Save embeddings with spatiotemporal metadata to GeoParquet

What I am changing

Storing the vector embeddings alongside some spatial bounding box and datetime information in a tabular GeoParquet format, instead of an npy file!

How I did it

In the LightningModule's predict_step, use geopandas to create a GeoDataFrame with three columns - date, embeddings, geometry. A sample table would look like this:

date
embeddings
geometry

2021-01-01
[0.1, 0.4, ... x768]
POLYGON(...)

2021-06-30
[0.2, 0.5, ... x768]
POLYGON(...)

2021-12-31
[0.3, 0.6, ... x768]
POLYGON(...)

The date is stored in Arrow's date32 format, embeddings are in FixedShapedTensorArray (TODO), and geometry is in WKB.

Each row would store the embedding for a single 256x256 chip, and the entire table could realistically store N rows for an entire MGRS tile (10000x1000) across different dates.

TODO in this PR:

[x] Save embeddings to GeoParquet
[x] Improve docstring

TODO in the future:

[ ] Ensure embeddings are saved as FixedShapeTensorArray? (see https://github.com/Clay-foundation/model/pull/73#discussion_r1419757638)

How you can test it

Locally, download some GeoTIFF data into the data/ folder, and then run:

python trainer.py fit --trainer.max_epochs=10 --trainer.precision=bf16-mixed --data.data_path=data/46REU --data.num_workers=4  # train the model
python trainer.py predict --ckpt_path=checkpoints/last.ckpt --data.batch_size=1024 --trainer.precision=bf16-mixed --data.num_workers=0  # generate embeddings

This should produce an embedding_0.gpq file under the data/embeddings/ folder

Sample file (need to unzip, about 3.0MB uncompressed): embeddings_0.gpq.zip

Extra configuration options can be found using python trainer.py predict --help

To load the embeddings from the geoparquet file:
import geopandas as gpd

geodataframe: gpd.GeoDataFrame = gpd.read_parquet(path="embeddings_0.gpq")
assert geodataframe.shape == (2, 3)
print(geodataframe)

        date	        embeddings	                                        geometry
0	2022-12-12	[-1.1094263, 1.0212796, -0.58915687, -1.144523...	POLYGON ((93.02647 30.71001, 93.02648 30.73311...
1	2022-12-12	[-1.1253564, 1.0260286, -0.5860151, -1.1528502...	POLYGON ((93.34729 30.70955, 93.34738 30.73265...
2	2022-12-12	[-1.1190275, 1.0268829, -0.59865385, -1.147052...	POLYGON ((93.74777 30.63856, 93.74794 30.66166...
3	2022-12-12	[-1.1115837, 1.0286477, -0.60599935, -1.143061...	POLYGON ((93.80119 30.63824, 93.80138 30.66134...
4	2022-12-12	[-1.1172316, 1.0246403, -0.59833527, -1.143900...	POLYGON ((93.82790 30.63808, 93.82810 30.66118...
...	...	...	...
750	2022-12-12	[-1.11294, 1.0265714, -0.6015097, -1.1443343, ...	POLYGON ((93.40048 30.64010, 93.40057 30.66320...
751	2022-12-12	[-1.1207774, 1.029693, -0.5964609, -1.1490294,...	POLYGON ((93.45391 30.63992, 93.45402 30.66302...
752	2022-12-12	[-1.1309807, 1.0274287, -0.57653224, -1.162805...	POLYGON ((93.58748 30.63939, 93.58762 30.66249...
753	2022-12-12	[-1.1268965, 1.0305986, -0.59025705, -1.154876...	POLYGON ((93.61420 30.63926, 93.61434 30.66236...
754	2022-12-12	[-1.1171025, 1.0268872, -0.60177326, -1.146309...	POLYGON ((93.69434 30.63886, 93.69450 30.66196...

755 rows × 3 columns

If you have a newer version of QGIS, it's also possible to load the GeoParquet file directly. The below screenshot shows the bounding box locations of the 755 embeddings (1 embedding for each 256x256 chip):

Related Issues

Extends #56, continuation of #66.

There are a couple of things that can be improved as mentioned above, such as the filenaming scheme, and streamlining how the embeddings are saved to the GeoParquet file, but will merge this in first, and handle those nice-to-haves in follow-up PRs.


please support remove vertex

+1

Absolutely. I‘ll try to add it in the upcoming release.

@liuxiaomeiG @davis-haba RemoveVertex has been released in graph v0.18.0.

Thank you!

Thank you


Add checksum to messages

PR Type
Enhancement, Tests, Other

Description

Implemented the adler32 checksum calculation function within the PPNetwork::Utils namespace.
Added unit tests for the adler32 function, covering both normal and reverse data sequences.
Introduced a GitHub Actions workflow to automate PR reviews, descriptions, and improvements using a PR agent.

Changes walkthrough 📝
Relevant filesTests

test-utils-adler.cppAdd unit tests for Adler-32 checksum calculation

test/test-utils-adler.cpp
Added unit tests for adler32 checksum calculation.  Included tests for both normal and reverse data sequences.

+31/-0

Other

ai.yamlAdd GitHub Actions workflow for PR agent automation

.github/workflows/ai.yaml
Added GitHub Actions workflow for PR agent.  Configured PR agent to auto-review, auto-describe, and auto-improve PRs.

+25/-0

Enhancement

adler.hImplement Adler-32 checksum calculation function

src/utils/adler.h
Implemented adler32 checksum calculation function.  Added namespace PPNetwork::Utils for the function.

+24/-0

💡 PR-Agent usage:
Comment /help on the PR to get a list of all available PR-Agent tools and their descriptions

/describe

/review

/describe

/review

/describe

/review

/review


Revert "bump release runner fanout to 4c runners"

Reverts chainguard-images/images#1409

There isn't a 4 core runner pool

There are three failures unrelated to this change (which only affects postsubmit).  Two of them are weird helm 403s, which I just started a slack thread on and the last is disk pressure hopefully resolved by https://github.com/chainguard-images/images/pull/1571.
I am going to TBR this to unblock our postsubmit builds.


feat: Add new enterprise-contract pipeline

This pipeline is meant to be used by the integration controller to
provider faster feedback to users.
https://issues.redhat.com/browse/HACBS-1005
Signed-off-by: Luiz Carvalho<EMAIL_ADDRESS>

@dirgim, ptal :pray:

I don't have access to merge this PR. Could a generous soul help me out? :pray:

@lcarva you should have access now

Thanks, @Michkov!


How can I gdb tfcompile by using bazel build?

tfcompile is a binary file to compile an inference graph into executable code for tensorflow XLA which created by bazel build.
If I want to gdb tfcompile file on ubuntu 16.04,  it will return message
Reading symbols from /PWD/tfcompile...(no debugging symbols found)...done.

It seem that should make bazel compile with something flag like -g?
I have tried to use
bazel build XXX --compilation_mode=dbg

but there seems not change anything.
How can I resolve this question?
by the way , I'm working on Ubuntu 16.04, bazel version 0.8.1 tensorflow r1.0
Thanks for any help!

Thank you for your post. We noticed you have not filled out the following field in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Thanks.
Have I written custom code
OS Platform and Distribution
TensorFlow installed from
TensorFlow version
CUDA/cuDNN version
GPU model and memory
Exact command to reproduce

This question is better asked on  StackOverflow since it is not a  bug or feature request. There is also a larger community that reads questions there. Thanks!

@xcv9685
Is this problem solved? I have met the similar issue,.though I have compiled the tensorflow/examples/label_image as follows
bazel build --compilation_mode=dbg //tensorflow/examples/label_image/..
but the the final produced binary label_image has no debug symbols .

Reading symbols from ./label_image...(no debugging symbols found)...done.
(gdb) b main
Breakpoint 1 at 0x8b39ab
(gdb) r
Starting program: /home/neo/.cache/bazel/_bazel_neo/b79e78d41078616f7b591dd11d552dc0/execroot/org_tensorflow/bazel-out/k8-dbg/bin/tensorflow/examples/label_image/label_image

@xcv9685
with --strip=never flag ,the  binary was build with debug symbol.
appreciate for your help


Documentation fix to set initial value of cupertino-picker

Updated documentation for the button should be updated to the selected value when the picker is dismissed
#110732
Pre-launch Checklist

[x] I read the [Contributor Guide] and followed the process outlined there for submitting PRs.
[x] I read the [Tree Hygiene] wiki page, which explains my responsibilities.
[x] I read and followed the [Flutter Style Guide], including [Features we expect every widget to implement].
[x] I signed the [CLA].
[x] I listed at least one issue that this PR fixes in the description above.
[x] I updated/added relevant documentation (doc comments with ///).
[X] I added new tests to check the change I am making, or this PR is [test-exempt].
[x] All existing and new tests are passing.

Closing this PR for no further action.


Add basic enchantment extraction

This adds basic enchantment extraction into the JSON file. Note: No rust parser has yet been written.
Do we want the top level to be an array or an object as currently defined in enchants.json? I used the other extracted files as reference and they use objects.

Do we want the top level to be an array or an object as currently defined in enchants.json?

An object. Makes it less of a pain to refactor the code gen if we need to add more info in this json.


Needed GlanceAppWidget RichText

I really want to get a RichText implementation for GlanceAppWidget. At least some functions for pleasant text display.
Can you tell if this will ever be added?
Happy new year 🎄

I'll implement RichText for GlanceAppWidget in the next releases.

Can we expect a simple API to display text with proper line breaks? (simplest solution to start with)
Now I need to save the annotated text to pass to the widget, but it's just a string, and this looks bad.
needed something like rememberRichTextWidgetState
Looks like in the application:

Looks in widget:


Adding the handling for CWR bit in TCP header.

This is in response to a IHV question. Our docs do not specify how to deal with CWR bit in the TCP header.

Thanks for the PR, @pravb! The changes look good, so I'll go ahead and get this merged for you. Should be live within a few minutes.


Default Program Plan when creating Program Enrolment

Hi there,
I noticed that the program plan is no longer be populated automatically when a program enrolment is created. Has this been removed?

Hi @wdci-dev! When creating a Program Enrollment you have the option to select an existing Program Plan or create a new Program Plan. Are you saying that when you populate the Program Plan field on the Program Enrollment with an existing Program Plan that the Program Plan value is not saving?

Hi @wdci-dev - I now understand what you are asking about. HEDA does not currently auto populate the Program Plan field on Program Enrollment with the Primary Plan for the associated Academic Program if left blank at the time of creation. If you were experiencing this behavior it may be due to custom automation built in to satisfy this requirement. I would start there. Does this help?

**lurch: attach W-023785

Tracking W-023785

Hi @jacebryan thanks for the reply. I don't have any customization but I remembered I have tested this before. Maybe I'm looking at the wrong stuff since you have confirmed this feature doesn't exist :)
Any chance that this will be included?

