text:
Unit 8 Part 2! Error:-Cannot build wheels for Vizdoom, issue in setup.py

The code is originally from Huggingface Deep RL Unit 8 Part 2, there seems to be an issue in the subprocess perhaps something the developers should look at! basically the error is:- Cannot build wheels for Vizdoom, issue in setup.py.
(Note:- I tried many things to solve this issue, at one point I thought I've probably installed some unknown library/dependency by accident, so I decided to try on from scratch in a completely different laptop with different email/username in colab without editing the code one bit but I got the same error, but in my original laptop the first time i ran it, this piece of code had run without a hitch, with vizdoom getting installed)
More details given below:-
Full Error message running this piece of code for huggingface Deep RL Unit 8 Part 2:-
install python libraries
thanks toinsson
!pip install sample-factory==2.0.2
!pip install faster-fifo==1.4.2
!pip install vizdoom
The entire error message is as below:-
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting sample-factory==2.0.2
Downloading sample_factory-2.0.2-py3-none-any.whl (9.0 MB)
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Collecting faster-fifo<2.0,>=1.4.2
Downloading faster-fifo-1.4.5.tar.gz (87 kB)
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Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Collecting pyglet
Downloading pyglet-2.0.5-py3-none-any.whl (831 kB)
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Requirement already satisfied: tensorboard>=1.15.0 in /usr/local/lib/python3.9/dist-packages (from sample-factory==2.0.2) (2.12.2)
Requirement already satisfied: psutil>=5.7.0 in /usr/local/lib/python3.9/dist-packages (from sample-factory==2.0.2) (5.9.5)
Collecting colorlog
Downloading colorlog-6.7.0-py2.py3-none-any.whl (11 kB)
Requirement already satisfied: filelock in /usr/local/lib/python3.9/dist-packages (from sample-factory==2.0.2) (3.11.0)
Collecting signal-slot-mp<2.0,>=1.0.3
Downloading signal_slot_mp-1.0.3-py3-none-any.whl (11 kB)
Collecting tensorboardx>=2.0
Downloading tensorboardX-2.6-py2.py3-none-any.whl (114 kB)
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Collecting torch<2.0,>=1.9
Downloading torch-1.13.1-cp39-cp39-manylinux1_x86_64.whl (887.4 MB)
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Collecting wandb>=0.12.9
Downloading wandb-0.15.0-py3-none-any.whl (2.0 MB)
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Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.9/dist-packages (from sample-factory==2.0.2) (3.1.0)
Collecting gym<1.0,>=0.26.1
Downloading gym-0.26.2.tar.gz (721 kB)
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Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Collecting huggingface-hub<1.0,>=0.10.0
Downloading huggingface_hub-0.13.4-py3-none-any.whl (200 kB)
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Requirement already satisfied: numpy>=1.18.1<2.0 in /usr/local/lib/python3.9/dist-packages (from sample-factory==2.0.2) (1.22.4)
Requirement already satisfied: opencv-python in /usr/local/lib/python3.9/dist-packages (from sample-factory==2.0.2) (4.7.0.72)
Requirement already satisfied: cython>=0.29 in /usr/local/lib/python3.9/dist-packages (from faster-fifo<2.0,>=1.4.2->sample-factory==2.0.2) (0.29.34)
Requirement already satisfied: setuptools>=45.2.0 in /usr/local/lib/python3.9/dist-packages (from faster-fifo<2.0,>=1.4.2->sample-factory==2.0.2) (67.6.1)
Requirement already satisfied: cloudpickle>=1.2.0 in /usr/local/lib/python3.9/dist-packages (from gym<1.0,>=0.26.1->sample-factory==2.0.2) (2.2.1)
Requirement already satisfied: importlib-metadata>=4.8.0 in /usr/local/lib/python3.9/dist-packages (from gym<1.0,>=0.26.1->sample-factory==2.0.2) (6.4.1)
Requirement already satisfied: gym-notices>=0.0.4 in /usr/local/lib/python3.9/dist-packages (from gym<1.0,>=0.26.1->sample-factory==2.0.2) (0.0.8)
Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.9/dist-packages (from huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (23.1)
Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.9/dist-packages (from huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (4.5.0)
Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (2.27.1)
Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.9/dist-packages (from huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (4.65.0)
Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.9/dist-packages (from huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (6.0)
Requirement already satisfied: grpcio>=1.48.2 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (1.53.0)
Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (0.7.0)
Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (2.17.3)
Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (0.40.0)
Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (1.4.0)
Requirement already satisfied: google-auth-oauthlib<1.1,>=0.5 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (1.0.0)
Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (1.8.1)
Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (3.4.3)
Requirement already satisfied: protobuf>=3.19.6 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (3.20.3)
Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from tensorboard>=1.15.0->sample-factory==2.0.2) (2.2.3)
Collecting nvidia-cublas-cu11==11.10.3.66
Downloading nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl (317.1 MB)
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Collecting nvidia-cudnn-cu11==8.5.0.96
Downloading nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl (557.1 MB)
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Collecting nvidia-cuda-runtime-cu11==11.7.99
Downloading nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB)
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Collecting nvidia-cuda-nvrtc-cu11==11.7.99
Downloading nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB)
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Collecting docker-pycreds>=0.4.0
Downloading docker_pycreds-0.4.0-py2.py3-none-any.whl (9.0 kB)
Collecting pathtools
Downloading pathtools-0.1.2.tar.gz (11 kB)
Preparing metadata (setup.py) ... done
Requirement already satisfied: appdirs>=1.4.3 in /usr/local/lib/python3.9/dist-packages (from wandb>=0.12.9->sample-factory==2.0.2) (1.4.4)
Collecting sentry-sdk>=1.0.0
Downloading sentry_sdk-1.20.0-py2.py3-none-any.whl (198 kB)
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Collecting setproctitle
Downloading setproctitle-1.3.2-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (30 kB)
Requirement already satisfied: Click!=8.0.0,>=7.0 in /usr/local/lib/python3.9/dist-packages (from wandb>=0.12.9->sample-factory==2.0.2) (8.1.3)
Collecting GitPython!=3.1.29,>=1.0.0
Downloading GitPython-3.1.31-py3-none-any.whl (184 kB)
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Requirement already satisfied: six>=1.4.0 in /usr/local/lib/python3.9/dist-packages (from docker-pycreds>=0.4.0->wandb>=0.12.9->sample-factory==2.0.2) (1.16.0)
Collecting gitdb<5,>=4.0.1
Downloading gitdb-4.0.10-py3-none-any.whl (62 kB)
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Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.9/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=1.15.0->sample-factory==2.0.2) (0.2.8)
Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.9/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=1.15.0->sample-factory==2.0.2) (4.9)
Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.9/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=1.15.0->sample-factory==2.0.2) (5.3.0)
Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.9/dist-packages (from google-auth-oauthlib<1.1,>=0.5->tensorboard>=1.15.0->sample-factory==2.0.2) (1.3.1)
Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.9/dist-packages (from importlib-metadata>=4.8.0->gym<1.0,>=0.26.1->sample-factory==2.0.2) (3.15.0)
Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (3.4)
Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (2022.12.7)
Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (2.0.12)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface-hub<1.0,>=0.10.0->sample-factory==2.0.2) (1.26.15)
Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.9/dist-packages (from werkzeug>=1.0.1->tensorboard>=1.15.0->sample-factory==2.0.2) (2.1.2)
Collecting smmap<6,>=3.0.1
Downloading smmap-5.0.0-py3-none-any.whl (24 kB)
Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.9/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard>=1.15.0->sample-factory==2.0.2) (0.4.8)
Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.9/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<1.1,>=0.5->tensorboard>=1.15.0->sample-factory==2.0.2) (3.2.2)
Building wheels for collected packages: faster-fifo, gym, pathtools
Building wheel for faster-fifo (pyproject.toml) ... done
Created wheel for faster-fifo: filename=faster_fifo-1.4.5-cp39-cp39-linux_x86_64.whl size=356657 sha256=ccb3de132617e5f61e121e7bd358832bc48739f8b456e2708bcadd8e67c67441
Stored in directory: /root/.cache/pip/wheels/9f/2c/8f/2a67c7cefc7551a4dc9de521a298836583f9946b6b50d7e696
Building wheel for gym (pyproject.toml) ... done
Created wheel for gym: filename=gym-0.26.2-py3-none-any.whl size=827653 sha256=87a39e558b0426cdd265f0107ada1d6d69953f0f3c55c9fff3c92747b1aa5364
Stored in directory: /root/.cache/pip/wheels/af/2b/30/5e78b8b9599f2a2286a582b8da80594f654bf0e18d825a4405
Building wheel for pathtools (setup.py) ... done
Created wheel for pathtools: filename=pathtools-0.1.2-py3-none-any.whl size=8807 sha256=d98d78d3810ff1ae74df5f02a3b9f1904d7a27b09452e009c36fd148ab07cc5d
Stored in directory: /root/.cache/pip/wheels/b7/0a/67/ada2a22079218c75a88361c0782855cc72aebc4d18d0289d05
Successfully built faster-fifo gym pathtools
Installing collected packages: pyglet, pathtools, tensorboardx, smmap, setproctitle, sentry-sdk, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cublas-cu11, faster-fifo, docker-pycreds, colorlog, signal-slot-mp, nvidia-cudnn-cu11, huggingface-hub, gym, gitdb, torch, GitPython, wandb, sample-factory
Attempting uninstall: gym
Found existing installation: gym 0.25.2
Uninstalling gym-0.25.2:
Successfully uninstalled gym-0.25.2
Attempting uninstall: torch
Found existing installation: torch 2.0.0+cu118
Uninstalling torch-2.0.0+cu118:
Successfully uninstalled torch-2.0.0+cu118
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
torchvision 0.15.1+cu118 requires torch==2.0.0, but you have torch 1.13.1 which is incompatible.
torchtext 0.15.1 requires torch==2.0.0, but you have torch 1.13.1 which is incompatible.
torchdata 0.6.0 requires torch==2.0.0, but you have torch 1.13.1 which is incompatible.
torchaudio 2.0.1+cu118 requires torch==2.0.0, but you have torch 1.13.1 which is incompatible.
dopamine-rl 4.0.6 requires gym<=0.25.2, but you have gym 0.26.2 which is incompatible.
Successfully installed GitPython-3.1.31 colorlog-6.7.0 docker-pycreds-0.4.0 faster-fifo-1.4.5 gitdb-4.0.10 gym-0.26.2 huggingface-hub-0.13.4 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 pathtools-0.1.2 pyglet-2.0.5 sample-factory-2.0.2 sentry-sdk-1.20.0 setproctitle-1.3.2 signal-slot-mp-1.0.3 smmap-5.0.0 tensorboardx-2.6 torch-1.13.1 wandb-0.15.0
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting faster-fifo==1.4.2
Downloading faster-fifo-1.4.2.tar.gz (84 kB)
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Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Requirement already satisfied: cython>=0.29 in /usr/local/lib/python3.9/dist-packages (from faster-fifo==1.4.2) (0.29.34)
Requirement already satisfied: setuptools>=45.2.0 in /usr/local/lib/python3.9/dist-packages (from faster-fifo==1.4.2) (67.6.1)
Building wheels for collected packages: faster-fifo
Building wheel for faster-fifo (pyproject.toml) ... done
Created wheel for faster-fifo: filename=faster_fifo-1.4.2-cp39-cp39-linux_x86_64.whl size=346504 sha256=c04e200411a2a431e46318231f3959a9dc7bf3821b8a5b36279e7a31b2ca124a
Stored in directory: /root/.cache/pip/wheels/0c/6e/e5/093da430960f5d651cd6e13cb1fe7424ad422887c9ca0d376f
Successfully built faster-fifo
Installing collected packages: faster-fifo
Attempting uninstall: faster-fifo
Found existing installation: faster-fifo 1.4.5
Uninstalling faster-fifo-1.4.5:
Successfully uninstalled faster-fifo-1.4.5
Successfully installed faster-fifo-1.4.2
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting vizdoom
Downloading vizdoom-1.1.14.tar.gz (15.7 MB)
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Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Requirement already satisfied: numpy in /usr/local/lib/python3.9/dist-packages (from vizdoom) (1.22.4)
Building wheels for collected packages: vizdoom
error: subprocess-exited-with-error
× Building wheel for vizdoom (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
Building wheel for vizdoom (pyproject.toml) ... error
ERROR: Failed building wheel for vizdoom
Failed to build vizdoom
ERROR: Could not build wheels for vizdoom, which is required to install pyproject.toml-based projects

