Hosting PyHARP Apps in the Cloud (HuggingFace Spaces)

Automatically generated Gradio endpoints are only available for a maximum of 72 hours. If you'd like to keep an endpoint active and share it with other users, you can use HuggingFace Spaces (similar hosting services are also available) to host your PyHARP app indefinitely.

Gradio Endpoints

This is the most convenient solution for hosting a PyHARP app. If you are a Hugging Face PRO subscriber, you can use ZeroGPU to dynamically allocate GPU resources according to user requests without any additional charges. Non-PRO users can select from CPU environments or paid GPU options.

1. Create a new HuggingFace Space.
2. Choose Gradio as the SDK along with the blank template.
3. Select the desired hardware option.
4. Create the space and clone the initialized repository locally:

git clone https://huggingface.co/spaces/<USERNAME>/<SPACE_NAME>

5. Add your files to the repository, commit, then push to the main branch:

git add .
git commit -m "initial commit"
git push -u origin main

6. Configure the following repository files:

   • README.md

     Set sdk_version to 5.28.0, the recommended version of gradio. HARP may not work with the very latest or earlier versions.

   • requirements.txt

     Place all of the required pip packages in this file. It should also include the latest version of pyharp:

     git+https://github.com/TEAMuP-dev/pyharp.git@v0.3.0

     Note that you do not have to include the gradio package in this file.

   • packages.txt

     Place any necessary apt-get install debian packages in this file. Some models may require these.

Docker Endpoints

Some models may have been developed with older versions of Python, and attempting to deploy them would lead to dependency issues. For example, the numpy.float and numpy.int deprecation in numpy==1.24 breaks older packages such as madmom. Therefore, we may need to patch any corresponding source files during the deployment process. However, this is not supported by the highly-modularized Gradio SDK.

Using Docker endpoints can help circumvent these issues. Docker will allow you to customize the deployment, which makes room for any necessary patches. Note however that ZeroGPU is not available for Docker spaces, meaning you must pay to use GPU resources with this option.

1. Create a new HuggingFace Space.
2. Choose Docker as the SDK along with the blank template.
3. Select the desired hardware option.
4. Create the space and clone the initialized repository locally:

git clone https://huggingface.co/spaces/<USERNAME>/<SPACE_NAME>

5. Add your files to the repository, commit, then push to the main branch:

git add .
git commit -m "initial commit"
git push -u origin main

6. Configure the following repository files:

   • README.md

     Set app_port to any valid <PORT>.

   • requirements.txt

     Place all of the required pip packages in this file. It should also include the recommended version of gradio and the latest version of pyharp:

     gradio==5.28.0
     git+https://github.com/TEAMuP-dev/pyharp.git@v0.3.0

   • packages.txt

     Place any necessary apt-get install debian packages in this file. Some models may require these.

   • Dockerfile

     Installs the required pip and apt-get packages, and supports manual patching (e.g. of madmom in the following example):

     FROM python:3.10-slim # Set python version
     
     WORKDIR /app
     COPY packages.txt /app/packages.txt
     
     # System dependencies for building packages from source
     RUN apt-get update
     RUN xargs apt-get install -y --no-install-recommends < /app/packages.txt
     RUN rm -rf /var/lib/apt/lists/*
     
     COPY requirements.txt /app/requirements.txt
     # Disable build isolation so Cython installed in the environment is visible at build time
     ENV PIP_NO_BUILD_ISOLATION=1
     RUN pip install --no-cache-dir -U pip wheel Cython
     RUN pip install --no-cache-dir setuptools==80.9.0
     RUN pip install --no-cache-dir -r /app/requirements.txt
     RUN pip install --no-cache-dir --no-build-isolation madmom
     
     # Patch madmom package
     COPY patch_madmom.py /app/scripts/patch_madmom.py # Script to patch madmom source files
     RUN python /app/scripts/patch_madmom.py
     RUN python -c "import madmom; print('madmom import OK')"
     
     # Copy remainder of the repo
     COPY . /app
     
     # HF Spaces route traffic to <PORT>
     # Gradio should listen accordingly
     ENV PORT=<PORT> # <PORT> in README.md
     EXPOSE <PORT>
     
     # Run the app
     CMD ["python", "app.py"]

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Here are a few tips and best practices when dealing with HuggingFace Spaces:

• Spaces operate based off of the files in the main branch
• An access token may be required to push commits to HuggingFace Spaces
• A .gitignore file should be added to maintain repository orderliness (e.g., to ignore src/_outputs)
• Pin versions for numpy (e.g., <2), torch (e.g., ==2.2.2), and torchaudio (e.g., ==2.2.2) to avoid unexpected build issues caused by the latest versions of these packages

For more information, please refer to the offical document from Hugging Face about Spaces.

Accessing Within HARP

PyHARP apps deployed to HuggingFace will begin running at https://huggingface.co/spaces/<USERNAME>/<SPACE_NAME>. The shorthand <USERNAME>/<SPACE_NAME> can also be used within HARP to reference the endpoint. The two deployment methods above produce identical UIs and functionality.