme compares performance
only to chardet, but not to cchardet
same for bin/performance.py
performance-sensitive users prefer cchardet
so the comparison to chardet is misleading
charset_normalizer says:
charset_normalizer is 20x faster than chardet
rs_chardet says:
cchardet is 40x faster than rs_chardet
cchardet is 4000x faster than chardet
→ cchardet is 200x faster than charset_normalizer
https://github.com/jawah/charset_normalizer/issues/182#issue-1221074881 says:
cchardet is 5x faster than charset_normalizer
anyway, both are useful:
cchardet works better on small inputs
charset_normalizer works better on large inputs (#486)
cchardet:
https://github.com/PyYoshi/cChardet
https://github.com/faust-streaming/cChardet

rs_chardet says:
cchardet is 40x faster than rs_chardet
cchardet is 4000x faster than chardet
→ cchardet is 200x faster than charset_normalizer

It does not seems right. Either the project do wrong or I missed something. chardetng is really much faster than what is presented. It is simply not possible. (chardet 	v5.1.0 	0.20407073211428026; rs_chardet 	v0.1.1 	25.446704726774133)
They use a single (file) sample to measure performances[...] We have 400+ samples. (And I consider it to be the absolute minimum).

cchardet works better on small inputs
charset_normalizer works better on large inputs

That seems like an over simplification of what is said. Sometime cchardet fail on small input and sometime charset-normalizer succeed where cchardet fail.

performance-sensitive users prefer cchardet
so the comparison to chardet is misleading

Where did I say something "misleading"? When charset-normalizer came, it was to propose an alternative to Chardet that was dominant at the time. Comparing pure C++ with Python isn't helping too. We already mention cchardet anyway for transparency.
Moreover, you can exponentially improve perf by simply disabling the support for 60 extra encodings, it will go a lot faster.
If you wanted to truly compare, apple-to-apple. I don't think anyone realize how they would perform with our 99 encodings support. It WILL be catastrophic.

cchardet:
https://github.com/PyYoshi/cChardet
https://github.com/faust-streaming/cChardet

To my eyes, they are both unmaintained. The first is long dead, the second gave up.
Regards,


Round values in format_forecast()

The Euro hub has updated to accept only integer values - see here.
This PR updates format_forecast() so that the formatted saved forecasts have integer values.
I think this PR should do the trick for the epiforecasts euro hub submission, but I haven't spent much time with this repo or know where else these forecasts are being used - so please check.

Thanks, Kath! That is really nice of you.
This is only the EpiNow2 stuff, but I'll update the crowd forecasts as well

🦸🏻♀


doesn't capture my callback

same as title doesn't capture my callback.don't why
 import 'package:flutter/cupertino.dart';
import 'package:flutter/material.dart';
import 'package:flutter_web_auth/flutter_web_auth.dart';
import 'package:flutter_web_auth_2/flutter_web_auth_2.dart';
import 'dart:convert' show jsonDecode;
import 'package:http/http.dart' as http;
// App specific variables
final googleClientId = 'client';
final callbackUrlScheme = 'com.example.ui://callback';
// Construct the url
final url = Uri.https('bungie.com', '/en/oauth/authorize', {
'client_id': googleClientId,
'response_type': 'code',
});
// Present the dialog to the user
Future<String?> getGoogleAuthCode() async {
final result = await FlutterWebAuth2.authenticate(
url: url.toString(),
callbackUrlScheme: callbackUrlScheme,
);
// Extract the code from the response URL
//String casteo = getGoogleAuthCode().toString();
//final result = await FlutterWebAuth2.authenticate(url: url.toString(), callbackUrlScheme: callbackUrlScheme);
// Extract code from resulting url
final result1 = Uri.parse(result).queryParameters['code'];
print(result) {
// TODO: implement print
throw UnimplementedError();
}
var headers = {
'Content-Type': 'application/x-www-form-urlencoded',
'code': '$result1',
};
var request = http.Request(
'POST', Uri.parse('https://www.bungie.net/platform/app/oauth/token'));
request.headers.addAll(headers);
http.StreamedResponse response = await request.send();
if (response.statusCode == 200) {
print(await response.stream.bytesToString());
} else {
print(response.reasonPhrase);
}
// Extract the access token from the response
//final data = jsonDecode(response.body);
// Use the access token to access the Google API
// Do something with the data
}
void main() {
runApp(miercoles());
}
class miercoles extends StatelessWidget {
@override
Widget build(BuildContext context) {
return MaterialApp(
home: Scaffold(
appBar: AppBar(
title: Text('Google Sign In'),
),
body: Center(
child: ElevatedButton(
child: Text('Sign in with Google'),
onPressed: () async {
// Get the auth code
          getGoogleAuthCode();
        },
      ),
    ),
  ),
);

}
}
my android manifest
<activity            android:name="com.linusu.flutter_web_auth.CallbackActivity"            android:exported="true"             tools:ignore="MissingClass">            <intent-filter android:label="flutter_web_auth_2">                <action android:name="android.intent.action.VIEW" />                <category android:name="android.intent.category.DEFAULT" />                <category android:name="android.intent.category.BROWSABLE" />                 <data android:scheme="com.example.ui://callback" />            </intent-filter>          </activity>

import 'package:flutter_web_auth/flutter_web_auth.dart';

It seems like you have flutter_web_auth and flutter_web_auth_2 installed simultaneously.
Could you please try removing flutter_web_auth?

ok

still happen

The webpage is showing the URL as com.example.ui:/?code=...
However, the callback scheme you provided is com.example.ui://callback.
Please change this in your Android Manifest to com.example.ui and in your dart file to final callbackUrlScheme = 'com.example.ui';

Also, the backend on web should redirect to com.example.ui://?code=... instead.
Please note the DOUBLE-slash (not one as seen in your screenshot above)

https://github.com/oshju/webauthmiercoles.git no works

You have not applied the changes I suggested. Your Android Manifest is still faulty and the dart code has also not been modified.
Also, your web application does need the suggested change as well.

i tried with one slash and 2 slash

As already said, this line should say <data android:scheme='com.example.ui' />
and this line should say final callbackUrlScheme = 'com.example.ui';.
Google OAuth should redirect to com.example.ui://?code=... instead.
After these changes, everything will work fine, as already stated. Please take a look at the example for each package for the future before creating issues.