I solved the problem by executing the below two lines before any dependency installation.
Then I removed the last pip install vizdoom.
!apt-get install cmake git libboost-all-dev libsdl2-dev libopenal-dev
!pip install vizdoom

This is the original installation guide from vizdoom repo (link)
I hope this could help you too.

so did you do it in linux or windows?

Hey there I just tested the notebook and I don't have the error did you run it on colab or it was on your machine?

The error occurs on colab.

I don't see the issue anymore I'm closing it for now. Don't hesitate to open it again if you encounter this issue again 🤗

repo: huggingface/deep-rl-class


text:
400: Bad Request when accessing a space

Describe the bug
Hi everyone,
When I try to get the space runtime or space info with:
runtime = api.get_space_runtime(space.id, token=ACCESS_TOKEN)
space_info = api.repo_info(space.id, repo_type="space")

It throws a huggingface_hub.utils._errors.BadRequestError with a body:
"""
Bad request:
"metadata" is required
"""
I have checked on the website that the repositories that throw this error also show a 400 bad request in the website (check here). It happened to a few repositories, I can share the list.
On the other side, I tried to catch the huggingface_hub.utils._errors.BadRequestError with:
from huggingface_hub.utils._errors import BadRequestError
try:
....
except BadRequestError as badreq_err:
....

but it doesn't catch the exception. Am I properly importing the error? Is it because it throws an HTTPError instead of BadRequestError?
Reproduction
from huggingface_hub import HfApi
api = HfApi()
space_id = "WitchHuntTV/WinnieThePoohSVC_sovits4"
runtime = api.get_space_runtime(space_id)
Logs
---------------------------------------------------------------------------
HTTPError                                 Traceback (most recent call last)
File ~/anaconda3/envs/hf/lib/python3.9/site-packages/huggingface_hub/utils/_errors.py:304, in hf_raise_for_status(response, endpoint_name)
    303 try:
--> 304     response.raise_for_status()
    305 except HTTPError as e:

File ~/anaconda3/envs/hf/lib/python3.9/site-packages/requests/models.py:1021, in Response.raise_for_status(self)
   1020 if http_error_msg:
-> 1021     raise HTTPError(http_error_msg, response=self)

HTTPError: 400 Client Error: Bad Request for url: https://huggingface.co/api/spaces/WitchHuntTV/WinnieThePoohSVC_sovits4/runtime

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

BadRequestError                           Traceback (most recent call last)
Cell In[4], line 6
      3 api = HfApi()
      4 space_id = "WitchHuntTV/WinnieThePoohSVC_sovits4"
----> 6 runtime = api.get_space_runtime(space_id)

File ~/anaconda3/envs/hf/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    111 if check_use_auth_token:
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)
...

BadRequestError:  (Request ID: Root=1-667e4ffb-30383f4f289a640224913112;012d2be1-3365-4977-b710-e110f2154801)

Bad request:
"metadata" is required

System info
- huggingface_hub version: 0.23.4
- Platform: Linux-6.2.16-4-pve-x86_64-with-glibc2.28
- Python version: 3.9.12
- Running in iPython ?: Yes
- iPython shell: ZMQInteractiveShell
- Running in notebook ?: Yes
- Running in Google Colab ?: No
- Token path ?: /root/.cache/huggingface/token
- Has saved token ?: False
- Configured git credential helpers:
- FastAI: N/A
- Tensorflow: N/A
- Torch: N/A
- Jinja2: 3.1.2
- Graphviz: N/A
- keras: N/A
- Pydot: N/A
- Pillow: N/A
- hf_transfer: N/A
- gradio: N/A
- tensorboard: N/A
- numpy: N/A
- pydantic: N/A
- aiohttp: N/A
- ENDPOINT: https://huggingface.co
- HF_HUB_CACHE: /root/.cache/huggingface/hub
- HF_ASSETS_CACHE: /root/.cache/huggingface/assets
- HF_TOKEN_PATH: /root/.cache/huggingface/token
- HF_HUB_OFFLINE: False
- HF_HUB_DISABLE_TELEMETRY: False
- HF_HUB_DISABLE_PROGRESS_BARS: None
- HF_HUB_DISABLE_SYMLINKS_WARNING: False
- HF_HUB_DISABLE_EXPERIMENTAL_WARNING: False
- HF_HUB_DISABLE_IMPLICIT_TOKEN: False
- HF_HUB_ENABLE_HF_TRANSFER: False
- HF_HUB_ETAG_TIMEOUT: 10
- HF_HUB_DOWNLOAD_TIMEOUT: 10

Hi @ademait, thanks for reporting! This Space has been disabled by an admin, which created some side effect on the API. This should now be fixed (at least gives more explicit error). See:

https://huggingface.co/spaces/WitchHuntTV/WinnieThePoohSVC_sovits4
https://huggingface.co/api/spaces/WitchHuntTV/WinnieThePoohSVC_sovits4
https://huggingface.co/api/spaces/WitchHuntTV/WinnieThePoohSVC_sovits4/runtime

Btw, it's best to catch huggingface_hub.utils._errors.HfHubHTTPError is this case. It's a subclass of HTTPError with more precise information. It's raised by huggingface_hub.urils.hf_raise_for_status.

Hi @Wauplin , thank you for the fast reply! I have found another spaces with the same issues, I could share the names here

Hi @ademait, that would be helpful if you could yes. Thanks in advance!

Hi @Wauplin , the spaces that gave me the very same error are: "qandeelfatima/ImageToText", "lunarflu/test2","fastaioncampus/Classificador-de-carros","xzkqaq/1". I hope it helps 😄  Thank you for addressing the issue so fast!

Thanks @ademait! Seems like we can correctly retrieve runtime for all 4 Spaces now so all good :)

source: gharchive/issue

authors: Wauplin ademait

license_type: permissive

license_source: bigquery


text:
True OpenAI drop-in replacement by InferenceClient

Closes https://github.com/huggingface/huggingface_hub/issues/2369 @lappemic
Goal is to be able to use InferenceClient exactly the same way as OpenAI client. To do so we need to:

[x] rename model to base_url => added an alias for it
[x] rename model_id to model
[x] rename token to api_key => added an alias for it
[x] add alias for client.chat.completions.create

@philschmid could you have a look at it and confirm it meets your expectations? See tests for real example (here and here)
Sync + stream=False
client = InferenceClient(
    base_url="https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct",
    api_key="my-api-key",
)
output = client.chat.completions.create(
    model="meta-llama/Meta-Llama-3-8B-Instruct",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Count to 10"},
    ],
    stream=False,
    max_tokens=1024,
)
assert output.choices[0].message.content == "1, 2, 3, 4, 5, 6, 7, 8, 9, 10!"

Sync + stream=True
client = InferenceClient()
output = client.chat.completions.create(
    model="meta-llama/Meta-Llama-3-8B-Instruct",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Count to 10"},
    ],
    stream=True,
    max_tokens=1024,
)

for chunk in output:
    print(chunk.choices[0].delta.content)

Async + stream=False
    client = AsyncInferenceClient(
        base_url="https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct",
        api_key="my-api-key",
    )
    output = await client.chat.completions.create(
        model="meta-llama/Meta-Llama-3-8B-Instruct",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "Count to 10"},
        ],
        stream=False,
        max_tokens=1024,
    )
    assert output.choices[0].message.content == "1, 2, 3, 4, 5, 6, 7, 8, 9, 10!"

Async + stream=True
client = AsyncInferenceClient()
output = await client.chat.completions.create(
    model="meta-llama/Meta-Llama-3-8B-Instruct",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Count to 10"},
    ],
    stream=True,
    max_tokens=1024,
)

chunked_text = [chunk.choices[0].delta.content async for chunk in output]

TODO:

[x] document this properly (see inference.md)

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

@philschmid could you have a look at it and confirm it meets your expectations?

from experience, a very tough test to pass usually 🤣

Thanks for the reviews!

source: gharchive/pull-request


text:
Zero scores on cnn-dm benchmark from HELM

When running the evaluation of Sheared-LLaMA-1.3B and original LLaMA-7B on helm|summarization:cnn-dm, I get zero scores:
accelerate launch --multi_gpu --num_processes=3 run_evals_accelerate.py --model_args "pr
etrained=princeton-nlp/Sheared-LLaMA-1.3B,model_parallel=True" --task "helm|summarization:cnn-dm|0|0" --override_batch_size 1 --out
put_dir "./evals/"

Output:
|           Task            |Version|         Metric          |Value|   |Stderr|
|---------------------------|------:|-------------------------|----:|---|-----:|
|all                        |       |rouge1                   |    0|±  |     0|
|                           |       |rouge2                   |    0|±  |     0|
|                           |       |rougeL                   |    0|±  |     0|
|                           |       |summac                   |    0|±  |     0|
|                           |       |summarization_coverage   |    0|±  |     0|
|                           |       |summarization_density    |    0|±  |     0|
|                           |       |summarization_compression|    0|±  |     0|
|helm:summarization:cnn-dm:0|      0|rouge1                   |    0|±  |     0|
|                           |       |rouge2                   |    0|±  |     0|
|                           |       |rougeL                   |    0|±  |     0|
|                           |       |summac                   |    0|±  |     0|
|                           |       |summarization_coverage   |    0|±  |     0|
|                           |       |summarization_density    |    0|±  |     0|
|                           |       |summarization_compression|    0|±  |     0|

Seems to have something to do with task_prompt_formatting
Change the prompt as follows:

instruction="### Instruction: Summarize the following passage in 3 sentences.\n", query=f"### Instruction: Summarize the following passage in 3 sentences.\n### Passage: {line['article']}\n### Summary: ",

And this issue can be fixed

Thanks so much for debugging, would you be OK with opening an issue to share this with the community?