Hi @wdci-dev - Yes. Our team is currently working to build this functionality into HEDA. No ETA as to when it will be released.
A little background for you: Usually we create a Github Issue for everything that requires work but because this specific ask began as an internal investigation we had yet to create the Issue.
However, since you created an Issue for this feature request (much appreciated!) I felt it would be useful to you, our community, and our team to link your submitted Issue to our internal Work Item (i.e. W-023785) in support of transparency. You can also see that @xinnanlisf has referenced the PR that will close this Issue once it's been merged with the master branch of HEDA which means you will receive a notification once the feature has been released.
Hope all that information helps :)

Included in beta release 1.65 (Beta 3)

Included in production release 1.65

@wdci-dev - if you follow the HEDA Release Announcements group in the Power of Us Hub you will see that this enhancement was pushed to Sandboxes on 11/21 and -  if no issues are reported by the HEDA Community - will be pushed to Production instances on 11/27.

Hi @jacebryan thanks for the update. I did follow the issue closely and already upgraded HEDA to 1.65. All good!


Internal Query Preprocessing

After the user inputs a query, we should internally split it between what is used to generate a kNFA and what is used during verification by RE2.
Some motifs contain anchors like < and > ie. ^ and $ for motifs that occur at the N and C terminus. This can be ignored by the IBF but not RE2.
Also the entire regex should be in a capture group (REGEX) so that the match can be reported as a whole

With the right encoding (ie a limit on the kmer length for amino acids) we can encode anchors and optimize the search at the IBF stage

Common operations like explicit count ranges for wildcards are common for biological motifs but not common in any POSIX regex flavour


any docker image command results in "[dumb-init] No such file or directory"?

I'm trying to follow the guide in the README, but no matter what command I run with the image, I get basically the same error:
$ docker run -v ~/archivebox:/data -it nikisweeting/archivebox manage createsuperuser
[dumb-init] manage: No such file or directory

Or with docker-compose:
$ docker-compose run init
[dumb-init] init: No such file or directory

$ docker-compose up
Starting archivebox_archivebox_1 ... done
Attaching to archivebox_archivebox_1
archivebox_1  | [dumb-init] server: No such file or directory
archivebox_archivebox_1 exited with code 2

I looked around in the project's issues and also tried Googling, but of no avail.

@tmladek what Image are you using? I am testing with the current master and I cannot reproduce it.

 I did have an outdated image, I must have already tried to run archivebox on that machine and forgot about it. I thought that by running nikisweeting/archivebox:latest as per the docker-compose.yml, I am really getting the latest image.
Anyway, thanks!


No dashboards are active for the current data set.

Issue type
Support
Have you reproduced the bug with TensorFlow Nightly?
No
Source
binary
TensorFlow version
2.1.0
Custom code
Yes
OS platform and distribution
Ubuntu 22
Mobile device
No response
Python version
3.6
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
NVIDIA RTX
Current behavior?
I am training a model for PPO training using RL with CARLA simulator. While training events files are generated but when I want to visualize the data the browser shows no data to show. I want to show the graph regarding reward and model training.
Standalone code to reproduce the issue
#!/bin/env python
import gym
import macad_gym  # noqa F401
import argparse
import os
from pprint import pprint

import cv2
import ray
import ray.tune as tune
from gym.spaces import Box, Discrete
from macad_agents.rllib.env_wrappers import wrap_deepmind
from macad_agents.rllib.models import register_mnih15_net

from ray.rllib.agents.ppo.ppo_tf_policy import PPOTFPolicy #0.8.5
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.models.preprocessors import Preprocessor
from ray.tune import register_env
import time
import tensorflow as tf
from tensorboardX import SummaryWriter

# from tensorflow.compat.v1 import ConfigProto
# from tensorflow.compat.v1 import InteractiveSession
# config = tf.ConfigProto()
# config.gpu_options.allow_growth = True
# session = InteractiveSession(config=config)
# config = tf.ConfigProto()
# config.gpu_options.per_process_gpu_memory_fraction = 0.7
# tf.keras.backend.set_session(tf.Session(config=config));

parser = argparse.ArgumentParser()
parser.add_argument(
    "--env",
    default="PongNoFrameskip-v4",
    help="Name Gym env. Used only in debug mode. Default=PongNoFrameskip-v4")
parser.add_argument(
    "--disable-comet",
    action="store_true",
    help="Disables comet logging. Used for local smoke tests")
parser.add_argument(
    "--num-workers",
    default=1, #2 #fix
    type=int,
    help="Num workers (CPU cores) to use")
parser.add_argument(
    "--num-gpus", default=1, type=int, help="Number of gpus to use. Default=2")
parser.add_argument(
    "--sample-bs-per-worker", #one iteration
    default=1024,
    type=int,
    help="Number of samples in a batch per worker. Default=50")
parser.add_argument(
    "--train-bs",
    default=128,
    type=int,
    help="Train batch size. Use as per available GPU mem. Default=500")
parser.add_argument(
    "--envs-per-worker",
    default=1,
    type=int,
    help="Number of env instances per worker. Default=10")
parser.add_argument(
    "--notes",
    default=None,
    help="Custom experiment description to be added to comet logs")
parser.add_argument(
    "--model-arch",
    default="mnih15",
    help="Model architecture to use. Default=mnih15")
parser.add_argument(
    "--num-steps",
    default=4000000,
    type=int,
    help="Number of steps to train. Default=20M")
parser.add_argument(
    "--num-iters",
    default=300,
    type=int,
    help="Number of training iterations. Default=20")
parser.add_argument(
    "--log-graph",
    action="store_true",
    help="Write TF graph on Tensorboard for debugging",default=True)
parser.add_argument(
    "--num-framestack",
    type=int,
    default=4,
    help="Number of obs frames to stack")
parser.add_argument(
    "--debug", action="store_true", help="Run in debug-friendly mode", default=False)
parser.add_argument(
    "--redis-address",
    default=None,
    help="Address of ray head node. Be sure to start ray with"
    "ray start --redis-address <...> --num-gpus<.> before running this script")
parser.add_argument(
    "--use-lstm", action="store_true", help="Append a LSTM cell to the model",default=True)

args = parser.parse_args()

model_name = args.model_arch
if model_name == "mnih15":
    register_mnih15_net()  # Registers mnih15
else:
    print("Unsupported model arch. Using default")
    register_mnih15_net()
    model_name = "mnih15"

# Used only in debug mode
env_name = "HomoNcomIndePOIntrxMASS3CTWN3-v0"
env = gym.make(env_name)
# print (env.spec.max_episode_steps,"-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+")
# env.spec.max_episode_steps=1024
# print (env.spec.max_episode_steps,"-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+")

env_actor_configs = env.configs

num_framestack = args.num_framestack
# env_config["env"]["render"] = False

def env_creator(env_config):

    import macad_gym
    env = gym.make("HomoNcomIndePOIntrxMASS3CTWN3-v0")

    # Apply wrappers to: convert to Grayscale, resize to 84 x 84,
    # stack frames & some more op
    env = wrap_deepmind(env, dim=84, num_framestack=num_framestack)
    return env

register_env(env_name, lambda config: env_creator(config))

# Placeholder to enable use of a custom pre-processor
class ImagePreproc(Preprocessor):
    def _init_shape(self, obs_space, options):
        self.shape = (84, 84, 3)  # Adjust third dim if stacking frames
        return self.shape

    def transform(self, observation):
        observation = cv2.resize(observation, (self.shape[0], self.shape[1]))
        # cv2.imshow("observation",observation)
        return observation
def transform(self, observation):
        observation = cv2.resize(observation, (self.shape[0], self.shape[1]))
        return observation

ModelCatalog.register_custom_preprocessor("sq_im_84", ImagePreproc)

if args.redis_address is not None:
    # num_gpus (& num_cpus) must not be provided when connecting to an
    # existing cluster
    ray.init(redis_address=args.redis_address,object_store_memory=10**10,log_to_driver=False)
else:
    ray.init(num_gpus=args.num_gpus,object_store_memory=10**10,log_to_driver=False)

config = {
    # Model and preprocessor options.
    "model": {
        "custom_model": model_name,
        "custom_options": {
            # Custom notes for the experiment
            "notes": {
                "args": vars(args)
            },
        },
        # NOTE:Wrappers are applied by RLlib if custom_preproc is NOT specified
        "custom_preprocessor": "sq_im_84",
        "dim": 84,
        "free_log_std": False,  # if args.discrete_actions else True,
        "grayscale": True,
        # conv_filters to be used with the custom CNN model.
        # "conv_filters": [[16, [4, 4], 2], [32, [3, 3], 2], [16, [3, 3], 2]]
    },
    # preproc_pref is ignored if custom_preproc is specified
    # "preprocessor_pref": "deepmind",

    # env_config to be passed to env_creator

    "env_config": env_actor_configs
}

def default_policy():
    env_actor_configs["env"]["render"] = True

    config = {
    # Model and preprocessor options.
    "model": {
        "custom_model": model_name,
        "custom_options": {
            # Custom notes for the experiment
            "notes": {
                "args": vars(args)
            },
        },
        # NOTE:Wrappers are applied by RLlib if custom_preproc is NOT specified
        "custom_preprocessor": "sq_im_84",
        "dim": 84,
        "free_log_std": False,  # if args.discrete_actions else True,
        "grayscale": True,
        # conv_filters to be used with the custom CNN model.
        # "conv_filters": [[16, [4, 4], 2], [32, [3, 3], 2], [16, [3, 3], 2]]
    },

    # Should use a critic as a baseline (otherwise don't use value baseline;
    # required for using GAE).
    "use_critic": True,
    # If true, use the Generalized Advantage Estimator (GAE)
    # with a value function, see https://arxiv.org/pdf/1506.02438.pdf.
    "use_gae": True,
    # The GAE(lambda) parameter.
    "lambda": 1.0,
    # Initial coefficient for KL divergence.
    "kl_coeff": 0.3,
    # Size of batches collected from each worker.
    "rollout_fragment_length": 128,
    # Number of timesteps collected for each SGD round. This defines the size
    # of each SGD epoch.
    # "train_batch_size": 4000,
    # Total SGD batch size across all devices for SGD. This defines the
    # minibatch size within each epoch.
    "sgd_minibatch_size": 64,
    # Whether to shuffle sequences in the batch when training (recommended).
    "shuffle_sequences": True,
    # Number of SGD iterations in each outer loop (i.e., number of epochs to
    # execute per train batch).
    "num_sgd_iter": 8,
    # Stepsize of SGD.
    "lr": 5e-5,
    # Learning rate schedule.
    # "lr_schedule": None,
    # Share layers for value function. If you set this to True, it's important
    # to tune vf_loss_coeff.
    "vf_share_layers": False,
    # Coefficient of the value function loss. IMPORTANT: you must tune this if
    # you set vf_share_layers: True.
    "vf_loss_coeff": 1.0,
    # Coefficient of the entropy regularizer.
    "entropy_coeff": 0.1,
    # Decay schedule for the entropy regularizer.
    "entropy_coeff_schedule": None,
    # PPO clip parameter.
    "clip_param": 0.3,
    # Clip param for the value function. Note that this is sensitive to the
    # scale of the rewards. If your expected V is large, increase this.
    "vf_clip_param": 10.0,
    # If specified, clip the global norm of gradients by this amount.
    "grad_clip": None,
    # Target value for KL divergence.
    "kl_target": 0.03,
    # Whether to rollout "complete_episodes" or "truncate_episodes".
    "batch_mode": "complete_episodes",
    # Which observation filter to apply to the observation.
    "observation_filter": "NoFilter",
    # Uses the sync samples optimizer instead of the multi-gpu one. This is
    # usually slower, but you might want to try it if you run into issues with
    # the default optimizer.
    "simple_optimizer": False,
    # Use PyTorch as framework?
    "use_pytorch": False,