Add interceptor to retrofit client

Since TMDB api has two ways to authenticate the clients and this project is using api_key method, present code is using @Query to add the key in every api request which leads to redundant code. It is better to have an interceptor to handle adding the api_key as query param to each request.

I have solved this issue


⚠ Bofrost.lu has degraded performance

In 41d9353, Bofrost.lu (https://www.bofrost.lu) experienced degraded performance:

HTTP code: 200
Response time: 1804 ms

Resolved: Bofrost.lu performance has improved in e6871e3 after 39 minutes.


Cant skip CASClient::Frameworks::Rails::Filter

I have before_filter CASClient::Frameworks::Rails::Filter in my application controller and can't skip it in my an ajax call in another controller using skip_before_filter CASClient::Frameworks::Rails::Filter.

Am using rails3.2.19, skip_before_filter CASClient::Frameworks::Rails::Filter and skip_filter CASClient::Frameworks::Rails::Filter not working


Subscribing to Integer type

If subscribe just action, I think to create entity is not a better idea, can launch Integer type such as :
int SHARE_SUCCESS = 0x101;
EventBus.getDefault().post(SHARE_SUCCESS);

Yes, you can post and subscribe to any object, so it can also be Integer or String. However, typically it is better to have specific event classes to differentiate between events.
-ut

No response. Closing. -ut


python310Packages.aws-lambda-builders: disable failing tests

Description of changes
Fix build (https://hydra.nixos.org/build/178360549)

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/)
22.05 Release Notes (or backporting 21.11 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.

Result of nixpkgs-review pr 175301 run on x86_64-linux 1

3 packages built:

aws-sam-cli
python310Packages.aws-lambda-builders
python39Packages.aws-lambda-builders


WIP: Feature/coyoneda

Hi @gcanti
This a pr request still in progress about coyoneda, I resolved the coyoneda problem using regular javascript. But I need some guidance from you in order to do it properly on your lib. The main problem is how to create the Partial type in order to keep the composed functions to next step. Anyway I will keep trying to do it.
Regards

@josete89 ok but first of all, is there a practical use case for Coyoneda?

Thanks @gcanti , Basically the main purpose of Coyoneda is convert any type into a functor. Also the key thing in coyoneda is the maps are a composition of the one before this means you apply several maps in one iteration, which is more performant. ( You can look into the test ) -> https://typelevel.org/cats/api/cats/free/Coyoneda.html

Yes that's the theoretical purpose, but what would be a practical application in fp-ts?
Keep in mind that fp-ts/lib/Free doesn't require a Functor instance (because AFAIK it already comprises Coyoneda).

That's true, but the thing is Coyoneda is more simple than create free monads if you only want to have the map method, which is quite handy.

Right, but who would even use Coyoneda for that since you can just manually compose the mappings:

Also true the benefit that I see is you are deferring the execution.

@josete89 I'd say such things make quite an impression on me because I'm no mathematician :) However I'd love to know how to use such theory on practice, could you show some useful examples?

@raveclassic Imagine the following program:
// Business logic

const bigArray = Array(100000)
const coyo = Coyoneda.lift(bigArray).map(expensiveOperation)

// View (Side effects)

