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Add Dockerfile, Cloud Build config, and deployment guide for Google C…#427

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ariaemaan wants to merge 2 commits intoWan-Video:mainfrom
ariaemaan:feat/gcloud-deployment
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Add Dockerfile, Cloud Build config, and deployment guide for Google C…#427
ariaemaan wants to merge 2 commits intoWan-Video:mainfrom
ariaemaan:feat/gcloud-deployment

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…loud

This commit introduces the necessary files and documentation to enable deployment of the Wan video generation application to Google Cloud Platform.

Key additions:

  • Dockerfile: Defines the container image, using an NVIDIA PyTorch base image and including special handling for flash-attn installation. It allows for configurable Gradio application startup.
  • cloudbuild.yaml: Provides a Google Cloud Build configuration to automate the Docker image build and push process to Google Artifact Registry.
  • DEPLOY_GCLOUD.md: A comprehensive guide detailing the steps to:
    • Set up prerequisites on GCP.
    • Configure and run Cloud Build.
    • Deploy the container to Cloud Run (with CPU and GPU options).
    • Deploy the container to Vertex AI Endpoints.
    • Troubleshoot common issues and select appropriate machine resources.

These changes aim to simplify and standardize the deployment process on Google Cloud, addressing potential issues related to dependencies and environment configuration.

google-labs-jules bot and others added 2 commits June 2, 2025 11:24
…loud

This commit introduces the necessary files and documentation to enable
deployment of the Wan video generation application to Google Cloud Platform.

Key additions:
- Dockerfile: Defines the container image, using an NVIDIA PyTorch base
  image and including special handling for flash-attn installation.
  It allows for configurable Gradio application startup.
- cloudbuild.yaml: Provides a Google Cloud Build configuration to automate
  the Docker image build and push process to Google Artifact Registry.
- DEPLOY_GCLOUD.md: A comprehensive guide detailing the steps to:
    - Set up prerequisites on GCP.
    - Configure and run Cloud Build.
    - Deploy the container to Cloud Run (with CPU and GPU options).
    - Deploy the container to Vertex AI Endpoints.
    - Troubleshoot common issues and select appropriate machine resources.

These changes aim to simplify and standardize the deployment process on
Google Cloud, addressing potential issues related to dependencies and
environment configuration.
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