Not sure if it has something to do with the evaluated model itself. When I use another finetuned model, the original code seems to be fine.
Maybe adjusting the task_prompt_formatting ourselves according to requirements is needed.

authors: clefourrier hicleo

repo: huggingface/lighteval

license: MIT

license_source: github-api


text:
[SAM] Split encoder and mask decoder into separate .onnx files

Feature request
Currently, exporting SAM models with optimum results in a single .onnx file (https://huggingface.co/Xenova/sam-vit-base/tree/main/onnx). It would be great if we could add an option to separate the encoder and decoder into separate onnx files (like traditional seq2seq models).
Example SAM exports for which this has been done:

https://huggingface.co/visheratin/segment-anything-vit-b/tree/main
https://huggingface.co/visheratin/segment-anything-vit-l/tree/main
https://huggingface.co/visheratin/segment-anything-vit-h/tree/main

Motivation
The primary motivation for this feature request is to reuse the encoded image (which should only be computed once), and then use the decoder for querying. At the moment, users would have to encode the image each time they wish to perform a query.
This would be great for Transformers.js.
Your contribution
I can integrate this into Transformers.js once it's available.

Just wanted to bump this issue as we've recently got another feature request for this (https://github.com/xenova/transformers.js/issues/163) and I think this could make for an awesome demo application!
cc @michaelbenayoun @fxmarty

How are you splitting encoder and decoder? Have you experimented with it to reuse embedding in the decode pass?

(replying to you here since I don't have other contact info) I probably didn't understand your question clearly yesterday through the noise, but we used the encoder/decoder separately, loading this example inside VS code to accept a custom image and generate the .onnx model and .npy embedding, followed by running this demo app with the decoder .onnx file and generated .npy embedding to map mouse coordinates to the mask.

Hey! 👋

loading this example inside VS code to accept a custom image and generate the .onnx model and .npy embedding

Right, so I guess my question was related to the feasibility of running the encoder in the browser. As you linked to, the original demo only runs the decoder in the browser (inference in <50ms according to their paper), so I was wondering whether you tested running both encoder and decoder in your tests 😊

Josha: I think if the .pth file (at 2.38GB's!) was converted to ONNX with external weights (to overcome the 2GB ProtoBuf limit), then converted to float16, then repacked with the weights back into the ONNX file (since ONNX Runtime for the web doesn't currently support external weights) that it should be possible to run with WebNN. It then becomes a matter of op coverage (I haven't collected the encoder's op list yet though ⏳).

Oh yikes 😅 I think we'll stick with the base and large versions:

model
size (MB)
8-bit quantized size (MB)

base
376
106

large
1250
330

huge
2560
664

Indeed, the base model looks much more feasible sizewise.

@xenova a PR should be coming soon

authors: fdwr fxmarty xenova

repo: huggingface/optimum


text:
Can't load Llama-2-7b-chat-coreml model

After getting SwiftChat to run with falcon-7b (but very very slowly, perhaps 45 minutes per prompt), I tried to load the supported Llama-2-7b-chat-coreml model by selecting the .mlpackage file from the SwiftChat dialog.
SwiftChat throws this error:
2023-08-16 08:56:47.315342-0400 SwiftChat[72086:2980822] +[CATransaction synchronize] called within transaction
2023-08-16 08:56:49.270422-0400 SwiftChat[72086:2980822] [default] CGSWindowShmemCreateWithPort failed on port 0

…and the model does not load, but keeps the falcon-7b model loaded.

Hmm, this seems to have resolved itself. Weird.

repo: huggingface/swift-chat


text:
[ORPO] Correct label mask for pad tokens

Recent fix for calculating NLL loss for a whole sequence introduced a bug. When input_ids are copied to labels, pad tokens are not masked.
This PR aims to patch this by masking labels based on the attention mask.
I've tested it with batch_size=1, and now the initial loss is correct.

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

thanks @IlyaGusev can we replace all the magic -100 by self.label_pad_token_id ?

cc @alvarobartt

Recent fix for calculating NLL loss for a whole sequence introduced a bug. When input_ids are copied to labels, pad tokens are not masked.
This PR aims to patch this by masking labels based on the attention mask.
I've tested it with batch_size=1, and now the initial loss is correct.

@IlyaGusev Hi! With 0.8.6 version of the trainer, losses continue to decrease, but using current trainer losses fluctuate greatly, Is this normal?

@AIR-hl did you try to uncomment out the changes to confirm its because of this?

@AIR-hl did you try to uncomment out the changes to confirm its because of this?

@kashif I did some samll experiments, I tested ORPO with a sft phi1_5 on different versions of trl（v0.8.6, v0.9.3）. For hyperparameters, I only changed the learning rate. I don't the model is bad, because for the DPO the reward accuracy can quickly stabilize at around 0.75

v0.8.6; lr=1e-5

v0.9.3; lr=1e-5

v0.9.3; lr=5e-5

v0.9.3; lr=5e-7

my python script and launch file:
import multiprocessing
from dataclasses import dataclass, field
from typing import Optional, Dict

import torch
from datasets import load_dataset
from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments
from trl import (
    get_kbit_device_map,
    get_quantization_config,
    get_peft_config,
    ModelConfig,
    ORPOTrainer,
    ORPOConfig
)
from trl.commands.cli_utils import TrlParser

@dataclass
class ORPOScriptArguments:
    dataset_name: str = field(default=None, metadata={"help": "the dataset name"})
    dataset_train_split: str = field(default="train", metadata={"help": "The dataset split to use for training"})

if __name__ == "__main__":
    parser = TrlParser((ORPOScriptArguments, ORPOConfig, ModelConfig))
    args, training_args, model_config = parser.parse_args_and_config()

    torch_dtype = (
        model_config.torch_dtype
        if model_config.torch_dtype in ["auto", None]
        else getattr(torch, model_config.torch_dtype)
    )
    quantization_config = get_quantization_config(model_config)

    model_kwargs = dict(
        revision=model_config.model_revision,
        trust_remote_code=model_config.trust_remote_code,
        attn_implementation=model_config.attn_implementation,
        torch_dtype=torch_dtype,
        use_cache=False if training_args.gradient_checkpointing else True,
        device_map=get_kbit_device_map() if quantization_config is not None else None,
        quantization_config=quantization_config,
    )

    model = AutoModelForCausalLM.from_pretrained(model_config.model_name_or_path,
                                                 **model_kwargs)

    tokenizer = AutoTokenizer.from_pretrained(model_config.model_name_or_path)
    if tokenizer.pad_token is None:
        tokenizer.pad_token = tokenizer.eos_token
    tokenizer.padding_side = 'right'

    train_dataset = load_dataset(args.dataset_name,
                                 split=args.dataset_train_split, )
    train_dataset = train_dataset.shuffle(seed=training_args.seed)

    def process(row):
        row["prompt"] = tokenizer.apply_chat_template(row["prompt"], tokenize=False)
        row["chosen"] = tokenizer.apply_chat_template(row["chosen"], tokenize=False)
        row["rejected"] = tokenizer.apply_chat_template(row["rejected"], tokenize=False)
        return row

    train_dataset = train_dataset.map(
        process,
        num_proc=multiprocessing.cpu_count(),
        load_from_cache_file=False,
    )

    trainer = ORPOTrainer(
        model,
        args=training_args,
        train_dataset=train_dataset,
        tokenizer=tokenizer,
        peft_config=get_peft_config(model_config),
    )

    trainer.train()

    trainer.save_model(training_args.output_dir)

python orpo_version.py \
  --attn_implementation flash_attention_2 \
  --beta 0.1 \
  --bf16 \
  --dataset_name autodl-tmp/ultrafeedback-binarized-preferences-cleaned \
  --do_train \
  --gradient_checkpointing \
  --gradient_accumulation_steps 8 \
  --learning_rate 0.00005 \
  --lr_scheduler_type cosine \
  --logging_first_step \
  --logging_steps 5 \
  --max_length 2048 \
  --max_prompt_length 1024 \
  --max_steps -1 \
  --model_name_or_path autodl-tmp/phi-1_5-uc-01 \
  --num_train_epochs 1 \
  --output_dir autodl-tmp/output \
  --per_device_train_batch_size 4 \
  --report_to tensorboard \
  --save_strategy steps \
  --save_steps 200 \
  --save_total_limit 2 \
  --torch_dtype bfloat16 \
  --warmup_steps 20

authors: AIR-hl HuggingFaceDocBuilderDev IlyaGusev kashif

repo: huggingface/trl


text:
MqttAgent, question related to subscription and publish?

Hi,
I have setup a MqttAgent using cloudmqtt. I have 2 questions.

What is the need of setting 'schedule', e.g. 1m, 1d? Shouldn't it be connected all the time for publishing and retrieving data?
How do I publish in the MqttAgent? Should I use payload or message? Could you folks add an example?

{
  "uri": "mqtt://zzz",
  "topic": "/data",
  "payload": "huginn",
  "message": {"test": "huginn"}
  "max_read_time": "10",
  "expected_update_period_in_days": "2"
}

Thank you!

1. What is the need of setting 'schedule', e.g. 1m, 1d? Shouldn't it be connected all the time for publishing and retrieving data?

That would be ideal, yes. However the Agent works by connecting to the server every time it's run, fetches the new data and emits Events for it.

2\. How do I publish in the MqttAgent? Should I use payload or message? Could you folks add an example?

When receiving Events the Agent uses the topic key of the Event payload as the topic and message for the data to publish.

Should it be?
{
  "topic": "/data",
  "payload": "huginn",
}

or
{
  "topic": "/data",
  "message": "huginn"
}

The latter should work.

repo: huginn/huginn

license: mit


text:
How can I get the Hugo default gist shortcode rendering?