if(something){
 show(coyo.lower())
} else {
 showError()
}
```
Delays the execution until the functor is needed.

Closing due to inactivity


Intellisense not working in .fs files

When I create an .fs file there is no intellisence or error underlining. When I create a .fsx file all features seem to work correctly.

Please enable debugging as described in readme and post detailed log from F# Language Service and F# Language Service (server) output tabs

Rerpoduction steps:

Create a new file with the .fs extension
Intellisense does not work
Create a new file with the .fsx extension
Intellisense does work

Log for when opening a .fs file:
[Extension Host] [IONIDE-FSAC] REQ (017) -> {parse}, File = "~\Model.fs"
Data=Object
[Extension Host] last output: [object Map]
[Extension Host] [IONIDE-FSAC] REQ (018) -> {lint}, File = "~\Model.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (018) <- {lint} in 5 ms: Kind={"info"}
Data=Cached typecheck results not yet available
[Extension Host] [IONIDE-FSAC] RES (017) <- {parse} in 32 ms: Kind={"info"}
Data=Parse aborted
[Extension Host] [IONIDE-FSAC] REQ (019) -> {declarations}, File = "~\Model.fs"
Data=Object

Having the same problem here.
.fsx file debug output:
[22:15:23 INFO ] REQ (257) -> {parse}, File = "c:\test.fsx" Data={"FileName":"c:\\test.fsx","IsAsync":true,"Lines":[""],"Version":1} [22:15:23 INFO ] REQ (258) -> {lint}, File = "c:\test.fsx" Data={"FileName":"c:\\test.fsx"} [22:15:23 INFO ] RES (258) <- {lint} in 36 ms: Kind={"lint"}  [22:15:23 INFO ] RES (257) <- {parse} in 99 ms: Kind={"errors"}  [22:15:23 INFO ] REQ (259) -> {declarations}, File = "c:\test.fsx" Data={"FileName":"c:\\test.fsx","Version":1} [22:15:23 INFO ] RES (259) <- {declarations} in 4 ms: Kind={"declarations"}
.fs file output:
[22:16:00 INFO ] REQ (268) -> {parse}, File = "c:\test2.fs" Data={"FileName":"c:\\test2.fs","IsAsync":true,"Lines":[""],"Version":1} [22:16:00 INFO ] REQ (269) -> {lint}, File = "c:\test2.fs" Data={"FileName":"c:\\test2.fs"} [22:16:00 INFO ] RES (269) <- {lint} in 3 ms: Kind={"info"}  [22:16:00 INFO ] RES (268) <- {parse} in 33 ms: Kind={"info"}  [22:16:01 INFO ] REQ (270) -> {declarations}, File = "c:\test2.fs" Data={"FileName":"c:\\test2.fs","Version":1}

vscode 1.10.0
ionide 2.23.5
The tooltip when hovering over the .fsx works (see the last line), as does the help/autocomplete popup when typing. Neither the help nor the popups work on the .fs
Is there any additional debugging that would help? Don't mind putting some breakpoints in the developer console or whatever and grabbing some live values.
test.fs
module Test
    let a = 1

test.fs.log
[Extension Host] [IONIDE-FSAC] REQ (001) -> {parse}, File = "~\test.fs"
Data=Object
[Extension Host] [msbuild] MSBuild found at C:\Program Files (x86)\\MSBuild\14.0\Bin\MSBuild.exe
[Extension Host] [msbuild] MSBuild activated
[Extension Host] [IONIDE-FSAC] RES (001) <- {parse} in 1699 ms: Kind={"info"}
Data=Parse aborted
[Extension Host] [IONIDE-FSAC] REQ (002) -> {parseProjects}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (002) <- {parseProjects} in 54 ms: Kind={"errors"}
Data=Object
[Extension Host] [IONIDE-FSAC] REQ (003) -> {lint}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (003) <- {lint} in 20 ms: Kind={"info"}
Data=Cached typecheck results not yet available
[Extension Host] [IONIDE-FSAC] REQ (004) -> {completion}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (004) <- {completion} ERROR in 19 ms: {SyntaxError: Unexpected token u in JSON at position 0}, Data=%O
[Extension Host] [IONIDE-FSAC] REQ (005) -> {tooltip}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (005) <- {tooltip} in 37 ms: Kind={"error"}
Data=Position is out of range
[Extension Host] [IONIDE-FSAC] REQ (006) -> {completion}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (006) <- {completion} ERROR in 11 ms: {SyntaxError: Unexpected token u in JSON at position 0}, Data=%O
[Extension Host] [IONIDE-FSAC] REQ (007) -> {tooltip}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (007) <- {tooltip} in 16 ms: Kind={"error"}
Data=Position is out of range
[Extension Host] [IONIDE-FSAC] REQ (008) -> {tooltip}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (008) <- {tooltip} in 24 ms: Kind={"error"}
Data=Position is out of range
[Extension Host] [IONIDE-FSAC] REQ (009) -> {parse}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] REQ (010) -> {lint}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (010) <- {lint} in 16 ms: Kind={"info"}
Data=Cached typecheck results not yet available
[Extension Host] [IONIDE-FSAC] RES (009) <- {parse} in 68 ms: Kind={"info"}
Data=Parse aborted
[Extension Host] [IONIDE-FSAC] REQ (011) -> {tooltip}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (011) <- {tooltip} in 8 ms: Kind={"error"}
Data=Position is out of range
[Extension Host] [IONIDE-FSAC] REQ (012) -> {completion}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (012) <- {completion} ERROR in 8 ms: {SyntaxError: Unexpected token u in JSON at position 0}, Data=%O
[Extension Host] [IONIDE-FSAC] REQ (013) -> {completion}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (013) <- {completion} ERROR in 8 ms: {SyntaxError: Unexpected token u in JSON at position 0}, Data=%O
[Extension Host] [IONIDE-FSAC] REQ (014) -> {tooltip}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (014) <- {tooltip} in 29 ms: Kind={"error"}
Data=Position is out of range
[Extension Host] [IONIDE-FSAC] REQ (015) -> {tooltip}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (015) <- {tooltip} in 14 ms: Kind={"error"}
Data=Position is out of range
[Extension Host] [IONIDE-FSAC] REQ (016) -> {parse}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] REQ (017) -> {lint}, File = "~\test.fs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (017) <- {lint} in 25 ms: Kind={"info"}
Data=Cached typecheck results not yet available
[Extension Host] [IONIDE-FSAC] RES (016) <- {parse} in 41 ms: Kind={"info"}
Data=Parse aborted

test.fsx
let a = 1

test.fsx.log
[Extension Host] [IONIDE-FSAC] REQ (043) -> {parse}, File = "~\test.fsx"
Data=Object
[Extension Host] last output: [object Map]
