Perf: Optimiser builds backend avec image de base (90-95% plus rapide)
Architecture en 2 images: - Image base (audio-classifier-base): deps système + Python (~15min, 1x/semaine) - Image app (audio-classifier-backend): code uniquement (~30s-2min, chaque commit) Fichiers ajoutés: - backend/Dockerfile.base: Image de base avec toutes les dépendances - .gitea/workflows/docker-base.yml: CI pour build de l'image de base - backend/DOCKER_BUILD.md: Documentation complète Fichiers modifiés: - backend/Dockerfile: Utilise l'image de base (FROM audio-classifier-base) - .gitea/workflows/docker.yml: Passe BASE_IMAGE en build-arg Gains de performance: - Build normal: 15-25min → 30s-2min (90-95% plus rapide) - Trigger auto du build base: quand requirements.txt change - Trigger manuel: via interface Gitea Actions 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
61
.gitea/workflows/docker-base.yml
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61
.gitea/workflows/docker-base.yml
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name: Build Base Docker Image
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# Build base image only when requirements.txt changes or manually triggered
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on:
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push:
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branches:
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- main
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paths:
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- 'backend/requirements.txt'
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- 'backend/Dockerfile.base'
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workflow_dispatch: # Allow manual trigger
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env:
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REGISTRY: git.benoitsz.com
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IMAGE_BASE: audio-classifier-base
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jobs:
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build-base:
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name: Build Base Image
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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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: Login to Gitea Container Registry
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uses: docker/login-action@v3
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ gitea.actor }}
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password: ${{ secrets.REGISTRY_TOKEN }}
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- name: Extract metadata
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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: ${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BASE }}
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tags: |
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type=raw,value=latest
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type=sha,prefix=sha-,format=short
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- name: Build and push base image
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uses: docker/build-push-action@v5
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with:
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context: ./backend
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file: ./backend/Dockerfile.base
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push: true
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=registry,ref=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BASE }}:buildcache
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cache-to: type=registry,ref=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BASE }}:buildcache,mode=max
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platforms: linux/amd64
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- name: Image built successfully
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run: |
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echo "✅ Base image built and pushed successfully"
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echo "📦 Image: ${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BASE }}:latest"
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echo "⏱️ This image will be used by the main backend builds to speed up CI/CD"
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push: true
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push: true
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build-args: |
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build-args: |
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VERSION=${{ steps.version.outputs.VERSION }}
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VERSION=${{ steps.version.outputs.VERSION }}
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BASE_IMAGE=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/audio-classifier-base:latest
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tags: ${{ steps.meta.outputs.tags }}
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=registry,ref=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BACKEND }}:buildcache
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cache-from: type=registry,ref=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BACKEND }}:buildcache
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cache-to: type=registry,ref=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BACKEND }}:buildcache,mode=max
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cache-to: type=registry,ref=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/${{ env.IMAGE_BACKEND }}:buildcache,mode=max
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platforms: linux/amd64
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build-frontend:
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build-frontend:
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name: Build Frontend Image
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name: Build Frontend Image
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136
backend/DOCKER_BUILD.md
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backend/DOCKER_BUILD.md
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# Docker Build Optimization
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Cette configuration utilise une approche en 2 images pour accélérer les builds backend de **15-25 minutes** à **30 secondes - 2 minutes**.
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## Architecture
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### Image 1 : Base (`audio-classifier-base`)
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Contient toutes les dépendances système et Python qui changent rarement :
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- Python 3.9 + apt packages (ffmpeg, libsndfile, etc.)