    # Discount factor of the MDP.
    "gamma": 0.99,
    # Number of steps after which the episode is forced to terminate. Defaults
    # to `env.spec.max_episode_steps` (if present) for Gym envs.
    "horizon": 512,
    # Calculate rewards but don't reset the environment when the horizon is
    # hit. This allows value estimation and RNN state to span across logical
    # episodes denoted by horizon. This only has an effect if horizon != inf.
    "soft_horizon": True,
    # Don't set 'done' at the end of the episode. Note that you still need to
    # set this if soft_horizon=True, unless your env is actually running
    # forever without returning done=True.
    "no_done_at_end": True,
    "monitor": True,

    # System params.
    # Should be divisible by num_envs_per_worker
    "sample_batch_size":
     args.sample_bs_per_worker,
    "train_batch_size":
    args.train_bs,
    # "rollout_fragment_length": 128,
    "num_workers":
    args.num_workers,
    # Number of environments to evaluate vectorwise per worker.
    "num_envs_per_worker":
    args.envs_per_worker,
    "num_cpus_per_worker":
    1,
    "num_gpus_per_worker":
    1,
    # "eager_tracing": True,

    # # Learning params.
    # "grad_clip":
    # 40.0,
    # "clip_rewards":
    # True,
    # either "adam" or "rmsprop"
    "opt_type":
    "adam",
    # "lr":
    # 0.003,
    "lr_schedule": [
        [0, 0.0006],
        [20000000, 0.000000000001],  # Anneal linearly to 0 from start 2 end
    ],
    # rmsprop considered
    "decay":
    0.5,
    "momentum":
    0.0,
    "epsilon":
    0.1,
    # # balancing the three losses
    # "vf_loss_coeff":
    # 0.5,  # Baseline loss scaling
    # "entropy_coeff":
    # -0.01,

    # preproc_pref is ignored if custom_preproc is specified
    # "preprocessor_pref": "deepmind",
   # "gamma": 0.99,

    "use_lstm": args.use_lstm,
    # env_config to be passed to env_creator
    "env":{
        "render": True
    },
    # "in_evaluation": True,
    # "evaluation_num_episodes": 1,
    "env_config": env_actor_configs
    }

    # pprint (config)
    return (PPOTFPolicy, Box(0.0, 255.0, shape=(84, 84, 3)), Discrete(9),config)

# pprint (args.checkpoint_path)
# pprint(os.path.isfile(args.checkpoint_path))

if args.debug:
    # For checkpoint loading and retraining (not used in this script)
    experiment_spec = tune.Experiment(
        "multi-carla/" + args.model_arch,
        "PPO",
        # restore=args.checkpoint_path,
        # timesteps_total is init with None (not 0) which causes issue
        # stop={"timesteps_total": args.num_steps},
        stop={"timesteps_since_restore": args.num_steps},
        config=config,
        # checkpoint_freq=1000, #1000
        # checkpoint_at_end=True,
        resources_per_trial={
            "cpu": 1,
            "gpu": 1
        })

    experiment_spec = tune.run_experiments({
            "MA-Inde-PPO-SSUI3CCARLA": {
                "run": "PPO",
                "env": env_name,
                "stop": {

                    "training_iteration": args.num_iters,
                    "timesteps_total": args.num_steps,
                    "episodes_total": 1024,
                },
                # "restore":args.checkpoint_path,
                "config": {

                    "log_level": "DEBUG",
                   # "num_sgd_iter": 10,  # Enables Experience Replay
                    "multiagent": {
                        "policies": {
                            id: default_policy()
                            for id in env_actor_configs["actors"].keys()
                                # print()
                        },
                        "policy_mapping_fn":
                        tune.function(lambda agent_id: agent_id),
                        "policies_to_train": ["car2","car3"],
                    },
                    "env_config": env_actor_configs,
                    "num_workers": args.num_workers,
                    "num_envs_per_worker": args.envs_per_worker,
                    "sample_batch_size": args.sample_bs_per_worker,
                    "train_batch_size": args.train_bs,
                    "horizon": 512,

                },
                "checkpoint_freq": 5,
                "checkpoint_at_end": True,

            }
        })

else:

    experiment_spec = tune.Experiment(
        "multi-carla/" + args.model_arch,
        "PPO",
        stop={"timesteps_since_restore": args.num_steps},
        config=config,
        resources_per_trial={
            "cpu": 1,
            "gpu": 1
        })

    experiment_spec = tune.run_experiments({
            "MA-Inde-PPO-SSUI3CCARLA": {
                "run": "PPO",
                "env": env_name,
                "stop": {

                    "training_iteration": args.num_iters,
                    "timesteps_total": args.num_steps,
                    "episodes_total": 1024,

                },

                "config": {

                    "log_level": "DEBUG",
                   # "num_sgd_iter": 10,  # Enables Experience Replay
                    "multiagent": {
                        "policies": {
                            id: default_policy()
                            for id in env_actor_configs["actors"].keys()
                        },
                        "policy_mapping_fn":
                        tune.function(lambda agent_id: agent_id),
                        "policies_to_train": ["car2","car3"],
                    },
                    "env_config": env_actor_configs,
                    "num_workers": args.num_workers,
                    "num_envs_per_worker": args.envs_per_worker,
                    "sample_batch_size": args.sample_bs_per_worker,
                    "train_batch_size": args.train_bs,
                    #"horizon": 512, #yet to be fixed

                },
                "checkpoint_freq": 5,
                "checkpoint_at_end": True,

            }
        })

ray.shutdown()

Relevant log output
No response

Hi @SExpert12 ,

It is not looking like tensorflow repo. Could you please provide more information about issue? And You are using old version(2.1.0) here, We are not supporting this version. Could you please execute your code using Latest Version (2.17) and let us know if the issue still persists?

Thank you!

Sure sir. Let me try and I will update you.
Thank you for your help.

Hi @SExpert12 ,

This is not a bug or feature request, for any further queries you may open this issue in tf discussion forum as there is a larger community there.

Thank you!


Integration Testing

Apart from testing of every component individually, it is equally important that they work together while interacting with each other.
Some dataset(big one) should be chosen to test. It makes no sense to include the dataset within the repository. Perhaps it would be better to download it from some external source on the fly.
Tests would be layered. Special command line options would allow for different types of testing.

Dataset is chosen from https://www.githubarchive.org/. Mirror is maintained at https://dhavalkapil.com/elasticsearch-test-dataset/dataset/2015-01-01-15.json.gz
Structure of integrations tests:

dataset/ : Directory that contains scripts to download dataset and load it into a lua table.
operations.lua : Contains functions to actually interact with elasticsearch server, using elasticsearch-lua. Functions pertain to one task. For eg. info, get, etc.
TestFiles : Various test files that call functions from operations.lua in some order. Complete functionality is tested here.


Backporting Placeholder support for Cube Store (#420)

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

26 of 31 (83.87%)  changed or added relevant lines in 4 files are covered.
50 unchanged lines in 6 files lost coverage.
Overall coverage decreased (-6.7%) to 82.433%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

src/parser.rs
3
4
75.0%

tests/sqlparser_common.rs
16
17
94.12%

src/tokenizer.rs
6
9
66.67%

Files with Coverage Reduction
New Missed Lines
%

src/ast/mod.rs
2
70.48%

src/ast/query.rs
2
85.07%

src/parser.rs
2
84.46%

tests/sqlparser_snowflake.rs
2
96.43%

tests/sqlparser_postgres.rs
8
97.06%

tests/sqlparser_common.rs
34
97.2%

Totals

Change from base Build<PHONE_NUMBER>:
-6.7%

Covered Lines:
5617

Relevant Lines:
6814

💛  - Coveralls


PF4 website documentation clarification on Inline Alerts

I was reading through the Inline Alert documentation at:
https://www.patternfly.org/v4/design-guidelines/usage-and-behavior/alerts-and-notifications#inline-alerts
And noticed the icon is specified but not the color used, or the color of the type.

Hey @Rohoover, this issue needs to be created in the patternfly-org repo, would you mind closing this one and creating one there? Thanks!


Update pdm to latest

Via https://latest.cat/pdm

@coffee-cup do I need to run cargo insta test and update the snapshots? 😊


Fixes useExec promise not returning if there's no work to do

Assigned to @dbaeumer based on GH's suggestion.

Good catch.


[Question] Can i use a select for user prompt.

hi,
I want to use a select prompt like rawselect with questionary package but it's doesn't work.
With click can i use a select or an other thing like this, or we can only use prompting in documentation?
Thx for your amazing work.
Regards

Please use Stack Overflow for questions about your own code. This tracker is for issues related to the project itself. Be sure to include a minimal, complete, and verifiable example.


Fixed an error preventing the osf to load in debug mode

This is a quick fix which prevents the osf from loading in debug mode on port 4200

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 71.302%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
5385

Relevant Lines:
7338

💛  - Coveralls


Enhancement Request: pgformatter style formatting

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
--> We use pgformatter  style formatting for SQL as It is suggested by official pg docs, but it is frustrating to use another tool and reformat the SQL.
Describe the solution you'd like
A clear and concise description of what you want to happen.
-->Ideally, I would like to have an additional option when I right-click and go to Format -> "Formate SQL (pgformatter)"
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
--> Currently, it is a two-step process, write SQL in dbeaver and make sure it works, put it in VS Code to format the code and bring the code back to d beaver.
Additional context
Add any other context or screenshots about the feature request here.
--> FYI: pgformatter  uses perl, so it may be hard to integrate in all os. (Ubuntu comes with perl)

Hello @lav-patel,
You can define an external formatter in Preferences ⇒ Editors ⇒ SQL Editor ⇒ Formatting and set Formatter to External formatter.
Does it solve your problem?

