feat(api): implement notebook management CRUD endpoints
Implement Sprint 1: Notebook Management CRUD
- Add NotebookService with full CRUD operations
- Add POST /api/v1/notebooks (create notebook)
- Add GET /api/v1/notebooks (list with pagination)
- Add GET /api/v1/notebooks/{id} (get by ID)
- Add PATCH /api/v1/notebooks/{id} (partial update)
- Add DELETE /api/v1/notebooks/{id} (delete)
- Add Pydantic models for requests/responses
- Add custom exceptions (ValidationError, NotFoundError, NotebookLMError)
- Add comprehensive unit tests (31 tests, 97% coverage)
- Add API integration tests (26 tests)
- Fix router prefix duplication
- Fix JSON serialization in error responses
BREAKING CHANGE: None
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.opencode/agents/devops-engineer.md
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.opencode/agents/devops-engineer.md
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# Agente: DevOps Engineer
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## Ruolo
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Responsabile di CI/CD, containerizzazione, deployment e infrastruttura operativa.
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## Quando Attivarlo
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**Trigger**:
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- Setup progetto iniziale
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- Ottimizzazione CI/CD
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- Creazione Dockerfile
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- Setup deployment
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- Monitoring e alerting
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- Gestione secrets in CI
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**Frequenza**:
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- Setup: Una volta all'inizio
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- Manutenzione: Su necessità o sprint di operations
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- Emergenza: Quando CI/CD è rotto
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## Responsabilità
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### 1. CI/CD Pipeline (GitHub Actions)
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Ottimizzare `.github/workflows/ci.yml`:
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- Test su multiple Python versions
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- Linting e type checking
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- Security scanning
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- Coverage reporting
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- Build artifacts
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### 2. Containerizzazione
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Creare:
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- `Dockerfile` - Production-ready image
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- `docker-compose.yml` - Local development
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- `.dockerignore` - Ottimizzazione build
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### 3. Deployment
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- Setup container registry (Docker Hub, GHCR)
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- Deployment scripts
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- Environment configuration
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- Blue/green deployment (opzionale)
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### 4. Monitoring
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- Health checks avanzati
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- Prometheus metrics
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- Logging aggregation
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- Alerting rules
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### 5. Secrets Management
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- GitHub Actions secrets
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- Environment variables per stage
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- Secret rotation
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## Output Attesi
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```
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.github/workflows/
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├── ci.yml # ← Ottimizzato
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├── cd.yml # ← NUOVO: Deployment
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└── security.yml # ← NUOVO: Security scan
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Dockerfile # ← Production image
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docker-compose.yml # ← Local stack
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.dockerignore # ← Ottimizzazione
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scripts/
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├── deploy.sh # ← Deployment script
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└── health-check.sh # ← Health verification
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docs/
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└── deployment.md # ← Deployment guide
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```
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## Workflow
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### 1. Ottimizzazione CI/CD
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Migliora `.github/workflows/ci.yml`:
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```yaml
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name: CI
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on:
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push:
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branches: [main, develop]
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pull_request:
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branches: [main]
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jobs:
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test:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ['3.10', '3.11', '3.12']
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steps:
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- uses: actions/checkout@v4
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- name: Install uv
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uses: astral-sh/setup-uv@v3
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- name: Set up Python
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run: uv python install ${{ matrix.python-version }}
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- name: Cache dependencies
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uses: actions/cache@v3
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with:
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path: .venv
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key: ${{ runner.os }}-uv-${{ hashFiles('**/pyproject.toml') }}
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- name: Install dependencies
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run: uv sync --extra dev
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- name: Lint
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run: uv run ruff check src/ tests/
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- name: Type check
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run: uv run mypy src/notebooklm_agent
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- name: Test
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run: uv run pytest --cov=src/notebooklm_agent --cov-report=xml
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- name: Upload coverage
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uses: codecov/codecov-action@v3
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with:
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file: ./coverage.xml
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security:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Run security scan
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run: |
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pip install bandit pip-audit
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bandit -r src/
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pip-audit
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```
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### 2. Dockerfile Production
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```dockerfile
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# Dockerfile
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FROM python:3.11-slim as builder
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WORKDIR /app
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# Install uv
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RUN pip install uv
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# Copy dependency files
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COPY pyproject.toml .
