- Add Dockerfile with minimal setup (supervisor, tailscale) - Add start.sh bootstrap script for container initialization - Add Gitea workflow for automated Docker image builds - Add comprehensive RUNPOD_TEMPLATE.md documentation - Add bootstrap-venvs.sh for Python venv health checks This enables deployment of the AI orchestrator on RunPod using: - Minimal Docker image (~2-3GB) for fast deployment - Network volume for models and data persistence (~80-200GB) - Automated builds on push to main or version tags - Full Tailscale VPN integration - Supervisor process management
59 lines
1.5 KiB
YAML
59 lines
1.5 KiB
YAML
name: Build and Push RunPod Docker Image
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on:
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push:
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branches:
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- main
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tags:
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- 'v*'
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pull_request:
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branches:
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- main
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Log in to Docker Hub
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if: github.event_name != 'pull_request'
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uses: docker/login-action@v3
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with:
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username: ${{ secrets.DOCKER_USERNAME }}
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password: ${{ secrets.DOCKER_PASSWORD }}
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- name: Extract metadata (tags, labels)
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id: meta
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uses: docker/metadata-action@v5
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with:
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images: ${{ secrets.DOCKER_USERNAME }}/runpod-ai-orchestrator
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tags: |
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type=ref,event=branch
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type=ref,event=pr
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type=semver,pattern={{version}}
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type=semver,pattern={{major}}.{{minor}}
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type=semver,pattern={{major}}
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type=sha,prefix={{branch}}-
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type=raw,value=latest,enable={{is_default_branch}}
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- name: Build and push Docker image
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uses: docker/build-push-action@v5
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with:
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context: .
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file: ./Dockerfile
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platforms: linux/amd64
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push: ${{ github.event_name != 'pull_request' }}
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=gha
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cache-to: type=gha,mode=max
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- name: Image digest
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run: echo ${{ steps.meta.outputs.digest }}
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