I have installed pg_format via the Ubuntu "pgformatter" package and it is working fine in Bash. But when I try to add it as an external formatter in DBeaver, I get Cannot run program "pg_format": error=2, No such file or directory. Could this be due to some sort of Snap sandboxing? (I'm on latest/stable <IP_ADDRESS>209251341 from snapcraft.io)

@boardend Yes, I tried this on DBeaver installed on snap and via non-sandboxing environments. This appears to be the snap issue. Thank you for the information.

Hello @lav-patel,
You can define an external formatter in Preferences ⇒ Editors ⇒ SQL Editor ⇒ Formatting and set Formatter to External formatter.
Does it solve your problem?

It did work, but It made dbeaver unstable, so I had to revert the changes. I'll capture the error I get, and I put it here.

Hello @lav-patel,
You can define an external formatter in Preferences ⇒ Editors ⇒ SQL Editor ⇒ Formatting and set Formatter to External formatter.
Does it solve your problem?

Any progress update for the requested feature? On right click, it would ideally show something like Format SQL (pgFormatter).
I tried to define pgFormatter as my external formatter by setting the Command line value to C:\Strawberry\perl\site\bin\pg_format.bat ${file}, and checking the Use temp file. It successfully formatted the preview.

But when I go to an SQL file, and run the formatter (Ctrl+Shift+F), it doesn't do anything. In fact, the execution is stuck as indicated in my status bar at the bottom of the window. I had to manually cancel the operation.

Yes it doesOn Apr 29, 2023, at 8:56 AM, Theresa De Ocampo @.***> wrote:
Hello @lav-patel,
You can define an external formatter in Preferences ⇒ Editors ⇒ SQL Editor ⇒ Formatting and set Formatter to External formatter.
Does it solve your problem?
Any progress update for the requested feature? On right click, it would ideally show something like Format SQL (pgFormatter).
I tried to define pgFormatter as my external formatter by setting the Command line value to C:\Strawberry\perl\site\bin\pg_format.bat ${file}, and checking the Use temp file. It successfully formatted the preview.
But when I go to an SQL file, and run the formatter (Ctrl+Shift+F), it doesn't do anything. In fact, the execution is stuck as indicated in my status bar at the bottom of the window. I had to manually cancel the operation.
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you were mentioned.Message ID: @.***>

Hello.
I am trying to install pg-formatter in DBEAVER.
Is there any tutorial on how to do it? I have tried to follow the steps in the README, but it does not work for me.
I appreciate if someone can send me the step by step.

Hello.
I am trying to install pg-formatter in DBEAVER. Is there any tutorial on how to do it? I have tried to follow the steps in the README, but it does not work for me.
I appreciate if someone can send me the step by step.
I have Windows 11

Me too

Freaking internat man ... i just lost multiple hours trying to find some good formatter for dbeaver that is free and does what i need ... god damn man the only answers i find is "dbeaver supports external formatter" or "there are free formatters online" or "read the documentation" but no one helps with installing these things step by step ... like i'm supposed to know another part of the programming/it/whatever world. shame on you guys for not spending a couple of minutes helping us out! i stopped looking and hpoing for an answer and asked chatgpt and installed it successfully. Though it would be nice to have multiple built in formatters inside dbeaver.
Rant over.
Because this is the top result when looking for dbeaver and pgformatter(at least for me) i'll provide here how i did it.
Step 1: Download and Install Perl from here https://strawberryperl.com/
Just go for latest release and simplest way is to download the msi (it's a windows installer you just double click next next finish)
To check if everything is ok open Command Prompt and write: "perl -v" if you get something then SUCCESS!!! if not ... u need to google the problem and start over.
Step 2: chatgpt says to install some perl modules because pgformatter needs them (i didn't so i didn't install but you may need them so here it is)
Open Command Prompt as Administrator and type:
cpan Text::CSV
cpan JSON::PP
cpan CGI
Step 3: Download and "install" pgformatter. Many options to download you'll find here: https://www.postgresql.org/about/news/pgformatter-v53-released-2493/
I just used sourceforge and got a zip file i unzipped it to "C:\tools\pgFormatter". Attention! In this folder is the "pg_format" file. You can unzip wherever you want.
To check if all is good you need to open Command Prompt go to the folder you have pgformatter like this:
"cd C:\tools\pgFormatter"
and then
"perl pg_format --version"
If you get something and not an error SUCCESS !!!! if there is an error please check the path
*Step 3.1: **
This is optional but i usually do this for ease of use. You can skip it if you want. Add "C:\tools\pgFormatter" to the system environment path so when opening command prompt you can just do this wherever you are "pg_format --version" or if you want actually format something then like this "pg_format -f input.sql -o output.sql"
NOTE: If this doesn't work go to your folder "C:\tools\pgFormatter" create a new bat (create it as txt and then change extension) file paste this:
"
@echo off
perl C:\tools\pgFormatter\pg_format %
"
Step 4
Go to DBeaver then Window -> Preferences -> Editors -> SQL Editor -> Formatting then select external formatter and paste in the command line this: "perl C:\tools\pgFormatter\pg_format -" -> Apply -> Apply & Close.
Nothing more
All the options to configure the formatter are in the readme file:
https://github.com/darold/pgFormatter
If you don't get this then for example in dbeaver where you wrote "perl C:\tools\pgFormatter\pg_format -" for example if you want to have indent set at 8 you modify the line like this:
"perl C:\tools\pgFormatter\pg_format -s 8 -"
Furthermore if you want to add a newline after each comma then you modify the line like this:
"perl C:\tools\pgFormatter\pg_format -s 8 -B -"
If anyone want to jump in with more deatils please do and if you want to copy paste it and help others struggling please feel free to give them these steps.
Hope it helps the next poor soul trying to do this

@atr0000 thanks for the feedback.
We don't provide instructions because there are just too many options - and the steps for each of those differ drastically.


Custom Properties for Dashboard Data Models

Is your feature request related to a problem? Please describe.
Dashboard Data Models are missing the Custom Properties.
Describe the solution you'd like
I would like to have the ability to register custom properties for  Dashboard Data Models.
Describe alternatives you've considered
Now I'm using the Dashboard  Custom Properties.

@mohityadav766 @sonika-shah, I verified that the API does not support extension in dashboard data models. Therefore, backend changes will be required.
REQ: http://localhost:8585/api/v1/dashboard/datamodels/name/sample_looker.model.orders
fields: owner,tags,followers,votes,domain,dataProducts,extension

RES:
{
    "code": 400,
    "message": "Invalid field name extension"
}

@mohityadav766 @sonika-shah, I have opened a PR here: feat(#16208): custom properties for Dashboard Data Models. Please push the backend changes directly to this PR.


Clean up apt block

Remove the conditional apt block (replacing it with simple include ::apt). Also explicitly state that apt::update should come before any packages are installed.

Jenkins standing by to test this. If you aren't a maintainer, you can ignore this comment. Someone with commit access, please review this and clear it for Jenkins to run; then  say 'jenkins, test it'.

Jenkins standing by to test this. If you aren't a maintainer, you can ignore this comment. Someone with commit access, please review this and clear it for Jenkins to run; then  say 'jenkins, test it'.

Reverted to short key and rebased

jenkins, test it

jenkins, test it


allowed 'CustomScalar | None' syntax for python >= 3.10

Since ScalarWrapper is kind of its own thing, I couldn't find another way than to define __or__ directly on the class.
From what I've gather about pending refactors (i.e. StrawberryScalar), it shouldn't stay like that forever.

Description

Types of Changes

[ ] Core
[ ] Bugfix
[ ] New feature
[x] Enhancement/optimization
[ ] Documentation

Issues Fixed or Closed by This PR

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 added tests to cover my changes.
[x] I have tested the changes and verified that they work and don't break anything (as well as I can manage).

Thanks for adding the RELEASE.md file!

Here's a preview of the changelog:

Allowed CustomScalar | None syntax for python >= 3.10.

Here's the preview release card for twitter:

Here's the tweet text:
🆕 Release (next) is out! Thanks to Guillaume Andreu Sabater for the PR 👏

Get it here 👉 https://github.com/strawberry-graphql/strawberry/releases/tag/(next)


Request feature update_with_media more than one image

I need to upload two images, like this:
tweet = api.update_with_media(['image1.png', 'image2.png'], status=msg)
Is it possible?
Thanks

The update_with_media endpoint is deprecated by Twitter. To post multiple images, you should use media_upload. It will looks something like this:
images = ('image1.png', 'image2.png')
media_ids = [api.media_upload(i).media_id_string for i in images]
api.update(status=msg, media_ids=media_ids)

" api.update_status " works for me.  INSTALLED: 3.5.0
images = ('image1.png', 'image2.png')
media_ids = [api.media_upload(i).media_id_string for i in images]
tweet = api.update_status(status=msg, media_ids=media_ids)

You should include this snippet to examples.

The update_with_media endpoint is deprecated by Twitter. To post multiple images, you should use media_upload. It will looks something like this:
images = ('image1.png', 'image2.png')
media_ids = [api.media_upload(i).media_id_string for i in images]
api.update_status(status=msg, media_ids=media_ids)

edited: typed update/update_status typo

This gives the following error to me:
Traceback (most recent call last):
  File "/home/bog/2test.py", line 31, in <module>
    status = api.update_status_with_media(status=tweet, media_id=media_ids)
  File "/home/bog/.local/lib/python3.9/site-packages/tweepy/api.py", line 46, in wrapper
    return method(*args, **kwargs)
TypeError: update_status_with_media() missing 1 required positional argument: 'filename'

here is the code:

# create tweet
tweet = "Test con img"
pics = ("ninja.jpg", "ninja2.jpg")
media_ids = [api.media_upload(i).media_id_string for i in pics]

status = api.update_status_with_media(status=tweet, media_id=media_ids)

Any advice?

Please don't necrobump old closed issues.
This is unrelated to this issue, and as the error says, API.update_status_with_media requires a filename argument.
If you want to create a Tweet with media IDs, you can use API.update_status instead.

" api.update_status " works for me. INSTALLED: 3.5.0
images = ('image1.png', 'image2.png')
media_ids = [api.media_upload(i).media_id_string for i in images]
tweet = api.update_status(status=msg, media_ids=media_ids)

I get an error:
'Media' object has no attribute 'media_id_str'

Again, please don't necrobump old closed issues.
And again, this is unrelated to this issue.
As the error says, there is no media_id_str attribute. Your error does not match that code, which uses the media_id_string attribute. See Twitter's API documentation on uploading media and for the POST media/upload endpoint.


Link next to searchbox ? makes no sense!