[Extension Host] [IONIDE-FSAC] REQ (044) -> {lint}, File = "~\test.fsx"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (044) <- {lint} in 24 ms: Kind={"lint"}
Data=Array[0]
[Extension Host] [IONIDE-FSAC] RES (043) <- {parse} in 303 ms: Kind={"errors"}
Data=Object
[Extension Host] [IONIDE-FSAC] REQ (045) -> {completion}, File = "~\test.fsx"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (045) <- {completion} in 87 ms: Kind={"completion"}
Data=Array[163]
[Extension Host] [IONIDE-FSAC] REQ (046) -> {helptext}, Symbol = "let"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (046) <- {helptext} in 4 ms: Kind={"error"}
Data=No help text available for symbol 'let'
[Extension Host] [IONIDE-FSAC] REQ (047) -> {helptext}, Symbol = "let"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (047) <- {helptext} in 8 ms: Kind={"error"}
Data=No help text available for symbol 'let'
[Extension Host] [IONIDE-FSAC] REQ (048) -> {completion}, File = "~\test.fsx"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (048) <- {completion} in 133 ms: Kind={"completion"}
Data=Array[198]
[Extension Host] [IONIDE-FSAC] REQ (049) -> {helptext}, Symbol = "abs"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (049) <- {helptext} in 4 ms: Kind={"helptext"}
Data=Object
[Extension Host] [IONIDE-FSAC] REQ (050) -> {tooltip}, File = "~\test.fsx"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (050) <- {tooltip} in 12 ms: Kind={"error"}
Data=Position is out of range
[Extension Host] [IONIDE-FSAC] REQ (051) -> {parse}, File = "~\test.fsx"
Data=Object
[Extension Host] [IONIDE-FSAC] REQ (052) -> {lint}, File = "~\test.fsx"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (052) <- {lint} in 37 ms: Kind={"lint"}
Data=Array[0]
[Extension Host] [IONIDE-FSAC] RES (051) <- {parse} in 152 ms: Kind={"errors"}
Data=Object
[Extension Host] [IONIDE-FSAC] REQ (053) -> {tooltip}, File = "~\test.fsx"
Data=Object
[Extension Host] [IONIDE-FSAC] RES (053) <- {tooltip} in 10 ms: Kind={"tooltip"}
Data=Array[1]

I can also reproduce the issue. I used the tour.fs file from https://github.com/dotnet/docs/blob/master/samples/snippets/fsharp/tour.fs
See the attached debug logs for each file.
tour.fsx.txt
tour.fs.txt

I've reproduced this on two Windows 10 computers. VS Code 1.10.2, ionide-fsharp 2.23.9.
Did not reproduce on Ubuntu 16.04. VS Code 1.8.1, ionide-fsharp 2.23.9.
Here are the logs from a Windows machine:
F# Language Service (server):
Resolving startup promise because FSAC printed the 'listener started' message
[I] 2017-03-14T18:37:42.7678820Z: listener started in 201.086 ms with binding <IP_ADDRESS>:8423 [Suave.Tcp.tcpIpServer]

F# Language Service:
[14:37:42 INFO ] REQ (001) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":["let exchange p1 p2 =\r","    let tmp = !p1\r","    p1 := !p2\r","    p2 := tmp\r","\r","l"],"Version":1}
[14:37:46 DEBUG] RES (001) <- {parse} in 3782 ms: Kind={"info"}
Data="Parse aborted"
[14:37:46 INFO ] REQ (002) -> {parseProjects}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:37:46 DEBUG] RES (002) <- {parseProjects} in 178 ms: Kind={"errors"}
Data={"File":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Errors":[{"FileName":"startup","StartLine":1,"EndLine":1,"StartColumn":1,"EndColumn":1,"Severity":"Error","Message":"internal error: BuildFrameworkTcImports: no resolution of 'FSharp.Core, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a'","Subcategory":"typecheck"},{"FileName":"startup","StartLine":1,"EndLine":1,"StartColumn":1,"EndColumn":1,"Severity":"Error","Message":"Could not resolve this reference. Could not locate the assembly \"FSharp.Core, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a\". Check to make sure the assembly exists on disk. If this reference is required by your code, you may get compilation errors. (Code=MSB3245)","Subcategory":"parameter"},{"FileName":"startup","StartLine":1,"EndLine":1,"StartColumn":1,"EndColumn":1,"Severity":"Error","Message":"internal error: BuildFrameworkTcImports: no resolution of 'FSharp.Core, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a'","Subcategory":"typecheck"},{"FileName":"startup","StartLine":1,"EndLine":1,"StartColumn":1,"EndColumn":1,"Severity":"Error","Message":"Could not resolve this reference. Could not locate the assembly \"FSharp.Core, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a\". Check to make sure the assembly exists on disk. If this reference is required by your code, you may get compilation errors. (Code=MSB3245)","Subcategory":"parameter"}]}
[14:37:46 INFO ] REQ (003) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:37:46 DEBUG] RES (003) <- {lint} in 50 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:47 INFO ] REQ (004) -> {declarations}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Version":1}
[14:37:47 INFO ] REQ (005) -> {symboluse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Line":6,"Column":2,"Filter":""}
[14:37:47 DEBUG] RES (005) <- {symboluse} in 25 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:47 INFO ] REQ (006) -> {tooltip}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Line":6,"Column":2,"Filter":""}
[14:37:47 DEBUG] RES (006) <- {tooltip} in 16 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:49 INFO ] REQ (007) -> {tooltip}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Line":6,"Column":1,"Filter":""}
[14:37:49 DEBUG] RES (007) <- {tooltip} in 17 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:50 INFO ] REQ (008) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":["let exchange p1 p2 =\r","    let tmp = !p1\r","    p1 := !p2\r","    p2 := tmp\r","\r",""],"Version":2}
[14:37:50 INFO ] REQ (009) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:37:50 DEBUG] RES (009) <- {lint} in 42 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:50 DEBUG] RES (008) <- {parse} in 81 ms: Kind={"info"}
Data="Parse aborted"
[14:37:55 INFO ] REQ (010) -> {tooltip}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Line":4,"Column":14,"Filter":""}
[14:37:56 DEBUG] RES (010) <- {tooltip} in 66 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:56 INFO ] REQ (011) -> {tooltip}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Line":5,"Column":5,"Filter":""}