Question
Using the gist shortcode with this theme give me undesirable output. There is so much extra space around each line that it is difficult to read (e.g. cannot see much on one screen). Here is a snapshot:
How can I get the default gist shortcode rendering?

We probably need to fix the CSS.

Do you have any idea which file that is? I tried commenting out the codeblocks section in main.css but it had no effect.

I have to check the generated HTML. This is Hugo's internal shortcode. I have to check the classes it produces.

Hi @quantitative-technologies! Fixed in #606. Please, pull the latest changes.

Perfect!

authors: hossainemruz quantitative-technologies

repo: hugo-toha/toha


text:
cannot load SPARQL table

While I am able to retrieve data from a SPARQL endpoint through the Palladio interface, it does not give me the option to then load the table. For example, using the British Museum endpoint http://collection.britishmuseum.org/sparql.json:
SELECT ?type (COUNT(?type) as ?n)
WHERE {
  ?object bmo:PX_object_type ?object_type .
  ?object_type skos:prefLabel ?type .

  ?object ecrm:P108i_was_produced_by ?production .
  ?production ecrm:P9_consists_of ?date_node .
  ?date_node ecrm:P4_has_time-span ?timespan .
  ?timespan ecrm:P82a_begin_of_the_begin ?date .
  FILTER(?date >= "1580-01-01"^^xsd:date && ?date <= "1600-01-01"^^xsd:date)
}
GROUP BY ?type
ORDER BY DESC(?n)

I can preview the results successfully:

However the "Load data" button remains inactive:

Indeed. Thanks for the report! Will get this fixed ASAP - hopefully today.

So, usually Palladio expects SPARQL results in CSV/TSV format. It looks like the British Museum endpoint supports only JSON and XML formats. Is that accurate? Assuming this is the issue, and that it would generally be nice to support JSON result formats, I'm going to have Palladio naively convert the JSON format into a CSV format in the event that the return value is JSON and not a string.

I've bumped the version on http://palladio.designhumanities.org/ to 1.0.1 and loading from this endpoint (or any SPARQL endpoint) in JSON format should now work. Thanks again for reporting the issue. I'm going to close this one. Please go ahead and open a new issue if you run into any other SPARQL issues. It is not a very heavily used part of the application as far as we are aware, so we appreciate you delving into it.

Thanks for following up so quickly on this! I've a few colleagues using this with some different SPARQL endpoints (none of which offer CSV/TSV download!) so I'll report back if we encounter further difficulties.

authors: esjewett mdlincoln

repo: humanitiesplusdesign/palladio


text:
[WIP] Feature/crd humio view

Fixes #207
Changes
Added HumioView CRD
Name and Connections can now be set.
Description is omitted for now as we would need an update to the view api
Controller
Added support for adding, updating and deleting views
Tests performed
I have run all tests via "make test".
I have also spun up a humio cluster via the hack tools and observed the changes to the humio views in the cluster.
Please let me know if anything is missing or should be changed.

I can see that the e2e tests are failing where running make test works.
I will gladly accept some hints on how to proceed 👍

I just had a look at the failing test, it looks like it's failing because the Humio View test tries to create a repository that already exists. We should change the repositoryKey and repositoryToCreate resources to be unique so that it doesn't conflict with the repository test.
Humio Resources Controllers Humio View
  Should handle view correctly
  /home/runner/work/humio-operator/humio-operator/controllers/humioresources_controller_test.go:343
STEP: Creating a shared humio cluster if it doesn't already exist
STEP: Creating the repository successfully

• Failure [0.008 seconds]
Humio Resources Controllers
/home/runner/work/humio-operator/humio-operator/controllers/humioresources_controller_test.go:35
  Humio View
  /home/runner/work/humio-operator/humio-operator/controllers/humioresources_controller_test.go:342
    Should handle view correctly [It]
    /home/runner/work/humio-operator/humio-operator/controllers/humioresources_controller_test.go:343

    Expected success, but got an error:
        <*errors.StatusError | 0xc000f4aa00>: {
            ErrStatus: {
                TypeMeta: {Kind: "", APIVersion: ""},
                ListMeta: {
                    SelfLink: "",
                    ResourceVersion: "",
                    Continue: "",
                    RemainingItemCount: nil,
                },
                Status: "Failure",
                Message: "humiorepositories.core.humio.com \"humiorepository\" already exists",
                Reason: "AlreadyExists",
                Details: {
                    Name: "humiorepository",
                    Group: "core.humio.com",
                    Kind: "humiorepositories",
                    UID: "",
                    Causes: nil,
                    RetryAfterSeconds: 0,
                },
                Code: 409,
            },
        }
        humiorepositories.core.humio.com "humiorepository" already exists

    /home/runner/work/humio-operator/humio-operator/controllers/humioresources_controller_test.go:389

Ah, that should be an easy fix. Will you go ahead or should I @kaspernissen ?

I think I might have it. make test succeeds locally (it also did in the initial version, so no guarantee), let's see if e2e succeeds here as well 🙏

Unfortunately, didn't fix the failing test. We found the issue, which seems to be an addition in the cli package, that now results in the expectation to not match; https://github.com/humio/cli/blame/dea38288df5de0e5e4c52a049207b7322ba1bc4c/api/repositories.go#L15
@mahlunar is working on a fix.

Fixed. The Repository Id was the culprit which failed on assertions. I have added a new struct in the test file that excludes the Id field. Let me know if this is ok.

Rebase done and updated manifests.

authors: Crevil kaspernissen mahlunar

repo: humio/humio-operator


text:
I am confused

This is a WebUI for hummingbot?

No, it is a script to generate UI component for web builders.

Got it, thank you

Hi @Kuchiriel. This repo is a couple of things:

The code that loads design tokens from the HBUI Figma file to generate React components in Hummingbot style and generate the HBUI NPM module
The code for the HBUI documentation site

If you want to use the HBUI design system in a React app you should use the NPM module. This NPM module not only has React components, but also design tokens and assets, which are useful to design apps using the Hummingbot style.
Alternative you can get started with one of the boilerplate projects:
Next.js
Gatsby
Webpack
Webpack (TypeScript)
Let us know if you would like to see a boilerplate project with different specifications.
You can also get design material from the Figma file to create your designs in Hummingbot style.

authors: Kuchiriel antoniobrandao mlguys

repo: hummingbot/hbui


text:
Client - Unhandled error in background task: MAC mismatch after password reset

Describe the bug
While running some test and deleted the .password_verification from ./conf folder to reset password. Client wont start with errorr below:
2023-11-17 22:25:17,430 - hummingbot.core.utils.async_utils - ERROR - Unhandled error in background task: MAC mismatch
Traceback (most recent call last):
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/core/utils/async_utils.py", line 9, in safe_wrapper
    return await c
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/core/utils/async_call_scheduler.py", line 127, in call_async
    return await self.schedule_async_call(coro, timeout_seconds, app_warning_msg=app_warning_msg)
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/core/utils/async_call_scheduler.py", line 116, in schedule_async_call
    return await fut
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/core/utils/async_call_scheduler.py", line 79, in _coro_scheduler
    fut.set_result(await coro)
  File "/Users/rapcomia/anaconda3/envs/hummingbot/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/client/config/security.py", line 55, in decrypt_all
    cls.decrypt_connector_config(file)
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/client/config/security.py", line 61, in decrypt_connector_config
    cls._secure_configs[connector_name] = load_connector_config_map_from_file(file_path)
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/client/config/config_helpers.py", line 668, in load_connector_config_map_from_file
    _load_yml_data_into_map(config_data, config_map)
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/client/config/config_helpers.py", line 750, in _load_yml_data_into_map
    config_validation_errors = cm.validate_model()  # try coercing values to appropriate type
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/client/config/config_helpers.py", line 199, in validate_model
    self.decrypt_all_secure_data()
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/client/config/config_helpers.py", line 237, in decrypt_all_secure_data
    decrypted_value = Security.secrets_manager.decrypt_secret_value(attr=traversal_item.attr, value=value)
  File "/Users/rapcomia/github/hummingbot/test01/hummingbot/client/config/config_crypt.py", line 60, in decrypt_secret_value
    decrypted_value = Account.decrypt(value.decode(), self._password).decode()
  File "/Users/rapcomia/anaconda3/envs/hummingbot/lib/python3.10/site-packages/eth_account/account.py", line 176, in decrypt
    return HexBytes(decode_keyfile_json(keyfile, password_bytes))
  File "/Users/rapcomia/anaconda3/envs/hummingbot/lib/python3.10/site-packages/eth_keyfile/keyfile.py", line 56, in decode_keyfile_json
    return _decode_keyfile_json_v3(keyfile_json, password)
  File "/Users/rapcomia/anaconda3/envs/hummingbot/lib/python3.10/site-packages/eth_keyfile/keyfile.py", line 178, in _decode_keyfile_json_v3
    raise ValueError("MAC mismatch")
ValueError: MAC mismatch

Steps to reproduce

Setup latest development branch
Setup initial password and open the client
Close the client and delete file /conf/.password_verification
Start client again and enter new password
Observe behavior

Release version
dev-1.22.0
Type of installation
Source
Attach required files
errors.log

same issue on main branch, commit cdfc1f8b9a8e8ef1feb52567ba9c1b38bd588e7a

Reproduced on staging 1.25.0
2024-02-21 09:36:13,118 - 7579 - hummingbot.core.utils.async_utils - ERROR - Unhandled error in background task: 'utf-8' codec can't decode byte 0xc2 in position 4: invalid continuation byte
Traceback (most recent call last):
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/core/utils/async_utils.py", line 9, in safe_wrapper
    return await c
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/core/utils/async_call_scheduler.py", line 127, in call_async
    return await self.schedule_async_call(coro, timeout_seconds, app_warning_msg=app_warning_msg)
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/core/utils/async_call_scheduler.py", line 116, in schedule_async_call
    return await fut
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/core/utils/async_call_scheduler.py", line 79, in _coro_scheduler
    fut.set_result(await coro)
  File "/Users/rapcomia/miniconda3/envs/hummingbot/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/client/config/security.py", line 65, in decrypt_all
    cls.decrypt_connector_config(file)
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/client/config/security.py", line 71, in decrypt_connector_config
    cls._secure_configs[connector_name] = load_connector_config_map_from_file(file_path)
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/client/config/config_helpers.py", line 668, in load_connector_config_map_from_file
    _load_yml_data_into_map(config_data, config_map)
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/client/config/config_helpers.py", line 750, in _load_yml_data_into_map
    config_validation_errors = cm.validate_model()  # try coercing values to appropriate type
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/client/config/config_helpers.py", line 199, in validate_model
    self.decrypt_all_secure_data()
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/client/config/config_helpers.py", line 237, in decrypt_all_secure_data
    decrypted_value = Security.secrets_manager.decrypt_secret_value(attr=traversal_item.attr, value=value)
  File "/Users/rapcomia/github/hummingbot/staging/hummingbot/client/config/config_crypt.py", line 60, in decrypt_secret_value
    decrypted_value = Account.decrypt(value.decode(), self._password).decode()

Tried to delete the /conf/.password_verification and setup diff wallet, no go, getting ValueError: MAC mismatch
Revert the password back to original ✅
Assuming something to do with the original password since there are already connectors added

Removed all connector.yml files on conf/connector folder

No error found and able to start client, added few connectors for tests then repeat steps to reset client password and use diff password
Error mismatched happened again ❌
Run using ./bin/hummingbot.py, Able prompted to enter password but ended with same error

Workaround - User must remove the .password_verification and all connector.yml files on conf/connector from previous password to be able to reset.