@fichtner
Since I use opnsense, I've been wondering what the meaning of the link is, right next to the search box. Somehow this does not make sense?
Wouldn´t it make more sense to use this link for something useful or to use the space for something else?

it's your user name, host name and domain. it's pretty useful to know. the link markup is just due to the bootstrap styling, but is not meant to be clickable unless we maybe want to link to system_usermanager_passwordmg.php ? what does @AdSchellevis think?

@fichtner

clickable unless we maybe want to link to system_usermanager_passwordmg.php

thats a great idea and makes sense!

@fichtner
@AdSchellevis
it would be best to use the link to get to the account settings of the currently logged user!

to be honest, I don't see real value in linking the user+domain part to the password page, but if it makes people happy, I don't mind ignoring that.

I guess it's either that or trying to remove the hover link notion

I can live with both, but prefer to ditch the hover, but that's probably a matter of taste.

it is alright to see with which user you logged in, but then it would also make sense to use this "link" meaningful. Just to take away the hover would be in my opinion not very meaningful.
but you have to decide that!
regards
rené

about that password page in general, should we always allow the page like logout ?

probably not, if the user isn't allowed to change it's password..... I don't use it, but I can see scenario's where people might want that

ok, best to only remove the markup then, because sometimes the link may not be available...


Fix ps-context edge cases

Please be sure to check out our contributing guidelines
before submitting your pull request.
Fixes #1524.
Proposed Changes

Checks to determine whether or not the prompt utilizes the editor:info before resetting the prompt. We ignore the completing as I did not observe it being an issue and only one prompt utilizes it with nothing else.
Removes the ps-context.
Fixes the smiley prompt.

@belak @yevhen-m - I was able to cut down the amount of files I thought I needed to edit, by utilizing zstyle instead of updating all of the prompts. This should resolve the issue for good at this point as it will only affect prompts that require a redraw.

This seems consistent with the temporary fix I was trying locally (but couldn't explain).
I pushed an updated version with only reflowed comments.
One question I've got though - will this continue to work with the sorin prompt, where we call this manually? When does zle reset-prompt actually need to be called?

Yes.
It needs to be called when the edit mode changes. If you're setup to use the big keymap, then hit ESC and you'll see the prompt redraw for certain themes (sorin, giddie, paradox to name a few). The contextual prompt showing whether you're in edit, overwrite or alternate is the crux of the issue here.
The ps-context is being removed because it should have been showing by default for everyone anyways. Without it enabled the only prompts that are affected are the same ones that require a redraw anyway.
I'll update the commit message as well. I haven't seen the updated push but I'll check again in the AM.

*vi keymap. Can't edit on my phone. Grrr.

If you've got updated text for a commit message, I can make the change and merge it. I'm fairly comfortable with this.

reset-prompt should only be called when the appropriate zstyle is set.

For clarification, if anyone is trying to fix this again - reset-prompt needs to be called in most instances. There are a number of prompts which rely on reset-prompt in order to update the display in the case of a keymap change which don't need to use editor_info in order to read from the KEYMAP variable.


feat: user config + default config merge for MeterProvider, Meter

Please review https://github.com/open-telemetry/opentelemetry-js/pull/1493 first, it is simpler than this PR, but shares some similarities.
Which problem is this PR solving?

partially #1417

Short description of the changes
@naseemkullah
Member
naseemkullah commented on Sep 3 •
Which problem is this PR solving?
partially #1417
Short description of the changes

Deep merge user supplied Meter and MeterProvider configs into default config by means of lodash.merge

Please review #1493 first, it is simpler than this PR, but shares some similarities.

lint failing in untouched file /home/runner/work/opentelemetry-js/opentelemetry-js/packages/opentelemetry-web/src/utils.ts
/home/runner/work/opentelemetry-js/opentelemetry-js/packages/opentelemetry-web/src/utils.ts
  128:70  error  Replace `⏎····PerformanceResourceTiming⏎··` with `PerformanceResourceTiming`  prettier/prettier

✖ 1 problem (1 error, 0 warnings)
  1 error and 0 warnings potentially fixable with the `--fix` option.


TestApp uses NibClassBuilder, dropped in XCode 4+

@typemytype @typesupply @adrientetar any pointers on how to fix this?

The line just needed to be deleted. I just pushed a change that lets the app launch. Beyond launching, um, I don't know if it still works. I haven't touched this in years.

It's not that simple. I have recent versions of setuptools and pyobjc. The app compiles but crashes on launch, because NibClassBuilder is still referenced. Removing it allows the app to launch, but then it crashes later, upon opening a UFO. Traceback below. Doesn't seem like it has anything to do with nib loading though. I'll try to look into it.
Traceback (most recent call last):
  File "/TestApp/dist/DefconAppKitTest.app/Contents/Resources/DefconAppKitTest.py", line 35, in readFromFile_ofType_
    window = self.vanillaWindowController = DefconAppKitTestDocumentWindow(font)
  File "/TestApp/dist/DefconAppKitTest.app/Contents/Resources/DefconAppKitTest.py", line 82, in __init__
    deleteCallback=self.collectionViewDeleteCallback, selfDropSettings=selfDropSettings, selfApplicationDropSettings=dropSettings)
  File "defconAppKit/controls/glyphCollectionView.pyc", line 143, in __init__
  File "defconAppKit/controls/glyphCellView.pyc", line 90, in initWithFrame_cellRepresentationName_detailWindowClass_
AttributeError: 'super' object has no attribute 'initWithFrame_'

Try changing that line to:
self = super(DefconAppKitGlyphCellNSView, self).alloc().initWithFrame_(frame)

There was a time ages ago when PyObjC was kinda flaky about the alloc call. It could have been the last time I worked on this branch.

Replaced line 90 and now the error is:
AttributeError: 'super' object has no attribute 'alloc'

Good times!
(And people wonder why the next MetricsMachine isn't finished.)

This works:
self = DefconAppKitGlyphCellNSView.alloc().initWithFrame_(frame)

The app compiles and launches, but then it freezes when switching to the GlyphCollectionView or GlyphView tabs. The traceback is now this:
Traceback (most recent call last):
  File "defconAppKit/controls/glyphCellView.pyc", line 332, in drawRect_
  File "defcon/objects/base.pyc", line 338, in getRepresentation
TypeError: GlyphCellFactory() takes at least 4 arguments (5 given)

I'll keep digging and report back if I get stuck.

@miguelsousa Looking at this, I think the root cause here may be that you're using the UFO3 branch of defcon, where this was likely written for the master branch — it looks (quick reading, could be missing something) that representations are slightly different in the UFO3 branch, which may be the reason here.

@benkiel you're right, this last error is caused by that. Thanks!


Appstudio update test-component-pac-lfgp

Pipelines as Code configuration proposal

Pipelines as Code CI/test-component-pac-lfgp-on-pull-request has successfully validated your commit.

StatusDurationName

✅ Succeeded
7 seconds
init

✅ Succeeded
32 seconds
clone-repository

✅ Succeeded
1 minute
build-container

✅ Succeeded
19 seconds
deprecated-base-image-check

✅ Succeeded
20 seconds
inspect-image

✅ Succeeded
3 minutes
clair-scan

✅ Succeeded
52 seconds
clamav-scan

✅ Succeeded
15 seconds
sbom-json-check

✅ Succeeded
11 seconds
label-check

✅ Succeeded
10 seconds
optional-label-check

✅ Succeeded
6 seconds
show-summary

Pipelines as Code CI/test-component-pac-lfgp-on-pull-request has successfully validated your commit.

StatusDurationName

✅ Succeeded
6 seconds
init

✅ Succeeded
13 seconds
clone-repository

✅ Succeeded
27 seconds
build-container

✅ Succeeded
12 seconds
inspect-image

✅ Succeeded
10 seconds
deprecated-base-image-check

✅ Succeeded
16 seconds
clair-scan

✅ Succeeded
38 seconds
clamav-scan

✅ Succeeded
13 seconds
sbom-json-check

✅ Succeeded
13 seconds
label-check

✅ Succeeded
12 seconds
optional-label-check

✅ Succeeded
4 seconds
show-summary


impossible de mettre  une photo en "background-image"

Prerequisites

[ ] Can you reproduce the problem with Debug -> Reload Without Extensions?
[ ] Did you perform a cursory search to see if your bug or enhancement is already reported?
[ ] Did you read the Troubleshooting guide?

For more information on how to write a good bug report read [here](https://github

.com/adobe/brackets/wiki/How-to-Report-an-Issue)
For more information on how to contribute read here
Description
[Description of the bug or feature]
Steps to Reproduce

[First Step]
[Second Step]
[and so on...]

Expected behavior: [What you expected to happen]
Actual behavior: [What actually happened]
Versions
Please include the OS and what version of the OS you're running

.

Please include the version of Brackets. You can find it under Help -> About Brackets (Windows and Linux) or Brackets -> About Brackets (macOS)

impossible de mettre une photo en background -image


there should be a mail_host parameter and if it is localhost then we install postfix

Added two params 'mail_host' and 'mail_port' in install script and puppet setup, and altered template for alf-glob.props


Cannot use instructor with o1-preview

[X] This is actually a bug report.
[ ] I am not getting good LLM Results
[ ] I have tried asking for help in the community on discord or discussions and have not received a response.
[X] I have tried searching the documentation and have not found an answer.

What Model are you using?

[ ] gpt-3.5-turbo
[ ] gpt-4-turbo
[ ] gpt-4
[X] Other (please specify)

Model: o1-preview
Describe the bug
When using instructor with o1-preview I run into an error -

import instructor
from pydantic import BaseModel
from openai import OpenAI

# Define your desired output structure
class UserInfo(BaseModel):
    name: str
    age: int

# Patch the OpenAI client
client = instructor.from_openai(OpenAI())

# Extract structured data from natural language
user_info = client.chat.completions.create(
    model="o1-preview",
    response_model=UserInfo,
    messages=[{"role": "user", "content": "John Doe is 30 years old."}],
)

print(user_info.name)
#> John Doe
print(user_info.age)
#> 30

Results in -
Traceback (most recent call last):
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/instructor/retry.py", line 185, in retry_sync
    response = func(*args, **kwargs)
               ^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/openai/_utils/_utils.py", line 274, in wrapper
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/openai/resources/chat/completions.py", line 742, in create
    return self._post(
           ^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/openai/_base_client.py", line 1270, in post
    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/openai/_base_client.py", line 947, in request
    return self._request(
           ^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/openai/_base_client.py", line 1051, in _request
    raise self._make_status_error_from_response(err.response) from None
openai.BadRequestError: Error code: 400 - {'error': {'message': "Unsupported parameter: 'tools' is not supported with this model.", 'type': 'invalid_request_error', 'param': 'tools', 'code': 'unsupported_parameter'}}

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/instructor/retry.py", line 182, in retry_sync
    for attempt in max_retries:
                   ^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/tenacity/__init__.py", line 443, in __iter__
    do = self.iter(retry_state=retry_state)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/tenacity/__init__.py", line 376, in iter
    result = action(retry_state)
             ^^^^^^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/tenacity/__init__.py", line 419, in exc_check
    raise retry_exc from fut.exception()
tenacity.RetryError: RetryError[<Future at 0x11040bec0 state=finished raised BadRequestError>]

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/ays57/Documents/Projects/RubberDuckVerification/t.py", line 51, in <module>
    user_info = client.chat.completions.create(
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/instructor/client.py", line 119, in create
    return self.create_fn(
           ^^^^^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/instructor/patch.py", line 291, in new_create_sync
    response = retry_sync(
               ^^^^^^^^^^^
  File "/Users/ays57/miniconda3/envs/rdv/lib/python3.12/site-packages/instructor/retry.py", line 220, in retry_sync
    raise InstructorRetryException(
instructor.exceptions.InstructorRetryException: Error code: 400 - {'error': {'message': "Unsupported parameter: 'tools' is not supported with this model.", 'type': 'invalid_request_error', 'param': 'tools', 'code': 'unsupported_parameter'}}

It looks like instructor is trying to call the opeani API for o1-preview with function calling when this is not supported.
I am observing similar behavior when using litellm with instructor for o1-preview.