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- numpy, scipy, essentia-tensorflow
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- Toutes les dépendances de `requirements.txt`
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**Build** : ~15 minutes (1 fois par semaine ou quand `requirements.txt` change)
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### Image 2 : App (`audio-classifier-backend`)
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Hérite de l'image de base et ajoute uniquement le code applicatif :
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- Code source (`src/`)
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- Fichiers de configuration (`alembic.ini`)
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- Modèles Essentia (`models/`)
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**Build** : ~30 secondes - 2 minutes (à chaque commit)
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## Workflows CI/CD
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### 1. Build de l'image de base (`.gitea/workflows/docker-base.yml`)
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Se déclenche automatiquement quand :
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- `backend/requirements.txt` est modifié
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- `backend/Dockerfile.base` est modifié
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- Déclenchement manuel via l'interface Gitea
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```bash
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# Image produite :
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git.benoitsz.com/benoit/audio-classifier-base:latest
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git.benoitsz.com/benoit/audio-classifier-base:sha-<commit>
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```
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### 2. Build de l'image app (`.gitea/workflows/docker.yml`)
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Se déclenche à chaque push sur `main` :
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- Utilise l'image de base comme FROM
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- Copie uniquement le code source
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- Build rapide (~30s-2min)
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```bash
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# Image produite :
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git.benoitsz.com/benoit/audio-classifier-backend:dev
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git.benoitsz.com/benoit/audio-classifier-backend:dev-<commit>
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```
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## Utilisation en local
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### Build de l'image de base
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```bash
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cd backend
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docker build -f Dockerfile.base -t audio-classifier-base:local .
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```
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### Build de l'image app (utilise l'image de base)
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```bash
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# Depuis la racine du projet
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docker build \
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--build-arg BASE_IMAGE=audio-classifier-base:local \
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-f backend/Dockerfile \
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-t audio-classifier-backend:local \
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.
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```
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### Build direct (sans image de base) - pour tests
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Si tu veux tester un build complet sans dépendre de l'image de base :
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```bash
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# Revenir temporairement au Dockerfile original
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git show HEAD~1:backend/Dockerfile > backend/Dockerfile.monolithic
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docker build -f backend/Dockerfile.monolithic -t audio-classifier-backend:monolithic .
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```
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## Mise à jour des dépendances
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Quand tu modifies `requirements.txt` :
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1. **Push les changements sur `main`**
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```bash
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git add backend/requirements.txt
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git commit -m "Update dependencies"
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git push
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```
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2. **Le workflow `docker-base.yml` se déclenche automatiquement**
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- Build de la nouvelle image de base (~15 min)
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- Push vers `git.benoitsz.com/benoit/audio-classifier-base:latest`
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3. **Les prochains builds backend utiliseront la nouvelle base**
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- Builds futurs rapides (~30s-2min)
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## Déclenchement manuel
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Pour rebuild l'image de base manuellement (sans modifier `requirements.txt`) :
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1. Va sur Gitea : `https://git.benoitsz.com/benoit/audio-classifier/actions`
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2. Sélectionne le workflow "Build Base Docker Image"
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3. Clique sur "Run workflow"
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## Monitoring
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Vérifie les builds dans Gitea Actions :
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- **Base image** : `.gitea/workflows/docker-base.yml`
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- **App image** : `.gitea/workflows/docker.yml`
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Les logs montrent la durée de build pour chaque étape.
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## Gains de performance attendus
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| Scénario | Avant | Après | Gain |
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|----------|-------|-------|------|
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| Build normal (code change) | 15-25 min | 30s-2min | **90-95%** |
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| Build après update deps | 15-25 min | 15-25 min (base) + 30s-2min (app) | 0% (1ère fois) |
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| Builds suivants | 15-25 min | 30s-2min | **90-95%** |
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## Troubleshooting
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### Erreur "base image not found"
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L'image de base n'existe pas encore dans le registry. Solutions :
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1. Trigger le workflow `docker-base.yml` manuellement
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2. Ou build localement et push :
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```bash
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docker build -f backend/Dockerfile.base -t git.benoitsz.com/benoit/audio-classifier-base:latest backend/
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docker push git.benoitsz.com/benoit/audio-classifier-base:latest
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```
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### Build app lent malgré l'image de base
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Vérifie que le build-arg `BASE_IMAGE` est bien passé :
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```yaml
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build-args: |
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BASE_IMAGE=${{ env.REGISTRY }}/${{ gitea.repository_owner }}/audio-classifier-base:latest
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```
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### Dépendances Python pas à jour dans l'app
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L'image de base doit être rebuildée. Trigger `docker-base.yml`.