[] Update docs https://hummingbot.org/client/password/#deleting-a-password

Closing ticket, workaround added to docs
Note that if you do remove the .password_verification file you'll also need to remove the existing connector.yml files under the conf/connector folder otherwise you'll run into an issue where the bot throws an error message and doesn't start.

authors: rapcmia wakamex

repo: hummingbot/hummingbot


text:
KeyError in get_candles_by_connector_trading_pair with different exchange and candle exchange configurations

Describe the bug
While using different configurations for the exchange and candle exchange in configuration, a KeyError is thrown in the function get_candles_by_connector_trading_pair. Specifically, this occurs when setting the exchange to binance_perpetual_testnet and the candle connector to binance_perpetual.
Steps to reproduce

Update the Hummingbot script from v2_market-making_dman_v2.py to use a different exchange as shown below:config_v2 = DManV2Config(
    exchange="binance_perpetual_testnet",
    trading_pair="ETH-USDT",
    order_levels=[...],  # Omitted for brevity
    candles_config=[
        CandlesConfig(connector="binance_perpetual", trading_pair="ETH-USDT", interval="15m", max_records=1000),
    ],
    ...  # Additional configuration omitted
)

Run the script.

Observed Result:
Upon the network status changing to connected, an error was thrown as captured in the log:
2023-11-25 18:15:51,560 - 15 - hummingbot.core.rate_oracle.rate_oracle - INFO - Network status has changed to NetworkStatus.CONNECTED. Starting networking...
2023-11-25 18:15:52,002 - 15 - hummingbot.core.utils.async_utils - ERROR - Unhandled error in background task: 'binance_perpetual_testnet_ETH-USDT'
[Traceback omitted for brevity]
KeyError: 'binance_perpetual_testnet_ETH-USDT'

Possible Root Cause:
The KeyError seems to cause from a mismatch in the naming conventions used in the candles dictionary. The system attempts to retrieve candle data using the key 'binance_perpetual_testnet_ETH-USDT', which does not exist as the candle name was set to binance_perpetual_ETH-USDT.
Release version
1.21.0
Type of installation
Docker
Attach required files
logs_v2_market-making_dman_v2.log

Tested. It is now working on development branch.
Thank you.


text:
ESLint Errors: SubElements

Describe the bug
I'm getting eslint errors for components defined like <Header.SubElement>. Is there a way to solve these ?
Object literal may only specify known properties, and 'children' does not exist in type 'HTMLAttributes<HTMLDivElement>'.

Reproduction
Follow install instructions
add components for Card from the CLI
Logs
"500 Internal Error"
System Info
System:
    OS: macOS 10.15.7
    CPU: (6) x64 Intel(R) Core(TM) i5-8500 CPU @ 3.00GHz
    Memory: 4.11 GB / 40.00 GB
    Shell: 3.2.57 - /bin/bash
  Binaries:
    Node: 20.11.0 - /usr/local/bin/node
    Yarn: 1.22.17 - /usr/local/bin/yarn
    npm: 10.2.4 - /usr/local/bin/npm
    pnpm: 8.6.0 - ~/Library/pnpm/pnpm
  Browsers:
    Chrome: 120.0.6099.216
    Safari: 15.6.1
  npmPackages:
    @sveltejs/kit: ^2.0.0 => 2.0.0
    bits-ui: ^0.14.0 => 0.14.0
    svelte: ^5.0.0-next.1 => 5.0.0-next.1

Severity
blocking

never mind! for some reason the latest version of packages wasn't installed.

repo: huntabyte/shadcn-svelte


text:
获取数据问题

我打开你的案例demo直接报错The getter 'length' was called on null. 点进去是这个地方
Scrollbar(
child: SingleChildScrollView(
child: Container(
width: bloc.rectWidth * data.length,(这里的length为null)
),
controller: _controller,
scrollDirection: Axis.horizontal,
))

Scrollbar(
child: SingleChildScrollView(
child: Container(
width: bloc.rectWidth * (data?.length ?? 0),(这里做一下这样的处理，就没有报错了)
),
controller: _controller,
scrollDirection: Axis.horizontal,
))

repo: huobiapp/flutter-candlesticks


text:
Fine tune rendering performance

Since there are multiple content-rich sections containing big/cover-size images, filter effects and sometimes even complete slides behaviour for the entire website background, it's interesting to identify, measure and remove or compensate any existing rendering bottlenecks.
One strategy available is informing the browser of these "hot regions" by using the CSS property will-change. For reference see this video: https://www.youtube.com/watch?v=2vFrZXWiwIc
Cheers!

Hey Davi! Thanks a lot! this is very interesting so far!


text:
🛑 Stream HLS encoding (slow) is down

In 86efd75, Stream HLS encoding (slow) (https://live.thekor.eu/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Stream HLS encoding (slow) is back up in 7996ed4 after 47 minutes.

repo: hupratt/upptime


text:
🛑 minio is down

In 0acd393, minio (https://minio.thekor.eu) was down:

HTTP code: 502
Response time: 3744 ms

Resolved: minio is back up in f179618 after 44 minutes.


text:
Feeding live data to app.py

i have hired one developer. . I have following queries one by one

What is the final command to run the app.py:  is it  agent.buy() or agent.trade(data) where data = [close(i), volume (i)].

If we can feed json data to agent.trade(data) from request.ipynb then why there is line 347 app.py we have :
df = pd.read_csv('TWTR.csv') real_trend = df['Close'].tolist() parameters = [df['Close'].tolist(), df['Volume'].tolist()] minmax = MinMaxScaler(feature_range = (100, 200)).fit(np.array(parameters).T) scaled_parameters = minmax.transform(np.array(parameters).T).T.tolist() initial_money = np.max(parameters[0]) * 2

why we need to feed again this data in app.py ?

Also inserting API call function to buy or sell the stocks where to add this function ? in :
def trade(): where the  if action == 1 : buy = buy_market OR
def buy():  where the  if action == 1 : buy = buy_market
plz guide @huseinzol05

I connect to live data using agent.buy(). But the app is pretty loss.  Probably the commission is not included.  Where we can add additional patams in app.py file.
Plz guide @huseinzol05

Yep, commission is not included, let me improve it, I really want to commit on this repo, but just too busy with my job.

Also how to integrate the inventory and capital to api so that the neural net cn decide whether he is really making any losess.  It should able to check the account balanaces of capital and total value of stock it holds.  This should work with tears function.  @huseinzol05

Whether the Best place to add the 1. Commission 2. Account balance 3. Stock holdings.   [
def _initiate(self):
# i assume first index is the close value
self.trend = self.timeseries[0]
self._mean = np.mean(self.trend)
self._std = np.std(self.trend)
self._inventory = assets
self._capital = self.initial_money
self. _commission = commission
]

@huseinzol05  its true that your code sucks :).

@augmen You are allowed to not follow the repo and code if you don't find it useful. I am pretty sure you won't be able to get to this state (as in this repo) if you do it yourself. @huseinzol05 : Ignore that prick. You are doing amazing work.


text:
question about DDIM step

非常感谢您的工作！
我想请问一下这里DDIM step输入的model_output对应的是trajectory？diffusion_scheduler的prediction_type是不是应该为‘sample’？

Thank you for pointing this out! It seems that I made an error while migrating and cleaning up the code. You are correct, the prediction_type="sample" in the DDIM scheduler. I have corrected this in the latest code.

authors: LegendBC YiJiangYue

repo: hustvl/DiffusionDrive


text:
Training code for TrackQuery

Hi,
Thank you for your great work. I have noticed that the repo contains the description about TrackQuery.
Could you please release the code for TrackQuery at your convenience?
Thank you!
Best,
Fan

Hi @Flowerfan, thanks for your interest in our work!
The code of QueryTrack (paper) may not be released recently.
Now we are working on a journal version of QueryInst & beyond, which may includes QueryTrack.
After that, we may release the code of QueryTrack.

authors: Flowerfan Yuxin-CV

repo: hustvl/QueryInst


text:
ValueError: Unknown loss function: 'dice'

Hello, I set my virtual environment according to your requirement, python3.9, tensorflow2.11, but I met the error
ValueError: Unknown loss function: 'dice'. Please ensure you are using a keras.utils.custom_object_scope and that this object is included in the scope.

Hi dear,
For the custom_object "dice", you can ignore it by compile = False during load model. During the load model, follow this:
model = tf.keras.models.load_model("your model name", compile = False)

You can solve that problem!
Thank you so much for raising this issue

Thanks for your answering. But I met the error when I use train.py, I can't find the code you refered in train.py and it occurs in the code below. Whether it may be caused by the version of tensorflow?
his = model.fit(train_dataset,
epochs=epochs,
verbose=1,
callbacks=callbacks,
steps_per_epoch=steps_per_epoch,
validation_data=valid_dataset, )

Hi, thanks for your response. To solve this problem, we can add directly the loss function to the compile attribute of the model via this code
model.compile(optimizer = opts,
            loss= dice_loss,
            metrics=[dice_coeff,bce_dice_loss, IoU, zero_IoU])

Thank you very much for solving my problem!

It's my pleasure. I will close this issue, thanks for raising it :>


text:
"node server/server.js" or "npm start" is not working

I have all packages (NPM,Socket,Bower, etc.). I think that I installed all of requires correctly. But I get an error like;

root@xxx:~/agar.io-clone# npm start

agar-clone@1.0.0 start /root/agar.io-clone
node server/server.js

Config file not found!

When I try to write "node server/server.js"

root@sinankose:~/agar.io-clone# node server/server.js
-bash: /usr/sbin/node: No such file or directory

Both are not working, what should I do?