Hi @threewisemonkeys-as , can you try this instead?
client = instructor.from_openai(OpenAI(), mode=instructor.Mode.JSON_O1)

O1 is a bit funky in the sense that it doesn't have tool calling, streaming or even support for a system prompt so i'd recommend sticking to JSON_O1 for now.
I tested it out and the code below works. Going to close this issue for now.
import instructor
from pydantic import BaseModel
from openai import OpenAI

# Define your desired output structure
class UserInfo(BaseModel):
    name: str
    age: int

# Patch the OpenAI client
client = instructor.from_openai(OpenAI(), mode=instructor.Mode.JSON_O1)

# Extract structured data from natural language
user_info = client.chat.completions.create(
    model="o1-preview",
    response_model=UserInfo,
    messages=[{"role": "user", "content": "John Doe is 30 years old."}],
)

print(user_info.name)
# > John Doe
print(user_info.age)
# > 30

Thanks for the speedy response!
Have you thought of modifying the behavior of instructor to use JSON_O1 by default if model='o1-preview' by default?


G

Describe the bug
A clear and concise description of what the bug is and what you expected to happen.
To Reproduce
Steps to reproduce the behavior:

Go to '...'
Click on '....'
Scroll down to '....'
See error

Screenshots
If applicable, add screenshots to help explain your problem.
Device (please complete the following information):

iOS Version:
iOS Device:
unc0ver Version:

Place an "x" between the brackets if true:

[ ] this is a bug others will be able to reproduce
[ ] this issue is present with all tweaks uninstalled(except for default packages) or disabled
[ ] this issue is present after a rootfs restore
[ ] this issue is present on the latest version of unc0ver

Logs
If applicable, add logs or error messages here.

Lemon apple cherry pie?

After long and careful consideration. We have come to the conclusion,,, No.


Add automation for the Resistance group of Familiar Abilities

The rule elements for the base Resistance ability are a bit clunky but it gets the job done and allows for the upgrades from the other two abilities.
Happy for some tips if there's a more succinct way to do the same though.

Technically this should get a migration to set some defaults on familiars who already have resistance but not either of the other two, but that's likely a small number of actors and it would be us injecting some default choice for players which I like less than making a bit of console noise.


Can't set ScrollBar Thumb Background using style selectors

I'd like to set the Background color when mousing over the ScrollBar thumb. Unfortunately, I still can't get this to work without copying over the entire original ScrollBar.xaml and modifying it.
I think the problem is the DynamicResource used for the Background. It appears to be overriding any changes I make to the background afterwards.
From the ScrollBar.xaml template
<Thumb Name="thumb">
    <Thumb.Template>
        <ControlTemplate>
            <Border Background="{DynamicResource ThemeControlHighBrush}" />
        </ControlTemplate>
    </Thumb.Template>
</Thumb

Custom overrides for the mouse over
<Style Selector="ScrollBar:horizontal /template/ Thumb#thumb /template/ Border">
    <Setter Property="Background" Value="Blue"/>
</Style>
<Style Selector="ScrollBar:horizontal /template/ Thumb#thumb /template/ Border:pointerover">
    <Setter Property="Background" Value="Red"/>
</Style>

The above overrides don't work until I remove the Background in the initial declaration.

Benedikt Schroeder@Gillibald
I think the template should be fixed by using a TemplateBinding and assigning the default to the background property. That way you can override it. Could you create an issue?

It might also be a good idea to add a default hover style to the default template to give it a more responsive feel.

One additional issue, even after disabling that original DynamicResource Background color, once I start dragging the thumb it reverts back to the original color.

This should be fixed.

Thanks for fixing this!
Do you know if the original style selectors I posted should work, or do they require some modification? I tried adding the code to the control catalog demo and it didn't seem to have any affect.
<Style Selector="ScrollBar:horizontal /template/ Thumb#thumb /template/ Border">
    <Setter Property="Background" Value="Blue"/>
</Style>
<Style Selector="ScrollBar:horizontal /template/ Thumb#thumb /template/ Border:pointerover">
    <Setter Property="Background" Value="Red"/>
</Style>

You need to target the Thumb itself


Adding URL ID to UXF_UI

I was wondering if it would be possible to add an additional PPID mode where the ID is grabbed directly from the URL.
I'm using Prolific to recruit participants which then are redirected to Gorilla, and finally to the web page of the WebGL experiment. The addressbar contains their unique participant ID in this form: http://www.your-url-above.com?id=PUBLICID
Gorilla and Prolific have a nice way of integrating their unique participant IDs: https://researcher-help.prolific.co/hc/en-gb/articles/360009223973-Gorilla-Integration-Guide
If the variable PUBLICID could be used directly, it would save the possible user error of entering this manually, and would make for a simple way to match all the data across multiple platforms without the need of several different generated unique IDs per participant.
If I was more comfortable editing the UIController.cs script I would attempt a pull request for this functionality but I think I would just mess it up!

Nice idea, I might get around to adding this - for a quick fix you could call javascript from Unity:
https://docs.unity3d.com/Manual/webgl-interactingwithbrowserscripting.html
Using this code from here:
https://stackoverflow.com/questions/901115/how-can-i-get-query-string-values-in-javascript
mergeInto(LibraryManager.library, {

  GetPPID: function () {
    var urlParams = new URLSearchParams(window.location.search);
    var myParam = urlParams.get('ppid');
    return myParam;
  }

)

Call this from Unity, then use this PPID to start the session manually, or set PPID to automatic but then record this new ppid elsewhere

Awesome thank you!


loadEnv overrides content from .env(.{mode})?.local with .env(.{mode})?

Just to make my issue title clearer, an example would be that the file .env.local could contain a PORT=5001, and the file .env would contain PORT=5000, then the result of loadEnv('development', process.cwd) would be
// import { loadEnv } from 'vite';
// console.log(loadEnv('development', process.cwd))
{
	'PORT': 5000 // assumed to be `5001` from `.env.local`!
	...
}

https://github.com/vitejs/vite/blob/e034ee2d9c7ef1497d1c9248ef05cdd8e0efb6ad/packages/vite/src/node/config.ts#L808-L824
In the code snippet above, since the envFiles array specifies .env.local before .env, the content of .env overrides .env.local. Actually, it even overrides other modes that would be loaded before the default .env. This effectively prevents me from providing default values for the .env file that is not gitignored (unless I add a default in the code).
Is this intentional? By reading https://vitejs.dev/guide/env-and-mode.html#env-files , I thought that since .env.*.local would override the values of .env, since it is ignored and probably contains private data...
Note : The plan was the use env variables in my config, especially for the dev server's port, like hinted at here : https://github.com/vitejs/vite/issues/1930#issuecomment-783747858
Thanks in advance!

Actually, the issue might be different :
.env :
# PORT=

.env.local :
PORT=5001

vite.config.ts :
...
import { defineConfig, loadEnv } from 'vite';

export default defineConfig(({ mode }) => {
	console.log(mode); // development

	Object.assign(process.env, loadEnv(mode, process.cwd()));

	const isProduction = mode === 'production';

	console.log('env port : ', process.env.PORT); // env port :  undefined
	const port: number = parseInt(process.env.PORT) || 5000;

	...

Seems like my .env.local isn't loaded at all - any idea why could that be?

Actually, the issue might be different :
.env :
# PORT=

.env.local :
PORT=5001

vite.config.ts :
...
import { defineConfig, loadEnv } from 'vite';

export default defineConfig(({ mode }) => {
	console.log(mode); // development

	Object.assign(process.env, loadEnv(mode, process.cwd()));

	const isProduction = mode === 'production';

	console.log('env port : ', process.env.PORT); // env port :  undefined
	const port: number = parseInt(process.env.PORT) || 5000;

	...

Seems like my .env.local isn't loaded at all - any idea why could that be?


'GTLDefines.h' file not found

Repro steps:

Start an iOS project with Podfile:

platform :ios, '9.3.1'

use_frameworks!

pod 'GoogleAPIClient', '~> 1.0.2'
pod 'GTMOAuth2', '~> 1.1.0'

Write an API for Google Cloud Endpoints and build it to get a discovery file out.

Clone this repo and build the ServiceGenerator tool from it, then run that tool on the discovery doc to generate Objective-C sources for the client to your cloud endpoints API.

CURRENT_DIR=`pwd`
REPO_DIR="google-api-objectivec-client-temp"

# Clone the Google API client library from git. Using --recursive gets the stuff in Deps too.
git clone --recursive https://github.com/google/google-api-objectivec-client.git ${REPO_DIR}

# Build the ServiceGenerator binary
cd ${REPO_DIR}/Source/Tools/ServiceGenerator/
xcodebuild -project ServiceGenerator.xcodeproj -alltargets -configuration Release build

# Run the ServiceGenerator on our discovery doc
cd ${CURRENT_DIR}
${REPO_DIR}/Source/Tools/ServiceGenerator/build/Release/ServiceGenerator ./foo-v1-rpc.discovery --outputDir ./foo-ios-client

# Clean up
rm -rf ${REPO_DIR}

Add GTLFoo.h and GTLFoo_Sources.m to your project in XCode, where Foo is the name of your API.