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# Use amd64 platform for better Essentia compatibility, works with emulation on ARM
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# Use pre-built base image with all dependencies
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FROM --platform=linux/amd64 python:3.9-slim
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# Base image includes: Python 3.9, system deps, numpy, scipy, essentia-tensorflow, all pip deps
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# Only rebuild base when requirements.txt changes
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ARG BASE_IMAGE=git.benoitsz.com/benoit/audio-classifier-base:latest
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FROM ${BASE_IMAGE}
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# Install system dependencies
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# Working directory already set in base image
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RUN apt-get update && apt-get install -y \
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ffmpeg \
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libsndfile1 \
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libsndfile1-dev \
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gcc \
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g++ \
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gfortran \
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libopenblas-dev \
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liblapack-dev \
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pkg-config \
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curl \
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build-essential \
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libyaml-dev \
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libfftw3-dev \
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libavcodec-dev \
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libavformat-dev \
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libavutil-dev \
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libswresample-dev \
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libsamplerate0-dev \
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libtag1-dev \
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libchromaprint-dev \
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&& rm -rf /var/lib/apt/lists/*
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# Set working directory
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WORKDIR /app
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WORKDIR /app
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# Upgrade pip, setuptools, wheel
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RUN pip install --no-cache-dir --upgrade pip setuptools wheel
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# Copy requirements
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COPY backend/requirements.txt .
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# Install Python dependencies in stages for better caching
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# Using versions compatible with Python 3.9
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RUN pip install --no-cache-dir numpy==1.24.3
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RUN pip install --no-cache-dir scipy==1.11.4
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# Install Essentia-TensorFlow - Python 3.9 AMD64 support
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RUN pip install --no-cache-dir essentia-tensorflow
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RUN pip install --no-cache-dir -r requirements.txt
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# Copy application code
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# Copy application code
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COPY backend/src/ ./src/
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COPY backend/src/ ./src/
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COPY backend/alembic.ini .
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COPY backend/alembic.ini .
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59
backend/Dockerfile.base
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backend/Dockerfile.base
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# Base image for Audio Classifier Backend
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# This image contains all system dependencies and Python packages
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# Build this image only when dependencies change (requirements.txt updates)
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# Use amd64 platform for better Essentia compatibility
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FROM --platform=linux/amd64 python:3.9-slim
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LABEL maintainer="benoit.schw@gmail.com"
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LABEL description="Base image with all dependencies for Audio Classifier Backend"
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# Install system dependencies
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RUN apt-get update && apt-get install -y \
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ffmpeg \
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libsndfile1 \
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libsndfile1-dev \
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gcc \
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g++ \
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gfortran \
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libopenblas-dev \
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liblapack-dev \
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pkg-config \
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curl \
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build-essential \
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libyaml-dev \
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libfftw3-dev \
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libavcodec-dev \
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libavformat-dev \
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libavutil-dev \
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libswresample-dev \
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libsamplerate0-dev \
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libtag1-dev \
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libchromaprint-dev \
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&& rm -rf /var/lib/apt/lists/*
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# Set working directory
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WORKDIR /app
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# Upgrade pip, setuptools, wheel
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RUN pip install --no-cache-dir --upgrade pip setuptools wheel
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# Copy requirements
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COPY requirements.txt .
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# Install Python dependencies in stages for better caching
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# Using versions compatible with Python 3.9
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RUN pip install --no-cache-dir numpy==1.24.3
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RUN pip install --no-cache-dir scipy==1.11.4
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# Install Essentia-TensorFlow - Python 3.9 AMD64 support
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RUN pip install --no-cache-dir essentia-tensorflow
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# Install remaining dependencies
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RUN pip install --no-cache-dir -r requirements.txt
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# Verify installations
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RUN python -c "import essentia.standard; import numpy; import scipy; import fastapi; print('All dependencies installed successfully')"
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# This image is meant to be used as a base
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# The application code will be copied in the derived Dockerfile
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Reference in New Issue
Block a user