d3975d7a29
* increment line limit to 81 * increment line length to 82 * increment line length to 83 * increment line length to 84 * increment line length to 85 * increment line length to 86 * increment line length to 87 * increment line length to 88
98 lines
3.1 KiB
Python
98 lines
3.1 KiB
Python
# # Generate: Fooocus
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#
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# This example demonstrates how to set up and run a web server using the Modal library with Fooocus as the frontend.
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# Fooocus provides a beginner-friendly interface to work with the SDXL 1.0 model for image generation tasks.
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# The script includes the setup of a Docker image, initialization of Fooocus, and launching a web server with GPU support.
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#
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# ## Basic setup
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import modal
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# To create an image that can run Fooocus, we start from an official NVIDIA base image and then add Python
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# and a few system packages.
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#
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# We then download the Fooocus repository.
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image = (
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modal.Image.from_registry("nvidia/cuda:12.3.1-base-ubuntu22.04", add_python="3.10")
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.apt_install(
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"software-properties-common",
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"git",
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"git-lfs",
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"coreutils",
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"aria2",
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"libgl1",
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"libglib2.0-0",
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"curl",
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"wget",
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"libsm6",
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"libxrender1",
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"libxext6",
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"ffmpeg",
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)
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.run_commands("git clone https://github.com/lllyasviel/Fooocus.git")
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)
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# ## Initialize Fooocus
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#
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# We are not limited to running shell commands and package installers in the image setup.
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# We can also run Python functions by defining them in our code and passing them to the `run_function` method.
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#
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# This function installs Fooocus's dependencies and downloads the SDXL 1.0 model to the container image.
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#
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# This all happens at the time the container image is defined, so that the image is ready to run Fooocus when it is deployed.
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def init_Fooocus():
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import os
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import subprocess
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# change the working directory to the Fooocus directory and install the required Python packages from the requirements file.
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os.chdir("/Fooocus")
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os.system("pip install -r requirements_versions.txt")
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# change the directory to the models' checkpoints and download the SDXL 1.0 model using wget.
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os.chdir("./models/checkpoints")
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subprocess.run(
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"wget -O juggernautXL_v8Rundiffusion.safetensors 'https://huggingface.co/lllyasviel/fav_models/resolve/main/fav/juggernautXL_v8Rundiffusion.safetensors'",
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shell=True,
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)
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GPU_CONFIG = "T4"
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image = image.run_function(init_Fooocus, gpu=GPU_CONFIG)
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# ## Run Fooocus
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#
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# The `run` function is decorated with `app.function` to define it as a Modal function.
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# The `web_server` decorator indicates that this function will serve a web application on the specified port.
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# We increase the startup timeout to three minutes to account for the time it takes to load the model and start the server.
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app = modal.App("Fooocus", image=image)
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PORT = 8000
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MINUTES = 60
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@app.function(gpu=GPU_CONFIG, timeout=10 * MINUTES)
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@modal.web_server(port=PORT, startup_timeout=3 * MINUTES)
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def run():
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import os
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import subprocess
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# change the working directory to the Fooocus directory.
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os.chdir("/Fooocus")
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# launch the Fooocus application using a subprocess that listens on the specified port
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subprocess.Popen(
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[
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"python",
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"launch.py",
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"--listen",
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"0.0.0.0",
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"--port",
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str(PORT),
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"--always-high-vram",
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]
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)
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