In your bridging header file, import your API header:

#import "GTLFoo.h"

Build. You'll get build errors (Foo below is now Api):

/Users/Eliot/dev/biketracker/biketracker-ios/BikeTracker/BikeTracker-Bridging-Header.h:20:9: note: in file included from /Users/Eliot/dev/biketracker/biketracker-ios/BikeTracker/BikeTracker-Bridging-Header.h:20:
#import "GTLApi.h"
        ^
/Users/Eliot/dev/biketracker/biketracker-ios/biketracker-ios-client/GTLApi.h:16:9: note: in file included from /Users/Eliot/dev/biketracker/biketracker-ios/biketracker-ios-client/GTLApi.h:16:
#import "GTLApiConstants.h"
        ^
/Users/Eliot/dev/biketracker/biketracker-ios/biketracker-ios-client/GTLApiConstants.h:21:11: error: 'GTLDefines.h' file not found
  #import "GTLDefines.h"
          ^
<unknown>:0: error: failed to import bridging header '/Users/Eliot/dev/biketracker/biketracker-ios/BikeTracker/BikeTracker-Bridging-Header.h'

GTLDefines.h is in the Pod, at Pods/GoogleAPIClient/Source/GTLDefines.h. Why can't XCode see it?
Build Settings -> Header Search Paths contains "$(inherited)".

The GTLApi* files missing is likely because they aren't on the Header Search Path for your project.  You can likely do the same thing mentioned in https://github.com/google/google-api-objectivec-client/wiki/BuildingTheLibrary#compiling-the-source-files-directly-into-a-mac-or-ios-application, specifically: Add the service's source folder, such as Source/Services/ServiceName/Generated, to the Header Search Path entry of you project's build settings.
Your generated headers not finding the the Core is more interesting.  Since you are using frameworks, the import likely needs to be a framework import. @perotinus how does this work for the services we ship?  We don't seem to be enabled any framework #import from for, what would need needed here?

When you added the Api's to your project, did you do it to and existing target?  Make a new one?  i.e. - what settings did it pick up from the other pods or is it left to all the Xcode defaults.

XCode can find the header files under my generated code just fine, it's when it compiles them and needs to find the Core stuff that it fails.
Did it to an existing target. Everything is XCode defaults. I've added GTLFoo_Sources.m to the "Compile Sources" phase under the target though.

I think CocoaPods allows sources within the Pod (maybe its subspecs too) to access headers in the Pod with #include "X.h" paths. It doesn't propagate that to the depender, though: the depender can access the headers through the
I think we'd either have to modify the podspec to explicitly add that header search path to the user's project (not all that pretty) or modify the service generator to generate in a "framework mode" where it accesses the headers with #import <GoogleAPIClient/GTLDefines.h>.
On that note, it might also be interesting to generate a local podspec for the created files, and tell the user to add that to their Podfile.

Ok, locally generate API isn't something we've fully sorted through the interactions with CocoaPods then.
@eliotstock Sounds like to get things building you have two options:

Add a Pods/GoogleAPIClient/Headers/Core to the Header Search Paths in Xcode
Tweak the generated files to use #import <GoogleAPIClient/GTLDefines.h>.

Yes, neither is great.  We'll look at trying to come up with a better way to handle this.

Apologies, I think that path is wrong! My bad.
I expect that instead you'll need to add:
<project_dir>/Pods/GoogleAPIClient/Source and <project_dir>/Pods/GoogleAPIClient/Source/Utilities, which contain the actual headers.

On option 1, the Header Search Paths are, I think, relative to the directory in which the .xcodeproj file sits. So in my case I tried:
./Pods/GoogleAPIClient/Source
./Pods/GoogleAPIClient/Source/Utilities

And also:
$SRCROOT/Pods/GoogleAPIClient/Source
$SRCROOT/Pods/GoogleAPIClient/Source/Utilities

I still get the same build error.
On option 2, which source files in the generated code need this hack? There are imports in every header for one of:

GTLDefines.h
GTLObject.h
GTLQuery.h
GTLService.h

Are you saying I need to edit every header file and change this sort of thing:
#if GTL_BUILT_AS_FRAMEWORK
  #import "GTL/GTLObject.h"
#else
  #import "GTLObject.h"
#endif

to this?
#import <GoogleAPIClient/GTLObject.h>

Re edit the header, yes.  That's what I was thinking might work.
There's gotta be a Header Search Path trick that also works…wait, try User Header Search Path also?  There's another Xcode setting that toggle if the user and system path are checked independently.
I haven't gotten a chance to try to recreate this locally, so I'm somewhat stuck trying to guess what the layout is.  :(

Got it. You forgot:
./Pods/GoogleAPIClient/Source/Objects
If I add that to Header Search Paths or User Header Search Paths, my main target builds. My *Test target still fails to build, but I think I can sort that out.
The approach @perotinus mentioned where you'd modify the service generator to generate in a "framework mode" sounds pretty good to me. Can we leave this open till you've had a crack at that?

Yup, please keep it open.  We're kicking around idea, nothing pretty at the moment.  :(

I dug into this a bit more, and it appears that it only happens with the Swift bridging header. Importing the header in Objective-C code works fine.
I think this has to do with header maps. When I disable header maps, the Objective-C import fails as well. When I disable header maps in the pod project, the GoogleAPIClient pod fails to build, because it can't find its own headers. Perhaps the bridging header doesn't use the header map, and so it fails to build? It looks like the bridging header gets access to its project's (target's?) header map, while the Objective-C code gets access to the header maps for everything.
I'm not quite sure why this is so. It seems like the header map magic breaks in this particular case, but they're much too magical for me to understand whether this is something we can fix. We might end up having to go with one of the ugly solutions, adding more preprocessor defines and checks as needed to make this case work. I can't think of a clean solution here right now (though it's Friday evening, so that may not be a surprise),

OK, I haven't thought of any cleaner solutions. I think we're stuck between:

suggest the Header Search Paths modification
add a "framework mode" to the service generation tool

@thomasvl, do you think this case is worth adding a framework mode to the tool? I don't think this will affect Objective-C users, just Swift users generating their own services.

Hm, if it is Swift only, does that mean we can't make the Pod auto define things to use the namespaced import?  i.e. - would that break for the ObjC developer?

@thomasvl Are you planning to add --gtlrFrameworkName flag in RPC as well?

I wasn't planning on it since per the note on the main README.md, folks really should be moving to REST based library instead of this one.

Sorry, I missed that note.

By the way the pod mentioned with the flag is 'GoogleApiClient', I guess it would better be 'GoogleApiClientForRest'

Oops, thanks.


Provide .apk releases for beta-testing

When there is something you want feedback on of course ;)

Sure, you can run it now directly on your computer since it uses Godot game engine. I’ll have to investigate how to export for android.
Currently the whole "game" loop works as in you can start the game, start the game and play the first level. But a lot more is required to make the game fun (restore the data, save the data, etc).
I’ll keep this ticket open so I can close it when I release the binaries and APK


Improve gazudouin behavior

Fixes #<issue_number_goes_here>

It's a good idea to open an issue first for discussion.

[ ] Tests pass
[ ] Appropriate changes to README are included in PR

gracias


Error when publishing content: error: Meilisearch could not add entry with id: 18: Transaction query already complete, run with DEBUG=knex:tx for more info.

Description
I'm doing a strapi 5 fresh install and our application relies on meilisearch for a lot of content types.
After i want to publish new content, the following appears in the logs:
2024-12-28 18:04:20.792] info: A task to delete one document from the Meilisearch index "dev_foundation_v5" has been enqueued (Task uid: 11815).
[2024-12-28 18:04:20.831] info: A task to delete 1 documents of the index "dev_foundation_v5" in Meilisearch has been enqueued (Task uid: 11816).
[2024-12-28 18:04:20.847] error: Meilisearch could not add entry with id: 36: Transaction query already complete, run with DEBUG=knex:tx for more info
The entry is not indexing into the meilisearch instance.
My meilisearch plugin screen is added as a screenshot. I can query the index successfully via a REST client, but it has no documents.
We had no problem using this plugin with Strapi 4. Since we are starting with new projects after the holidays, i'm curious if this can be fixed or identified. Will also look into the meilisearch package myself.
Expected behavior
After publish a content-type, it needs to be indexing correctly.
Current behavior
After a save, it gives the following error message:
error: Meilisearch could not add entry with id: 36: Transaction query already complete, run with DEBUG=knex:tx for more info
When digging into the code, there is no check for published content? The new document service of strapi is currently default to draft, but you want to use the published one.
Screenshots or Logs

Environment (please complete the following information):

OS: MacOS 15.2 (24C101)
Meilisearch version:   "pkgVersion": "1.8.1"
strapi-plugin-meilisearch version: 0.13.1
Strapi version: 5.6.0

Debugged the node_modules package, dist -> server -> index.js file.
There are two functions break for me.
On line 950, the getCredentials doesnt work.
If i return a hardcoded object instead of the current logic, it works, otherwise it breaks. Strangely I logged the results of:
 const apiKey = await this.getApiKey();
 const host = await this.getHost();
 const ApiKeyIsFromConfigFile = !!await this.getApiKeyIsFromConfigFile()  false;
 const HostIsFromConfigFile = !!await this.getHostIsFromConfigFile()  false;
 return { apiKey, host, ApiKeyIsFromConfigFile, HostIsFromConfigFile };

And those are all correct, i just hardcoded them.
And also need to  comment out the following in index.js line 1629:
await store2.addIndexedContentType({ contentType: contentType2 });
After those 2 changes it works

Did some more digging ;)
Changed the afterCreate functionality to beforeCreate and some minor changes to the getEntry functionality so its gets the published one. It now works with my custom transform function inside plugins.ts and also with the Credentials function.
Only function which still breaks the code is:
addIndexedContentType in the addEntriesToMeilisearch function.


Add stdlib docs

These docs are missing on the site, would you accept a PR adding them?
https://reasonml.github.io/api/index

Hey,
Thanks for the report.
Let me give you a quick overview of what modules docs we would accept:

Pervasives ...  but some functionality in there is actually not recommended for usage, e.g. string_of_int (vs. Belt.Int.toString), etc.