[14:37:56 DEBUG] RES (011) <- {tooltip} in 62 ms: Kind={"error"}
Data="Position is out of range"
[14:37:57 INFO ] REQ (012) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":["let exchange p1 p2 =\r","    let tmp = !p1\r","    p1 := !p2\r","    p2 := tmp\r","    "],"Version":8}
[14:37:57 INFO ] REQ (013) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:37:57 DEBUG] RES (013) <- {lint} in 41 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:57 DEBUG] RES (012) <- {parse} in 88 ms: Kind={"info"}
Data="Parse aborted"
[14:37:58 INFO ] REQ (014) -> {tooltip}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Line":4,"Column":14,"Filter":""}
[14:37:58 DEBUG] RES (014) <- {tooltip} in 15 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:58 INFO ] REQ (015) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":["let exchange p1 p2 =\r","    let tmp = !p1\r","    p1 := !p2\r","    p2 := tmp"],"Version":11}
[14:37:58 INFO ] REQ (016) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:37:58 DEBUG] RES (016) <- {lint} in 47 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:37:58 DEBUG] RES (015) <- {parse} in 87 ms: Kind={"info"}
Data="Parse aborted"
[14:37:59 INFO ] REQ (017) -> {tooltip}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","Line":1,"Column":1,"Filter":""}
[14:37:59 DEBUG] RES (017) <- {tooltip} in 62 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:38:00 INFO ] REQ (018) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:38:00 INFO ] REQ (019) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:38:00 DEBUG] RES (019) <- {lint} in 19 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:38:00 DEBUG] RES (018) <- {parse} in 76 ms: Kind={"info"}
Data="Parse aborted"
[14:38:13 INFO ] REQ (020) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:38:13 INFO ] REQ (021) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:38:13 DEBUG] RES (021) <- {lint} in 14 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:38:13 DEBUG] RES (020) <- {parse} in 78 ms: Kind={"info"}
Data="Parse aborted"
[14:38:19 INFO ] REQ (022) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:38:19 INFO ] REQ (023) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:38:19 DEBUG] RES (023) <- {lint} in 41 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:38:19 DEBUG] RES (022) <- {parse} in 86 ms: Kind={"info"}
Data="Parse aborted"
[14:38:22 INFO ] REQ (024) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:38:22 INFO ] REQ (025) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:38:22 DEBUG] RES (025) <- {lint} in 17 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:38:22 DEBUG] RES (024) <- {parse} in 46 ms: Kind={"info"}
Data="Parse aborted"
[14:38:41 INFO ] REQ (026) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:38:41 INFO ] REQ (027) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:38:41 DEBUG] RES (027) <- {lint} in 50 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:38:41 DEBUG] RES (026) <- {parse} in 225 ms: Kind={"info"}
Data="Parse aborted"
[14:40:01 INFO ] REQ (028) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:40:01 INFO ] REQ (029) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:40:01 DEBUG] RES (029) <- {lint} in 54 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:40:01 DEBUG] RES (028) <- {parse} in 100 ms: Kind={"info"}
Data="Parse aborted"
[14:40:17 INFO ] REQ (030) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:40:17 INFO ] REQ (031) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:40:17 DEBUG] RES (031) <- {lint} in 17 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:40:17 DEBUG] RES (030) <- {parse} in 74 ms: Kind={"info"}
Data="Parse aborted"
[14:41:13 INFO ] REQ (032) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:41:13 INFO ] REQ (033) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:41:13 DEBUG] RES (033) <- {lint} in 16 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:41:13 DEBUG] RES (032) <- {parse} in 43 ms: Kind={"info"}
Data="Parse aborted"
[14:41:16 INFO ] REQ (034) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:41:16 INFO ] REQ (035) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:41:16 DEBUG] RES (035) <- {lint} in 100 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:41:17 DEBUG] RES (034) <- {parse} in 171 ms: Kind={"info"}
Data="Parse aborted"
[14:41:29 INFO ] REQ (036) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:41:29 INFO ] REQ (037) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:41:29 DEBUG] RES (037) <- {lint} in 79 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:41:29 DEBUG] RES (036) <- {parse} in 98 ms: Kind={"info"}
Data="Parse aborted"
[14:41:30 INFO ] REQ (038) -> {parse}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs","IsAsync":true,"Lines":[""],"Version":14}
[14:41:30 INFO ] REQ (039) -> {lint}, File = "c:\Users\Carl\OneDrive\Desktop\test.fs"
Data={"FileName":"c:\\Users\\Carl\\OneDrive\\Desktop\\test.fs"}
[14:41:30 DEBUG] RES (039) <- {lint} in 47 ms: Kind={"info"}
Data="Cached typecheck results not yet available"
[14:41:30 DEBUG] RES (038) <- {parse} in 73 ms: Kind={"info"}
Data="Parse aborted"

@Krzysztof-Cieslak: Do you know if this affects all Windows 10 machines?

Creating a new project from the CLI and opening that now works for me (followed https://twitter.com/enricosada/status/843569801448570881).
Looked at the .fsproj and it had some differences from the one I was using, so I amended mine to match and my project now has intellisense and error squigglies, etc.
👍

Should be fixed in 2.25.7

Syntax highlighting and intellisense don't work in .fs files for me. .fsx files are okay though.

Idem, same message as OP.
I've just done "Reload window" on VS Code and lost al intellisense for 10 mins now.
[Error - 11:06:02 PM] Request textDocument/hover failed.
  Message: Cached typecheck results not yet available
  Code: -32603
[Error - 11:06:24 PM] Request textDocument/hover failed.
  Message: Cached typecheck results not yet available
  Code: -32603
[Error - 11:06:25 PM] Request textDocument/definition failed.