-bash: /usr/sbin/node: No such file or directory

May be it was a problem with your nodejs installation
Could you run this command?
node -v

OK. Found the problem.
It's not node problem, but there is a new Config file (config.yml)
I fixed it in the latest commit

Should I clone again?

@nezcafe clone, please

I get an error again;
root@xxx:~/agar.io-clone# node server/server.js
module.js:340
throw err;
Error: Cannot find module 'js-yaml'
at Function.Module._resolveFilename (module.js:338:15)
at Function.Module._load (module.js:280:25)
at Module.require (module.js:364:17)
at require (module.js:380:17)
at Object. (/root/agar.io-clone/server/server.js:7:12)
at Module._compile (module.js:456:26)
at Object.Module._extensions..js (module.js:474:10)
at Module.load (module.js:356:32)
at Function.Module._load (module.js:312:12)
at Function.Module.runMain (module.js:497:10)

That's good, you are almost there. Rerun npm install and it should work.

https://github.com/huytd/agar.io-clone/pull/98

Doesnt figure out. I get still an error.

post the error here

root@xxx:~/agar.io-clone# node server/server.js
module.js:340
throw err;
^
Error: Cannot find module 'js-yaml'
at Function.Module._resolveFilename (module.js:338:15)
at Function.Module._load (module.js:280:25)
at Module.require (module.js:364:17)
at require (module.js:380:17)
at Object. (/root/agar.io-clone/server/server.js:7:12)
at Module._compile (module.js:456:26)
at Object.Module._extensions..js (module.js:474:10)
at Module.load (module.js:356:32)
at Function.Module._load (module.js:312:12)
at Function.Module.runMain (module.js:497:10)

try this command:
´´´´
npm install js-yaml
´´´´

root@xxx:~/agar.io-clone# node server/server.js
Config file not found!

omg, create a new file in server folder called config.yml
and paste in config.yml:
port: 3000
maxSizeMass: 50
maxMoveSpeed: 10
massDecreaseRatio: 1000
foodMass: 1
newFoodPerPlayer: 30
respawnFoodPerPlayer: 1
foodRandomWidth: 500
foodRandomHeight: 500
maxFoodCount: 50
noPlayer: 0
defaultPlayerSize: 10
eatableMassDistance: 5

save and start server

I got it, but again error.
root@sinankose:~/agar.io-clone/server# npm start

agar-clone@1.0.0 start /root/agar.io-clone
node server/server.js

listening on *:undefined

delete and download this:
https://github.com/Ariamiro/agar.io-clone.git
use command:
npm install

after, open the server

I did these;

root@xxx:~# rm -rf agar.io-clone/
root@xxx:~# git clone https://github.com/Ariamiro/agar.io-clone.git
Cloning into 'agar.io-clone'...
remote: Counting objects: 566, done.
remote: Compressing objects: 100% (21/21), done.
remote: Total 566 (delta 6), reused 0 (delta 0), pack-reused 541
Receiving objects: 100% (566/566), 105.07 KiB | 0 bytes/s, done.
Resolving deltas: 100% (278/278), done.
Checking connectivity... done.

Then;
root@xxx:~# npm install
npm ERR! install Couldn't read dependencies
npm ERR! Linux 3.13.0-27-generic
npm ERR! argv "node" "/usr/local/bin/npm" "install"
npm ERR! node v0.10.25
npm ERR! npm  v2.11.0
npm ERR! path /root/package.json
npm ERR! code ENOPACKAGEJSON
npm ERR! errno 34
npm ERR! package.json ENOENT, open '/root/package.json'
npm ERR! package.json This is most likely not a problem with npm itself.
npm ERR! package.json npm can't find a package.json file in your current directory.
npm ERR! Please include the following file with any support request:
npm ERR!     /root/npm-debug.log

the npm can't find a package.json, are you in the right folder?

Yes, I installed now. But start server isnt working.
root@xxx:~/agar.io-clone# npm start

agar-clone@1.0.0 start /root/agar.io-clone
node server/server.js

fs.js:432
return binding.open(pathModule._makeLong(path), stringToFlags(flags), mode);
^
Error: ENOENT, no such file or directory 'config/config.yml'
at Object.fs.openSync (fs.js:432:18)
at Object.fs.readFileSync (fs.js:286:15)
at Object. (/root/agar.io-clone/server/server.js:12:31)
at Module._compile (module.js:456:26)
at Object.Module._extensions..js (module.js:474:10)
at Module.load (module.js:356:32)
at Function.Module._load (module.js:312:12)
at Function.Module.runMain (module.js:497:10)
at startup (node.js:119:16)
at node.js:902:3
npm ERR! Linux 3.13.0-27-generic
npm ERR! argv "node" "/usr/local/bin/npm" "start"
npm ERR! node v0.10.25
npm ERR! npm  v2.11.0
npm ERR! code ELIFECYCLE
npm ERR! agar-clone@1.0.0 start: node server/server.js
npm ERR! Exit status 8
npm ERR!
npm ERR! Failed at the agar-clone@1.0.0 start script 'node server/server.js'.
npm ERR! This is most likely a problem with the agar-clone package,
npm ERR! not with npm itself.
npm ERR! Tell the author that this fails on your system:
npm ERR!     node server/server.js
npm ERR! You can get their info via:
npm ERR!     npm owner ls agar-clone
npm ERR! There is likely additional logging output above.
npm ERR! Please include the following file with any support request:
npm ERR!     /root/agar.io-clone/npm-debug.log

go to server and rename config.dist.yml to config.yml

I did it, but again error :(
root@xxx:~/agar.io-clone# node server/server.js
fs.js:432
return binding.open(pathModule._makeLong(path), stringToFlags(flags), mode);
^
Error: ENOENT, no such file or directory 'config/config.yml'
at Object.fs.openSync (fs.js:432:18)
at Object.fs.readFileSync (fs.js:286:15)
at Object. (/root/agar.io-clone/server/server.js:12:31)
at Module._compile (module.js:456:26)
at Object.Module._extensions..js (module.js:474:10)
at Module.load (module.js:356:32)
at Function.Module._load (module.js:312:12)
at Function.Module.runMain (module.js:497:10)
at startup (node.js:119:16)
at node.js:902:3

authors: Ariamiro huytd jniles nezcafe


text:
Feature Request: pvc-autoresizer

when the pvc meet a threshold of capacity, it will be auto resized, and if fail, some warning show up somewhere.

@sun7927

https://github.com/topolvm/pvc-autoresizer

planned already

planned and in progress of feature developing

done

repo: hwameistor/hwameistor


text:
s3Directory Loader with prefix error

I am running into an error when attempting to read a bunch of csvs from a folder in s3 bucket.
from langchain.document_loaders import S3FileLoader, S3DirectoryLoader
loader = S3DirectoryLoader("s3-bucker", prefix="folder1")
loader.load()

Traceback:
---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
/tmp/ipykernel_27645/1860550440.py in <cell line: 18>()
     16 from langchain.document_loaders import S3FileLoader, S3DirectoryLoader
     17 loader = S3DirectoryLoader("stroom-data", prefix="dbrs")
---> 18 loader.load()

~/anaconda3/envs/python3/lib/python3.10/site-packages/langchain/document_loaders/s3_directory.py in load(self)
     29         for obj in bucket.objects.filter(Prefix=self.prefix):
     30             loader = S3FileLoader(self.bucket, obj.key)
---> 31             docs.extend(loader.load())
     32         return docs

~/anaconda3/envs/python3/lib/python3.10/site-packages/langchain/document_loaders/s3_file.py in load(self)
     28         with tempfile.TemporaryDirectory() as temp_dir:
     29             file_path = f"{temp_dir}/{self.key}"
---> 30             s3.download_file(self.bucket, self.key, file_path)
     31             loader = UnstructuredFileLoader(file_path)
     32             return loader.load()

~/anaconda3/envs/python3/lib/python3.10/site-packages/boto3/s3/inject.py in download_file(self, Bucket, Key, Filename, ExtraArgs, Callback, Config)
    188     """
    189     with S3Transfer(self, Config) as transfer:
--> 190         return transfer.download_file(
    191             bucket=Bucket,
    192             key=Key,

~/anaconda3/envs/python3/lib/python3.10/site-packages/boto3/s3/transfer.py in download_file(self, bucket, key, filename, extra_args, callback)
    324         )
    325         try:
--> 326             future.result()
    327         # This is for backwards compatibility where when retries are
    328         # exceeded we need to throw the same error from boto3 instead of

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/futures.py in result(self)
    101             # however if a KeyboardInterrupt is raised we want want to exit
    102             # out of this and propagate the exception.
--> 103             return self._coordinator.result()
    104         except KeyboardInterrupt as e:
    105             self.cancel()

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/futures.py in result(self)
    264         # final result.
    265         if self._exception:
--> 266             raise self._exception
    267         return self._result
    268

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/tasks.py in __call__(self)
    137             # main() method.
    138             if not self._transfer_coordinator.done():
--> 139                 return self._execute_main(kwargs)
    140         except Exception as e:
    141             self._log_and_set_exception(e)

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/tasks.py in _execute_main(self, kwargs)
    160         logger.debug(f"Executing task {self} with kwargs {kwargs_to_display}")
    161
--> 162         return_value = self._main(**kwargs)
    163         # If the task is the final task, then set the TransferFuture's
    164         # value to the return value from main().

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/download.py in _main(self, fileobj, data, offset)
    640         :param offset: The offset to write the data to.
    641         """
--> 642         fileobj.seek(offset)
    643         fileobj.write(data)
    644

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/utils.py in seek(self, where, whence)
    376
    377     def seek(self, where, whence=0):
--> 378         self._open_if_needed()
    379         self._fileobj.seek(where, whence)
    380

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/utils.py in _open_if_needed(self)
    359     def _open_if_needed(self):
    360         if self._fileobj is None:
--> 361             self._fileobj = self._open_function(self._filename, self._mode)
    362             if self._start_byte != 0:
    363                 self._fileobj.seek(self._start_byte)

~/anaconda3/envs/python3/lib/python3.10/site-packages/s3transfer/utils.py in open(self, filename, mode)
    270
    271     def open(self, filename, mode):
--> 272         return open(filename, mode)
    273
    274     def remove_file(self, filename):

FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmpx99uzbme/dbrs/.792d2ba4'

I'm able to reproduce on langchain==0.0.102
I created test objects in S3 using the following code snippet:
import boto3

s3 = boto3.resource('s3')

for i in range(0, 10):
  s3.Bucket('langchain-debugging-test').put_object(Key=f'folder/hello-{i}.txt', Body=f'Hello World {i}!')