Following modules will not be accepted for following reasons:

Array ... use Js.Array / Belt.Array instead
List, ListLabels ... use Belt.List instead
String or even Str ... use Js.String instead
Set ... use Belt.Set (+ its variants) instead
No Bytes,  Buffer, Callback, Digest, Complex, Filename, NativeInt, Stream, Random, Scanf, Sys, Unix. Those are platform dependent and probably won't compile (or at least not nicely) on JS and are too native oriented
Stack ... use Belt.MutableStack instead
Sort ... use Belt.SortArray instead (besides, Sort is even deprecated in OCaml)
No Docstrings, GenLex, Lexer, Lexing, Location, Longident, Parse, Parser, Parsetree, Pprintast, Printast. These are literally compiler building modules, we don't expose that to our users.
No Oo.. ReScript doesn't expose object related syntax features
No Obj... this one is a little weird, since it shouldn't be used by any users, not even Obj.magic
No Gc... doesn't look like something we want to expose to JS users
Hashtbl ... use Belt.HashMap (+ variants) instead
No CamlinternalFormat, CamlinternalLazy, CamlinternalMod, CamlinternalOO, ... those are internal and probably not useful for our JS users

For OCamlers who still need to use the OCaml related libraries, it's probably better to refer to the actual OCaml 4.06 docs instead. We care mostly about the JS target here, so we recommend our JS optimised modules (which are also partly adapted OCaml stdlib modules). It's most likely also easier to read for them since they are using OCaml syntax.
Following modules I am not sure, but for now it's not accepted:

Queue .. no idea on how useful this is for JS compilation and if it's optimized for JS usage
Bigarray, Int32 / Int64 .. not sure about those.. we should probably offer a Belt.BigInt at some point
Num ... not sure if this translates to JS
Syntaxerr... not sure if useful for JS context
Weak... not sure if it translates to JS
Printexn .. not sure about this one, probably not equivalent to Js.Exn
Arg ... not sure if useful for JS (we have better alternatives in the JS ecosystem)

Hope this makes sense.
Would be happy to review a PR adding Pervasives, or the Node module (located in the rescript compiler).

Thank you for the explanations. AFAIK Num is dependent on C bindings so it wouldn't translate anyway (and anyway for big numbers Zarith is recommended and there is a bs-zarith port).
It would make sense to put the above explanations in a documentation page(s) in the API docs section, so that it was more discoverable.

It would make sense to put the above explanations in a documentation page(s) in the API docs section, so that it was more discoverable.

Probably good to have on the API overview page, right when you enter the API docs for now?

It would make sense to put the above explanations in a documentation page(s) in the API docs section, so that it was more discoverable.

Probably good to have on the API overview page, right when you enter the API docs for now?

This is superseded by Core which is automatically generated. Everything that is not in Core (or Belt or Js) won't be documented anymore anyways.


Switch bit.dev dependency install system

Pull Request
Description
In this PR I've migrated to using yarn to incorporate bit dependencies. Tailwind with bit just doesn't seem to work on tailwindcss 3, so we'll be using it mostly for config sharing and icon/logo sharing (we're already using it, this just keeps this repo up to date with what's on the bit cloud, note the version bumps for components.).
I also removed the source for the bit component that was still in the repo (layout header). I'm not sure the best practice here, but I think just leaving the source on bit cloud for now won't be much of a problem since there won't be frequent changes to the icons and logo.
To update any of the components, one can just bit import them and push new snapped changes.
I can also replace instances of the source components in this repo to use the bit versions (remove source from this repo and install from bit.dev), like this one for example:
https://github.com/openclimatefix/nowcasting/blob/80e7511aeea799cc4103e93ee84a198acc9e0947/apps/nowcasting-app/components/icons/icons.tsx#L16
Also: it's been a while since I've looked into the monorepo setup, so my additions to the root yarn.lock might be unnecessary. Let me know and I can revert that.
How Has This Been Tested?
Currently these bit dependencies are available on the bit cloud, and installed in pv-sites-mobile.
Checklist:

[x] My code follows OCF's coding style guidelines
[x] I have performed a self-review of my own code
[x] I have made corresponding changes to the documentation
[ ] I have added tests that prove my fix is effective or that my feature works
[x] I have checked my code and corrected any misspellings

@braddf this all good?

@braddf, so this code hasn't gone into another branch in any way, but the code here is the most recent version that I've sent up to the bit cloud with all the components. Additionally, I removed all components stored in bit cloud from this repo to reduce clutter, and they can be added back if necessary (to edit them). Merging this PR won't affect what's in bit cloud (since it's already there), it will just, hopefully, reduce clutter in the repo.


[Bug/Library bitwise mode] build_expression consumes end token in ALTER values

The code snippet
packedMessage = packedMessage << 8;
packedMessage = packedMessage | m[byte];

will not compile with the error
Error: Expected '<end>', got '='

Thanks to allmesi on discord for finding the bug

Upon some further investigation it seems like build_expression adds the second identifier to the expression, while it is not supposed to
[core/src/parser.rs:492] &expr = [
    SYMBOL(
        "bit.lshift",
    ),
    CALL(
        [
            [
                IDENT {
                    expr: [
                        SYMBOL(
                            "packedMessage",
                        ),
                    ],
                    line: 1,
                },
            ],
            [
                SYMBOL(
                    "8",
                ),
            ],
        ],
    ),
    IDENT {
        expr: [
            SYMBOL(
                "packedMessage",
            ),
        ],
        line: 2,
    },
]

this bug might be have been fixed, I'll close it if so


Implement real world testing by Nov 1

Overview: https://docs.google.com/document/d/12DiK3Yx1dJMuIjuiQVATIX5n-2HmdItYNUwTvOecSUA/edit
https://www.medplum.com/docs/compliance/onc#real-world-testing

https://www.medplum.com/docs/compliance/onc


have a look at Windows builds

Checklist

[x] Used a personal fork of the feedstock to propose changes
[ ] Bumped the build number (if the version is unchanged)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[x] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender

looking good. I will merge this in together with one of the upcoming version updates after the dependency update migration PRs


Retire TopLevelDescribe

Why?

it was slow https://github.com/rubocop-hq/rubocop-rspec/pull/925#discussion_r436988718
it ignored non-describe top-level example groups https://github.com/rubocop-hq/rubocop-rspec/pull/925#issuecomment-641140259

TopLevelGroup is a modern replacement for TopLevelDescribe.
Examples how to migrate cops from TopLevelDescribe to TopLevelGroup:

https://github.com/rubocop-hq/rubocop-rspec/pull/932
https://github.com/rubocop-hq/rubocop-rspec/pull/977

Before submitting the PR make sure the following are checked:

[ ] Rebase when #977 is merged
[x] Feature branch is up-to-date with master (if not - rebase it).
[x] Squashed related commits together.
[x] Added tests.
[x] Updated documentation.
[x] Added an entry to the CHANGELOG.md if the new code introduces user-observable changes.
[x] The build (bundle exec rake) passes (be sure to run this locally, since it may produce updated documentation that you will need to commit).

Not much to review. Atop of #977 there's one commit that removes the TopLevelDescribe class and a require line for it.

I'll rebase this one.


Vitest doesn't ignore webstorm / vscode folders

Describe the bug
The runner doesn't ignore the .idea folder.
The defalt value mentioned by the documentation (['/node_modules/', '/dist/']) is wrong. if I'm setting this value - the runner crashes after the first run.
Reproduction
The defalt value mentioned by the documentation (['/node_modules/', '/dist/']) is wrong. if I'm setting this value - the runner crashes after the first run.
System Info
System:
    OS: macOS 12.1
    CPU: (12) x64 Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
    Memory: 316.45 MB / 16.00 GB
    Shell: 5.8 - /bin/zsh
  Binaries:
    Node: 14.17.0 - ~/.nvm/versions/node/v14.17.0/bin/node
    Yarn: 1.22.4 - /usr/local/bin/yarn
    npm: 7.13.0 - ~/.nvm/versions/node/v14.17.0/bin/npm
    Watchman: 2<IP_ADDRESS> - /usr/local/bin/watchman
  Browsers:
    Chrome: 96.0.4664.110
    Firefox: 57.0.4
    Safari: 15.2
  npmPackages:
    @vitejs/plugin-vue: ^2.0.0 => 2.0.1
    vite: ^2.7.2 => 2.7.10
    vitest: ^0.0.131 => 0.0.131

Used Package Manager
npm
Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Check that this is a concrete bug. For Q&A open a GitHub Discussion or join our Discord Chat Server.
[X] The provided reproduction is a minimal reproducible example of the bug.

What file under .idea caused the crash? Can you provide more info?

Workspaces.xml

Could you post a log of the crash?
I'm using Vitest and Webstorm together without any issues.

it's not crashing, it's just re-run the tests when my workspace.xml is changing (which is happening every time webstorm is calculating everything..)

I will need a minimal reproduction repo.

https://github.com/davidmeirlevy/demo-vue-vitest
Run it on Webstorm in order to create the .idea folder.

The defalt value mentioned by the documentation (['/node_modules/', '/dist/']) is wrong. if I'm setting this value - the runner crashes after the first run.

I guess the docs are wrong, since default value is this right now:
[
  '**/node_modules/**',
  '**/dist/**',
  '**/cypress/**',
  '**/.{idea,git,cache,output,temp}/**'
]

Maybe we need to update docs

@sheremet-va i think that the best approach is to ignore everything that is mentioned at the gitignore file.

Ignoring watching all files in .gitignore will not work for everyone. I saw multiple projects that have tests importing code from the dist folder.


Do not hide user provided network mounts [v2]

Prevent the docker daemon from mounting the created network files over
those provided by the user via -v command line option. This would otherwise
hide the one provide by the user.
The benefit of this is that a user can provide these network files using the
-v command line option and place them in a size-limited filesystem.

Please sign your commits following these rules:
https://github.com/docker/docker/blob/master/CONTRIBUTING.md#sign-your-work
The easiest way to do this is to amend the last commit:
$ git clone -b "nohidevols2" git@github.com:stefanberger/docker.git somewhere
$ cd somewhere
$ git commit --amend -s --no-edit
$ git push -f

Ammending updates the existing PR. You DO NOT need to open a new one.


Deployment error, Nodejs/React, deployment source local git

Repro steps:

1.Deploying Nodejs/React webapp to azure linux
2.
Action: appService.Deploy
Error type: Error
Error Message: getaddrinfo ENOTFOUND XXX.scm.azurewebsites.net XXX.scm.azurewebsites.net:443
Version: 0.15.0
OS: win32
Product: Visual Studio Code
Product Version: 1.36.1
Language: en

Call Stack
Object.<anonymous> extension.bundle.js:332:350604
a extension.bundle.js:332:350244
process._tickCallback next_tick.js:68:7

Hi @Kelpieracer
Thanks for reporting this issue.
Is this issue recurring?
And is this a new app?
I've seen this error occurring if people are using a proxy. You might have to configure a custom domain.

Hi, I haven't received this error again (but I have only deployed once after receiving this error).

Forgot... yes this is a new app. I'm not sure if it was the first deployment. Possibly.

@Kelpieracer Okay, I'll keep monitoring this.  Let me know if you run into this issue again.


Multi-bar label type percent?

I looked through the source and noticed it didn't have a label type. Is there a way to make percentage label type for multi bar charts and disable the decimal point?
Also, is there a way to actually show the value in the bar on a stacked bar chart?
Great work on this library! Thanks in advance!

how to display values(x,y) on the line chart graph using NVD3.. directly on the line chart i need to display ?? if possible reply me ...

Its straight forward
add .showValues(true) in you code