  Message: Cached typecheck results not yet available
  Code: -32603
[Error - 11:06:25 PM] Request textDocument/hover failed.
  Message: Cached typecheck results not yet available
  Code: -32603

It seems that you could try "Select Language Mode" in VS Code, probably ".fs" is associated with other files, e.g. GLSL file like in my VS code which caused the intellisense unable to work, that should be OK

I have something similar. I cannot to use intellisense but syntax highlighting is fine. It pertains only to .fs files. There is a yellow message on status bar below: "Not in a F# project (still loading)" and VSC error on click: "Running the contributed command: 'fsharp.AddFileToProject' failed". I managed with it by installing "F# language support" extension which is deprecated by itself (added to F#), I think.

I am also experiencing this issue. I am on VSCode version 1.81.1 on Ubuntu 22.04 and .NET sdk 7.0.306.


In Proxy setup, helm install pod won't start if I use stable/traefik for chart

Version - v0.3.0
To Reproduce

Setup proxy server
Put k3 on machine behind server
edit /var/lib/rancher/k3s/server/manifests/traefik.yaml and change chart to point at stable/traefik

Results: helm-install-traefik- pod keeps restarting and the job never completes

Expected behavior
Should restart and job should complete

@galal-hussein Investigate how to pass the proxy variables to helm install job from the helm controller

Version - v0.5.0-rc3
Verified fixed

Version - 0.5.0-rc2
This is still broken
Error for pod in logs:
[storage/driver] 2019/05/02 21:16:43 list: failed to list: Get https://<IP_ADDRESS>:443/api/v1/namespaces/kube-system/secrets?labelSelector=OWNER%3DTILLER: Unable to connect
Error: Get https://<IP_ADDRESS>:443/api/v1/namespaces/kube-system/secrets?labelSelector=OWNER%!D(MISSING)TILLER: Unable to connect

This should be fixed in 0.5.0-rc4

Version - v0.5.0-rc4
Verified fixed.


Expo EAS build android apk crash on physical device

Build/Submit details page URL
No response
Summary
I am new to expo , I build an app with expo and when i try to run with npx expo run:android   it was working fine on emulator ,
but when i generate a debug and preview build apk with eas App crash after showing splash screen.
I am attaching my package.json file
{
"name": "deltacard",
"version": "2",
"main": "node_modules/expo/AppEntry.js",
"scripts": {
"start": "expo start",
"android": "expo run:android",
"ios": "expo run:ios",
"web": "expo start --web"
},
"dependencies": {
"@react-native-async-storage/async-storage": "1.18.2",
"@react-native-community/masked-view": "^0.1.11",
"@react-navigation/bottom-tabs": "^5.11.15",
"@react-navigation/native": "^5.9.8",
"@react-navigation/stack": "^5.14.9",
"apisauce": "^3.0.1",
"eas": "^0.1.0",
"expo": "~49.0.8",
"expo-app-loading": "^2.1.1",
"expo-auth-session": "~5.0.2",
"expo-barcode-scanner": "~12.5.3",
"expo-camera": "~13.4.2",
"expo-constants": "~14.4.2",
"expo-image": "~1.3.2",
"expo-image-picker": "~14.3.2",
"expo-linking": "~5.0.2",
"expo-random": "~13.2.0",
"expo-secure-store": "~12.3.1",
"expo-splash-screen": "~0.20.5",
"expo-status-bar": "~1.6.0",
"expo-updates": "~0.18.12",
"expo-web-browser": "~12.3.2",
"formik": "^2.1.4",
"moment": "^2.29.4",
"react": "18.2.0",
"react-native": "0.72.3",
"react-native-google-places-autocomplete": "^2.5.1",
"react-native-reanimated": "~3.3.0",
"react-native-safe-area-context": "4.6.3",
"react-native-screens": "~3.22.0",
"yup": "^1.2.0"
},
"resolutions": {
"@expo/config-plugins": "~6.0.0",
"@expo/prebuild-config": "~6.0.0",
"@babel/core": "^7.20.2",
"babel-loader": "8.3.0"
},
"packagerOpts": {
"sourceExts": [
"js",
"json",
"ts",
"tsx",
"jsx",
"vue"
]
},
"private": true,
"devDependencies": {
"sharp-cli": "^4.1.1"
}
}
I saw this on stackoverflow to fix , that realted to    "react-native-reanimated": "~3.3.0",
but when i downgrade this , i got this as an error and asked me to upgrade
Managed or bare?
Bare
Environment
expo-env-info 1.0.5 environment info:
System:
OS: Windows 10 10.0.22621
Binaries:
Node: 18.17.1 - C:\Program Files\nodejs\node.EXE
npm: 10.0.0 - C:\Program Files\nodejs\npm.CMD
IDEs:
Android Studio: AI-223.8836.35.2231.10671973
npmPackages:
expo: ~49.0.8 => 49.0.9
react: 18.2.0 => 18.2.0
react-native: 0.72.3 => 0.72.3
Expo Workflow: bare
**Doctor check**

✔ Check Expo config for common issues

✔ Check package.json for common issues
✔ Check dependencies for packages that should not be installed directly
✔ Check for common project setup issues
✔ Check npm/ yarn versions
✔ Check Expo config (app.json/ app.config.js) schema
✔ Check that native modules do not use incompatible support packages
✔ Check for legacy global CLI installed locally
✖ Check that packages match versions required by installed Expo SDK
✖ Check that native modules use compatible support package versions for installed Expo SDK
Detailed check results:
Expected package<EMAIL_ADDRESS>Found invalid:
<EMAIL_ADDRESS>(for more info, run: npm why @expo/config-plugins)
Expected package<EMAIL_ADDRESS>Found invalid:
<EMAIL_ADDRESS>(for more info, run: npm why @expo/prebuild-config)
Advice: Upgrade dependencies that are using the invalid package versions.
Some dependencies are incompatible with the installed expo version:
<EMAIL_ADDRESS>- expected version: 0.72.4
Your project may not work correctly until you install the correct versions of the packages.
Fix with: npx expo install --fix
Found outdated dependencies
Advice: Use 'npx expo install --check' to review and upgrade your dependencies.
Error output
No response
Reproducible demo or steps to reproduce from a blank project
NA

Hi, do you have expo-updates configured correctly in the same way as recommended in these docs? https://docs.expo.dev/versions/latest/sdk/updates/
https://docs.expo.dev/bare/installing-updates/

@szdziedzic We have a very similar issue (after using expo-update) but on iOS following the details for the link you sent and launching on the physical device whist having iOS logs running i can see the following error when it crashed

Does that mean anything to do you? We are on SDK 49 which pretty much same setup as poster


Document features