I then have the same error when running the following code:
from langchain.document_loaders import S3DirectoryLoader

loader = S3DirectoryLoader("langchain-debugging-test", prefix="folder")
loader.load()

Full stack trace
Traceback (most recent call last):
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/recreate-s3-error.py", line 11, in <module>
    loader.load()
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/langchain/document_loaders/s3_directory.py", line 31, in load
    docs.extend(loader.load())
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/langchain/document_loaders/s3_file.py", line 30, in load
    s3.download_file(self.bucket, self.key, file_path)
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/boto3/s3/inject.py", line 190, in download_file
    return transfer.download_file(
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/boto3/s3/transfer.py", line 326, in download_file
    future.result()
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/futures.py", line 103, in result
    return self._coordinator.result()
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/futures.py", line 266, in result
    raise self._exception
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/tasks.py", line 139, in __call__
    return self._execute_main(kwargs)
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/tasks.py", line 162, in _execute_main
    return_value = self._main(**kwargs)
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/download.py", line 642, in _main
    fileobj.seek(offset)
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/utils.py", line 378, in seek
    self._open_if_needed()
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/utils.py", line 361, in _open_if_needed
    self._fileobj = self._open_function(self._filename, self._mode)
  File "/Users/alprielse/src/sandboxed/2023-03-07_langchain/.venv/lib/python3.9/site-packages/s3transfer/utils.py", line 272, in open
    return open(filename, mode)
FileNotFoundError: [Errno 2] No such file or directory: '/var/folders/kt/7gdyyk6d75lbw1xwdqkrbrjw0000gn/T/tmpgypdhma7/folder/hello-0.txt.ddBa004f'

Working on a fix


text:
LLMMathChain 'VariableNode' object has no attribute 'factorial'. Please try again with a valid numerical expression

System Info
langchain version 0.0.196
windows, wsl2
python 3.11.3
Who can help?
@agola11
Information

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

Related Components

[ ] LLMs/Chat Models
[ ] Embedding Models
[ ] Prompts / Prompt Templates / Prompt Selectors
[ ] Output Parsers
[ ] Document Loaders
[ ] Vector Stores / Retrievers
[ ] Memory
[X] Agents / Agent Executors
[ ] Tools / Toolkits
[X] Chains
[ ] Callbacks/Tracing
[ ] Async

Reproduction
Follow instructions on this page:
https://python.langchain.com/en/latest/modules/agents/plan_and_execute.html
Then run the following prompt:
agent.run("Who is Elon Musk in a relationship with? What is their current age factorial?")

Expected behavior
It should plan out how to solve the problem (search significant other, search age, find factorial, respond) then execute each action and respond to the user. Instead, when it gets to the factorial part, it fails, claiming that there's no factorial function. Stacktrace:
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
File [~/miniconda3/envs/langchain/lib/python3.11/site-packages/langchain/chains/llm_math/base.py:80](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/oriont/dev/langchain-phx/~/miniconda3/envs/langchain/lib/python3.11/site-packages/langchain/chains/llm_math/base.py:80), in LLMMathChain._evaluate_expression(self, expression)
     78     local_dict = {"pi": math.pi, "e": math.e}
     79     output = str(
---> 80         numexpr.evaluate(
     81             expression.strip(),
     82             global_dict={},  # restrict access to globals
     83             local_dict=local_dict,  # add common mathematical functions
     84         )
     85     )
     86 except Exception as e:

File [~/miniconda3/envs/langchain/lib/python3.11/site-packages/numexpr/necompiler.py:817](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/oriont/dev/langchain-phx/~/miniconda3/envs/langchain/lib/python3.11/site-packages/numexpr/necompiler.py:817), in evaluate(ex, local_dict, global_dict, out, order, casting, **kwargs)
    816 if expr_key not in _names_cache:
--> 817     _names_cache[expr_key] = getExprNames(ex, context)
    818 names, ex_uses_vml = _names_cache[expr_key]

File [~/miniconda3/envs/langchain/lib/python3.11/site-packages/numexpr/necompiler.py:704](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/oriont/dev/langchain-phx/~/miniconda3/envs/langchain/lib/python3.11/site-packages/numexpr/necompiler.py:704), in getExprNames(text, context)
    703 def getExprNames(text, context):
--> 704     ex = stringToExpression(text, {}, context)
    705     ast = expressionToAST(ex)

File [~/miniconda3/envs/langchain/lib/python3.11/site-packages/numexpr/necompiler.py:289](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/oriont/dev/langchain-phx/~/miniconda3/envs/langchain/lib/python3.11/site-packages/numexpr/necompiler.py:289), in stringToExpression(s, types, context)
    288 # now build the expression
...
     93 return re.sub(r"^\[|\]$", "", output)

ValueError: LLMMathChain._evaluate("
math.factorial(33)
") raised error: 'VariableNode' object has no attribute 'factorial'. Please try again with a valid numerical expression

I believe this is related to #3108, it looks like factorial isn't a function from numexpr


text:
feat: notion db loader

Basic Notion Database loader.

Hey @jacoblee93, this one should be good to go.

Thank you! Will take a look as soon as I can.

Thank you! Will merge with the next release.

Thank you! Will merge with the next release.

Thanks for the fixes!


text:
報酬関数の修正について

compute_reward の実質的な計算箇所
https://github.com/hwip/synergy/blob/bb5e1cd2a55ebd4a7224adc67c6f3c64cd4f0f3d/baselines/her/experiment/config.py#L123
忘れないようにメモ．
※下記の件について対応

何故かというと、HERでは報酬の計算をExperience Replayのフェーズで再計算するため、Rolloutで計算した内容は廃棄されます。
もちろん、報酬の再計算の際は、把持姿勢データセットへの姿勢の追加は済んでいます。
そうすると、HERでの報酬再計算においてcompute_rewardで用いられるself.variance_ratioは常に一定値になります。
従って、報酬関数の寄与率の項は同epoch間で定数になりますので、学習に影響を及ぼしません。
以上が、報酬関数における寄与率の項が機能していなかった理由になります。

多分ここから
https://github.com/hwip/synergy/blob/bb5e1cd2a55ebd4a7224adc67c6f3c64cd4f0f3d/baselines/her/her.py#L54

repo: hwip/synergy


text:
ld.lld: error: undefined hidden symbol: __math_invalidf

I built tinygo from source as per official documentation  (on gentoo here)
tried to run ping pong example on nicenano
$ sudo ~/go/bin/mecha flash -i wazero -m nicenano
Building TinyGo module ping
Done.
   code    data     bss |   flash     ram
      9       0       0 |       9       0
Application built. Now flashing...
ld.lld: error: undefined hidden symbol: __math_invalidf
>>> referenced by sf_sqrt.c:0 (/home/zogg/dev/tinygo/lib/picolibc/newlib/libm/math/sf_sqrt.c:0)
>>>               sf_sqrt.c.o:(sqrtf) in archive /root/.cache/tinygo/picolibc-thumbv7em-unknown-unknown-eabi-cortex-m4/lib.a
>>> did you mean: __math_invalid
>>> defined in: /root/.cache/tinygo/picolibc-thumbv7em-unknown-unknown-eabi-cortex-m4/lib.a(math_err_invalid)
failed to run tool: ld.lld
error: failed to link /tmp/tinygo2142027620/main: exit status 1
/usr/local/bin/tinygo flash -size short -stack-size 8kb -tags wazero -target nicenano -monitor .: exit status 1

btw i tried to do use only tinygo and wazero and get the same results
$ tinygo version
tinygo version 0.31.2 linux/amd64 (using go version go1.22.2 and LLVM version 17.0.1)

Hello @funkycode thanks for the report. I think this is actually related more to your TinyGo custom build than Mechanoid itself.
Can you flash the normal blinky1 program on your board?
tinygo flash -target nicenano examples/blinky1

Perhaps you can open an issue in the TinyGo repo to resolve. It might require some docs update for gentoo? Not sure on that one.

please notice the wazero team currently is not actively maintaining support for this type of cross-build, we merely assisted the mechanoid team to upstream their patches ;)

Sorry if I was unclear. I doubt it is anything specific to Wazero, rather is something to do with the custom TinyGo install. I meant to
suggest opening issue in TinyGo repo, not Wazero repo.

Also see https://github.com/tinygo-org/tinygo/issues/3530

authors: deadprogram evacchi funkycode

repo: hybridgroup/mechanoid


text:
Raster band information editing fails unless all metadata elements are provided

In a raster resource when editing band information I get an error "Metadata failed to update" if I change VariableName and Meters which both have * next to them indicating required and do not enter information for Method or Comment, both of which should not be required.  However if I enter content in Method or Comment it works.

Tested on beta.

repo: hydroshare/hydroshare


text:
1.6.10 - solr rebuild_index / update_index error

UPDATE:
@zhiyuli - Decided to scrap the database and start over with the copy of www database from Sunday which seemed to deploy as expected in regards to solr rebuild index and update index.
The issue denoted before was in regards to drew collection 1, of which there are two versions of. Neither would render as valid end points previously, they now seem to resolve on alpha.

Using copy of www resources (as seen on alpha.hydroshare.org) there is an error in reference to BaseResource: drew collection 1, @zhiyuli may have an idea...
./hsctl rebuild_index
[hydrobuild@alpha hydroshare]$ ./hsctl rebuild_index
/usr/local/lib/python2.7/site-packages/mezzanine/utils/conf.py:55: UserWarning: TIME_ZONE setting is not set, using closest match: Etc/UTC
  warn("TIME_ZONE setting is not set, using closest match: %s" % tz)
/usr/local/lib/python2.7/site-packages/django/contrib/contenttypes/models.py:161: RemovedInDjango19Warning: Model class django.contrib.contenttypes.models.ContentType doesn't declare an explicit app_label and either isn't in an application in INSTALLED_APPS or else was imported before its application was loaded. This will no longer be supported in Django 1.9.
  class ContentType(models.Model):

/usr/local/lib/python2.7/site-packages/autocomplete_light/widgets.py:19: RemovedInDjango19Warning: The django.forms.util module has been renamed. Use django.forms.utils instead.
  from django.forms.util import flatatt

/usr/local/lib/python2.7/site-packages/autocomplete_light/fields.py:8: RemovedInDjango19Warning: django.contrib.contenttypes.generic is deprecated and will be removed in Django 1.9. Its contents have been moved to the fields, forms, and admin submodules of django.contrib.contenttypes.
  from django.contrib.contenttypes.generic import GenericForeignKey

System check identified some issues:

WARNINGS:
?: (mezzanine.core.W01) Please update your settings to use the TEMPLATES setting rather than the deprecated individual TEMPLATE_ settings. The latter are unsupported and correct behaviour is not guaranteed. Here's a suggestion based on on your existing configuration:

TEMPLATES = [{u'APP_DIRS': True,
              u'BACKEND': u'django.template.backends.django.DjangoTemplates',
              u'DIRS': (u'/home/docker/hydroshare/hydroshare/templates',),
              u'OPTIONS': {u'builtins': [u'mezzanine.template.loader_tags'],
                           u'context_processors': (u'django.contrib.auth.context_processors.auth',
                                                   u'django.contrib.messages.context_processors.messages',
                                                   u'django.core.context_processors.debug',
                                                   u'django.core.context_processors.i18n',
                                                   u'django.core.context_processors.static',
                                                   u'django.core.context_processors.media',
                                                   u'django.core.context_processors.request',
                                                   u'django.core.context_processors.tz',
                                                   u'mezzanine.conf.context_processors.settings',
                                                   u'mezzanine.pages.context_processors.page')}}]

?: (mezzanine.core.W02) TEMPLATE_DEBUG and DEBUG settings have different values, which may not be what you want. Mezzanine used to fix this for you, but doesn't any more. Update your settings.py to use the TEMPLATES setting to have template debugging controlled by the DEBUG setting.
hs_tools_resource.SupportedResTypes.supported_res_types: (fields.W340) null has no effect on ManyToManyField.
Removing all documents from your index because you said so.
All documents removed.
Indexing 377 Generics
Traceback (most recent call last):
  File "manage.py", line 8, in <module>
    execute_from_command_line(sys.argv)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
    utility.execute()
  File "/usr/local/lib/python2.7/site-packages/django/core/management/__init__.py", line 346, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/base.py", line 394, in run_from_argv
    self.execute(*args, **cmd_options)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/base.py", line 445, in execute
    output = self.handle(*args, **options)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/rebuild_index.py", line 26, in handle
    call_command('update_index', **options)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/__init__.py", line 120, in call_command
    return command.execute(*args, **defaults)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/base.py", line 445, in execute
    output = self.handle(*args, **options)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 183, in handle
    return super(Command, self).handle(*items, **options)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/base.py", line 623, in handle
    label_output = self.handle_label(label, **options)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 188, in handle_label
    self.update_backend(label, using)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 233, in update_backend
    do_update(backend, index, qs, start, end, total, verbosity=self.verbosity, commit=self.commit)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 96, in do_update
    backend.update(index, current_qs, commit=commit)
  File "/usr/local/lib/python2.7/site-packages/haystack/backends/solr_backend.py", line 56, in update
    docs.append(index.full_prepare(obj))
  File "/usr/local/lib/python2.7/site-packages/haystack/indexes.py", line 212, in full_prepare
    self.prepared_data = self.prepare(obj)
  File "/usr/local/lib/python2.7/site-packages/haystack/indexes.py", line 203, in prepare
    self.prepared_data[field.index_fieldname] = field.prepare(obj)
  File "/usr/local/lib/python2.7/site-packages/haystack/fields.py", line 159, in prepare
    return self.convert(super(CharField, self).prepare(obj))
  File "/usr/local/lib/python2.7/site-packages/haystack/fields.py", line 103, in prepare
    raise SearchFieldError("The model '%s' combined with model_attr '%s' returned None, but doesn't allow a default or null value." % (repr(obj), self.model_attr))
haystack.exceptions.SearchFieldError: The model '<BaseResource: drew collection 1>' combined with model_attr 'first_creator' returned None, but doesn't allow a default or null value.

./hsctl update_index
[hydrobuild@alpha hydroshare]$ ./hsctl update_index
/usr/local/lib/python2.7/site-packages/mezzanine/utils/conf.py:55: UserWarning: TIME_ZONE setting is not set, using closest match: Etc/UTC
  warn("TIME_ZONE setting is not set, using closest match: %s" % tz)
/usr/local/lib/python2.7/site-packages/django/contrib/contenttypes/models.py:161: RemovedInDjango19Warning: Model class django.contrib.contenttypes.models.ContentType doesn't declare an explicit app_label and either isn't in an application in INSTALLED_APPS or else was imported before its application was loaded. This will no longer be supported in Django 1.9.
  class ContentType(models.Model):

/usr/local/lib/python2.7/site-packages/autocomplete_light/widgets.py:19: RemovedInDjango19Warning: The django.forms.util module has been renamed. Use django.forms.utils instead.
  from django.forms.util import flatatt

/usr/local/lib/python2.7/site-packages/autocomplete_light/fields.py:8: RemovedInDjango19Warning: django.contrib.contenttypes.generic is deprecated and will be removed in Django 1.9. Its contents have been moved to the fields, forms, and admin submodules of django.contrib.contenttypes.
  from django.contrib.contenttypes.generic import GenericForeignKey

System check identified some issues:

WARNINGS:
?: (mezzanine.core.W01) Please update your settings to use the TEMPLATES setting rather than the deprecated individual TEMPLATE_ settings. The latter are unsupported and correct behaviour is not guaranteed. Here's a suggestion based on on your existing configuration:

TEMPLATES = [{u'APP_DIRS': True,
              u'BACKEND': u'django.template.backends.django.DjangoTemplates',
              u'DIRS': (u'/home/docker/hydroshare/hydroshare/templates',),
              u'OPTIONS': {u'builtins': [u'mezzanine.template.loader_tags'],
                           u'context_processors': (u'django.contrib.auth.context_processors.auth',
                                                   u'django.contrib.messages.context_processors.messages',
                                                   u'django.core.context_processors.debug',
                                                   u'django.core.context_processors.i18n',
                                                   u'django.core.context_processors.static',
                                                   u'django.core.context_processors.media',
                                                   u'django.core.context_processors.request',
                                                   u'django.core.context_processors.tz',
                                                   u'mezzanine.conf.context_processors.settings',
                                                   u'mezzanine.pages.context_processors.page')}}]

?: (mezzanine.core.W02) TEMPLATE_DEBUG and DEBUG settings have different values, which may not be what you want. Mezzanine used to fix this for you, but doesn't any more. Update your settings.py to use the TEMPLATES setting to have template debugging controlled by the DEBUG setting.
hs_tools_resource.SupportedResTypes.supported_res_types: (fields.W340) null has no effect on ManyToManyField.
Indexing 377 Generics
Traceback (most recent call last):
  File "manage.py", line 8, in <module>
    execute_from_command_line(sys.argv)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
    utility.execute()
  File "/usr/local/lib/python2.7/site-packages/django/core/management/__init__.py", line 346, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/base.py", line 394, in run_from_argv
    self.execute(*args, **cmd_options)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/base.py", line 445, in execute
    output = self.handle(*args, **options)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 183, in handle
    return super(Command, self).handle(*items, **options)
  File "/usr/local/lib/python2.7/site-packages/django/core/management/base.py", line 623, in handle
    label_output = self.handle_label(label, **options)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 188, in handle_label
    self.update_backend(label, using)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 233, in update_backend
    do_update(backend, index, qs, start, end, total, verbosity=self.verbosity, commit=self.commit)
  File "/usr/local/lib/python2.7/site-packages/haystack/management/commands/update_index.py", line 96, in do_update
    backend.update(index, current_qs, commit=commit)
  File "/usr/local/lib/python2.7/site-packages/haystack/backends/solr_backend.py", line 56, in update
    docs.append(index.full_prepare(obj))
  File "/usr/local/lib/python2.7/site-packages/haystack/indexes.py", line 212, in full_prepare
    self.prepared_data = self.prepare(obj)
  File "/usr/local/lib/python2.7/site-packages/haystack/indexes.py", line 203, in prepare
    self.prepared_data[field.index_fieldname] = field.prepare(obj)
  File "/usr/local/lib/python2.7/site-packages/haystack/fields.py", line 159, in prepare
    return self.convert(super(CharField, self).prepare(obj))
  File "/usr/local/lib/python2.7/site-packages/haystack/fields.py", line 103, in prepare
    raise SearchFieldError("The model '%s' combined with model_attr '%s' returned None, but doesn't allow a default or null value." % (repr(obj), self.model_attr))
haystack.exceptions.SearchFieldError: The model '<BaseResource: drew collection 1>' combined with model_attr 'first_creator' returned None, but doesn't allow a default or null value.

Closing as the error doesn't seem to be reproducible on a clean deploy of the environment.


text:
bot ignores messages please help

Hey bro. Just wanna ask for help. The bot seems ignoring the commands. Please help :( Thank you!

Hi, it's been a while since I touched this so it could be the case that some of the dependencies (probably discord.js) got updated and what I have is deprecated.
I would recommend looking at their documentation and seeing what is the new and proper way of making the bot respond to messages.

Hey bro. Im r3ally sorry. I am no developer myself. Uhm can you try
updating this bot of yours? I am really interested with this one. Thabk you
bro great work!
On Fri, 26 Apr 2019, 10:57 AM Haoyang Zhu notifications@github.com wrote:

Hi, it's been a while since I touched this so it could be the case that
some of the dependencies (probably discord.js) got updated and what I have
is deprecated.
I would recommend looking at their documentation and seeing what is the
new and proper way of making the bot respond to messages.
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Sorry, I am currently quite busy with some other commitments so I won't be able to update it. There might be others with similar projects so I would suggest searching for those. Otherwise, you don't have to be a developer to learn a bit of javascript :)

Thank you bro. One more tuing, can I update or put my own database or own
music on your bot? Or is it gonna be fixed already?
On Mon, 29 Apr 2019, 8:20 AM Haoyang Zhu notifications@github.com wrote:

Sorry, I am currently quite busy with some other commitments so I won't be
able to update it. There might be others with similar projects so I would
suggest searching for those. Otherwise, you don't have to be a developer to
learn a bit of javascript :)
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Sorry, I don't quite understand. If you mean to play your own music through the bot, you can definitely find a way to do so.

authors: hygzhu tunatic

repo: hygzhu/discord-bot-song-trivia


text:
🛑 MCPRS - Bell is down

In 461b09a, MCPRS - Bell (https://mcprs.hydev.org) was down:

HTTP code: 0
Response time: 0 ms

Resolved: MCPRS - Bell is back up in 2a9ace0 after 16 minutes.

repo: hykilpikonna/Uptime


text:
Start download after changing start index when using tail

Otherwise all blocks get downloaded.
(still needs a test)

A test for it would be nice!

Closing cause old and lots have changed

authors: jimpick mafintosh martinheidegger

repo: hypercore-protocol/hypercore


text:
Fixed bug that amqp io has been bound to more than one coroutine when out of buffer.

fix https://github.com/hyperf/hyperf/issues/4235

谢谢

repo: hyperf/hyperf