First of all thanks for that really useful trait. I just could not get it working with latest aws sdk dynamodb version 0.10.1.
Error:
the trait bound `aws_sdk_dynamodb::model::AttributeValue: serde_dynamo::AttributeValue` is not satisfied
the trait `serde_dynamo::AttributeValue` is not implemented for `aws_sdk_dynamodb::model::AttributeValue`

when calling
let rows: Vec<LeaseTableRow> = from_items(items)?;

while items is of type items: Vec<HashMap<String, AttributeValue>>
Edit: Downgrading to 0.10.0 gives me the same error.
Edit 2: Changing my dependency to serde_dynamo = { version = "3.0.3", features = ["full"] } fixed the issue. Wasn't aware of that as there was no hint in the README.

This is documented at https://docs.rs/serde_dynamo/latest/serde_dynamo/#features and at https://docs.rs/serde_dynamo/latest/serde_dynamo/#aws-sdk-support.
You mention it’s not on the README. You were looking at the GitHub page on the readme for this information, and not on docs.rs? If there was a link from the README to the features section on docs.rs, would that have helped?

If there was a link from the README to the features section on docs.rs, would that have helped?

Yes.
It would also have helped to enrich the example with a hint to the necessary feature. I assumed I don't need anything else beside the base dependency.

OK. Would you be willing to submit a PR with what you think would have helped you get up to speed faster?
Yeah, I’d love for serde_dynamo to just work without any features required, but unfortunately that’s not feasible at this point.

A features section has been added to the README.


README does not reflect breaking change in format configuration introduced in 8.1.0

#324 introduced a breaking change without documentation. The format configuration described in the README's Kotlin DSL example should now include a .toString() invocation as in:
dependencyCheck {
    format = org.owasp.dependencycheck.reporting.ReportGenerator.Format.ALL.toString()
}

A downside of the approach taken: We lose type safety for the format value.

We accept PRs.
Yes, we lose type safety - but users can create custom templates to output in whatever format they choose.


Implementation of 'Distinct' command

http://docs.mongodb.org/manual/reference/method/db.collection.distinct/

Hi, thanks for your contribution. It will be reviewed soon.

Please squash the commit into a single one for the final review. Thanks

@cchantep Done

Thanks @viktortnk


Broken test runner when narrowing tests

When running jake runtests with the option t= there is maximum call stack error.
$ jake runtests t=amdImportAsPrim
rm -rf tests/baselines/local/
rm -rf internal/baselines/rwc/local
Running test(s): amdImportAsPrim
mocha -R dot -g amdImportAsPrim --colors  -t 20000 built/local/run.js

  ․․․․․․

  5 passing (159ms)
  1 failing

  1) compiler tests for tests/cases/conformance/externalModules/amdImportAsPrimaryExpression.ts "after all" hook:
     Uncaught RangeError: Maximum call stack size exceeded

The above is from the current master with an arbitrary test file.
node -v
v0.12.2

I think @RyanCavanaugh might have mentioned something about this in passing.

@ahejlsberg was actually the one running into this. We debugged through it and found the harness was actually in a different test than what it was reporting when failing (if you look at the after hook in the harness it's just not doing anything that could stack overflow). It ended up being in a suspicious sounding test given Anders changes' and I didn't hear about the final resolution which I assumed meant things were back to normal (ie working). Apparently we need to investigate further.

This bug was fixed and released in Mocha recently.

thanks @tinganho

@tinganho out of curiousity, what was the mocha issue?

@danquirk there was a recursive loop that traversed all the tests in Mocha. But when we passed a grep option that recursive loop was recursing without a next tick on the event loop, which caused the maximum call stack error.
Here was the commit:
https://github.com/mochajs/mocha/commit/1a68cc2f102dcf73dc53515aed9112360632b1b4


IRGen: Fix handling of empty fields in Clang-imported types.

Clang allows C structs to have zero-sized array fields for things like trailing buffers. Lower these correctly into Swift types in IRGen so that Swift codegen knows to treat them as empty types. Fixes rdar://problem/31042794.

@swift-ci Please smoke test


Fix build error when api-version=6.0 and arch=x86

The IoT-Headed 6.0 SDK doesn't have a rootstrap for emulator. Use the mobile 6.0 rootstrap instead.
$ flutter-tizen build tpk --debug --target-arch x86 -p common

target: tizen_cpp_embedding
exception:Error: The rootstrap iot-headed-6.0-emulator.core could not be found.
To install missing package(s), run:
/home/swift/tizen-studio/package-manager/package-manager-cli.bin install IOT-Headed-6.0-NativeAppDevelopment-CLI
#0      throwToolExit (package:flutter_tools/src/base/common.dart:10:3)
#1      TizenSdk.getRootstrap (package:flutter_tizen/tizen_sdk.dart:320:7)
#2      NativeEmbedding.build (package:flutter_tizen/build_targets/embedding.dart:103:43)
#3      _BuildInstance._invokeInternal (package:flutter_tools/src/build_system/build_system.dart:861:27)
<asynchronous suspension>
#4      Future.wait.<anonymous closure> (dart:async/future.dart:518:21)

$ /home/swift/tizen-studio/package-manager/package-manager-cli.bin install IOT-Headed-6.0-NativeAppDevelopment-CLI
Package Manager (0.5.54)

****************************************
******* Start to update packages *******
****************************************
Nothing to update.

****************************************
****** Start to install packages *******
****************************************
Nothing to install.

@swift-kim 6.0 does not have a tizen-headed emulator, so there is no rootstrap.
As far as I know, building 6.0, there are no scenarios where common is set in --profile-name.
It seems like it's normal for the build to fail, but shouldn't more error handling be added?

@JSUYA Tried https://github.com/flutter-tizen/flutter-tizen/issues/552? Create a project from the default template, run on a Tizen 8.0 emulator (or build tpk -pcommon), and the build will immediately fail.


[Bug]: Explicitly setting llm property to None is overridden in core settings

Bug Description
I am trying to write my own document ingestion pipeline using the llamaindex core and IngestionPipeline framework. My use case calls for using a local llm only which I am doing via Ollama and the OllamaEmbedding class. It works. However, other transformer classes seem to be always attempting to use OpenAI as a default regardless of what is set in the base class "llm" property.
        try:
            transformations = [
                SentenceSplitter(chunk_size=512, chunk_overlap=20),
                TitleExtractor(llm=None),
                OllamaEmbedding(llm="llama2")
            ]
            pipeline = IngestionPipeline(transformations=transformations)
            return pipeline
        except Exception as e:
            self.logger.error("Error in my pipeline: %s", str(e))
            raise

So in the above definition, setting llm=None has no effect and ultimately gets reset to default regardless of setting llm.
I've traced this via through metadata_extractors.py and the super class properties of TitleExtractor and discovered this code in settings.py:

    @property
    def llm(self) -> LLM:
        """Get the LLM."""
        if self._llm is None:
            self._llm = resolve_llm("default")

        if self._callback_manager is not None:
            self._llm.callback_manager = self._callback_manager

        return self._llm

So it appears that no matter when None is set, the value always goes back to default, which is the Open AI LLM hard coded and which will throw an error since no OPENAI_API_KEY has been set.
This doesn't appear to me to be expected nor intended behavior.
Version
0.10.26
Steps to Reproduce
Using the above sample ingestion pipeline definition provided, set  TitleExtractor(llm=None), in the pipeline, do not set an OPENAI_API_KEY either inline or in the environment and call the pipeline,
Relevant Logs/Tracbacks
Here is my error trace:

20240403 16:30:26 - Error in pipeline:
******
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.
******
20240403 16:30:26 - Error ingesting document:
******

Change the defaults in the global settings, or specifically pass in the LLM and embed model to your modules (anything that uses an LLM or embed model  accepts it in the interface)

The title extractor needs an LLM, you can't set it to none

For example, you can do
from llama_index.llms.Ollama import Ollama

llm = Ollama(model="llama2", request_timeout=3000.0)

# set the default LLM in settings
from llama_index.core import Settings
Settings.llm = llm

# or pass in the LLM to the extractor
TitleExtractor(llm=llm)

The title extractor needs an LLM, you can't set it to none

@logan-markewich thank you for the quick reply. Of course it does lol.... Was unclear to me in the docs, but seeing your comments now makes it obvious. Thanks again

Happy to help!


added isSameMonthOf and isSameYearOf

added isSameMonthOf and isSameYearOf, cheers

Just merged. Thank you :)
I'm thinking to merge all these comparing methods in a single call.
Could be something:
let isSameYear = date.compare("year",anotherDate)

What do you think?

Not unreasonable. I would do like so:
let isSameYear = date.isSame(TIME_ENUM.Year, anotherDate)
then the shorthand would read let isSameYear = date.isSame(.Year, anotherDate)
likewise: date.isAfter(.Year, anotherDate) & date.isBefore(.Year, anotherDate)
Cheers

Well, right, enum is a more robust solution of course.
Anyway I think you can obtain the same result using date.year == anotherDate.year so I'm really torn about it. Could be more useful when grouping multiple components to compare in a single call.

True.  Would be useful when checking a date is after the current date down to hour/min/sec granularity.
Example: 2015-05-05 9 AM > 2015-05-04 10AM, but date05.hour > date04.hour would return false
but date05.isAfter(.Hour, date04) would return true while ignore minutes and seconds.


Allow non-unique hidden steps in TorXakis models

As a user I would like to have maximal specification power.
Hence, I want to be able to specify hidden behaviour which is not unique, e.g. like in #217 where one of two commands can be taken out of the list.
Instead of being limited by TorXakis which currently disallows non-unique hidden steps, I would like to use them as much as possible (i.e., limited by the capabilities of the problem solvers).

Then we must first have a version of the solver to gives ALL solutions;
so, in addition to randSolve, uniSolve we must have  "allSolve"
(which obviously cannot always be done).

I want to use torxakis both a simulator and tester.
However, since torxakis uses sockets I have to include an asynchronous channel in the sut model
This works perfectly as the channel has no value or an unique value, see e.g.
STAUTDEF stautdef [ Stimulus, Response , Event ] () ::=
    STATE init, response
    INIT init
    TRANS

    init -> Stimulus -> response
    response -> Response -> init
    init -> Event -> init
ENDDEF

PROCDEF channel [ EIn, EOut ] () ::=
    EIn >-> EOut >-> channel [EIn, EOut]()
ENDDEF

CHANDEF ChannelDefs ::=
    Stimulus, Response, Event
ENDDEF

MODELDEF Model ::=
	CHAN IN Stimulus
	CHAN OUT Event,Response

	BEHAVIOUR
	stautdef [Stimulus, Response, Event ] ()
ENDDEF

MODELDEF ModelDelay ::=
	CHAN IN Stimulus
	CHAN OUT Event,Response

	BEHAVIOUR
        HIDE [ h ] IN
            channel [h, Event] () |[ h ]| stautdef [Stimulus, Response, h ] ()
        NI
ENDDEF

CNECTDEF Sut
::=
	CLIENTSOCK

	CHAN OUT Stimulus 	HOST "localhost" PORT 7890
	ENCODE Stimulus ->	! "s"

	CHAN IN Event 	HOST "localhost" PORT 7891
	DECODE Event 	<-	? s

	CHAN IN Response 	HOST "localhost" PORT 7890
	DECODE Response 	<-	? s

ENDDEF

CNECTDEF Sim
::=
	SERVERSOCK

	CHAN IN Stimulus 	HOST "localhost" PORT 7890
	DECODE Stimulus <- ? s

	CHAN OUT Event 	HOST "localhost" PORT 7891
	ENCODE Event -> ! "e"

	CHAN OUT Response 	HOST "localhost" PORT 7890
	ENCODE Response -> ! "r"

ENDDEF

However, when the output channel has a value it is no longer allowed.
See Event in the example.