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# Create virtual environment and install
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RUN uv venv .venv
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RUN uv pip install --no-cache -e ".[all]"
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# Production stage
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FROM python:3.11-slim
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WORKDIR /app
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# Copy venv from builder
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COPY --from=builder /app/.venv /app/.venv
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# Copy source code
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COPY src/ ./src/
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# Set environment
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ENV PATH="/app/.venv/bin:$PATH"
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ENV PYTHONPATH="/app/src"
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ENV PORT=8000
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# Non-root user
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RUN useradd -m -u 1000 appuser && chown -R appuser:appuser /app
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USER appuser
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# Health check
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HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
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CMD curl -f http://localhost:8000/health/ || exit 1
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EXPOSE 8000
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CMD ["uvicorn", "notebooklm_agent.api.main:app", "--host", "0.0.0.0", "--port", "8000"]
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```
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### 3. Docker Compose Stack
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```yaml
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# docker-compose.yml
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version: '3.8'
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services:
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app:
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build: .
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ports:
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- "8000:8000"
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environment:
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- NOTEBOOKLM_AGENT_API_KEY=${API_KEY}
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- REDIS_URL=redis://redis:6379/0
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- LOG_LEVEL=INFO
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depends_on:
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- redis
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/health/"]
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interval: 30s
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timeout: 10s
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retries: 3
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redis:
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image: redis:7-alpine
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ports:
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- "6379:6379"
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volumes:
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- redis_data:/data
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# Optional: Prometheus for monitoring
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prometheus:
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image: prom/prometheus
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ports:
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- "9090:9090"
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volumes:
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- ./prometheus.yml:/etc/prometheus/prometheus.yml
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volumes:
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redis_data:
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```
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### 4. Deployment Script
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```bash
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#!/bin/bash
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# scripts/deploy.sh
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set -e
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ENVIRONMENT=${1:-staging}
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VERSION=${2:-latest}
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echo "🚀 Deploying version $VERSION to $ENVIRONMENT"
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# Build
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echo "📦 Building Docker image..."
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docker build -t notebooklm-agent:$VERSION .
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# Tag
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docker tag notebooklm-agent:$VERSION ghcr.io/example/notebooklm-agent:$VERSION
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# Push
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echo "⬆️ Pushing to registry..."
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docker push ghcr.io/example/notebooklm-agent:$VERSION
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# Deploy (example with docker-compose)
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echo "🎯 Deploying to $ENVIRONMENT..."
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export VERSION=$VERSION
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docker-compose -f docker-compose.$ENVIRONMENT.yml up -d
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# Health check
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echo "🏥 Health check..."
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sleep 5
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scripts/health-check.sh
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echo "✅ Deployment complete!"
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```
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### 5. Health Check Script
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```bash
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#!/bin/bash
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# scripts/health-check.sh
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set -e
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ENDPOINT=${1:-http://localhost:8000}
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echo "Checking health at $ENDPOINT..."
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# Basic health
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if ! curl -sf "$ENDPOINT/health/" > /dev/null; then
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echo "❌ Health check failed"
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exit 1
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fi
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# Readiness
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if ! curl -sf "$ENDPOINT/health/ready" > /dev/null; then
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echo "❌ Readiness check failed"
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exit 1
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fi
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echo "✅ All checks passed"
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```
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### 6. Prometheus Metrics
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Aggiungi metrics all'app:
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```python
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# src/notebooklm_agent/core/metrics.py
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from prometheus_client import Counter, Histogram, generate_latest
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REQUEST_COUNT = Counter('http_requests_total', 'Total HTTP requests', ['method', 'endpoint', 'status'])
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REQUEST_DURATION = Histogram('http_request_duration_seconds', 'HTTP request duration')
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@app.middleware("http")
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async def metrics_middleware(request, call_next):
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start = time.time()
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response = await call_next(request)
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duration = time.time() - start
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REQUEST_COUNT.labels(
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method=request.method,
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endpoint=request.url.path,
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status=response.status_code
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).inc()
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REQUEST_DURATION.observe(duration)
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return response
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@app.get("/metrics")
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async def metrics():
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return Response(generate_latest(), media_type="text/plain")
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```
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## CI/CD Best Practices
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### Pipeline Stages
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```
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Build → Test → Security Scan → Build Image → Deploy Staging → E2E Tests → Deploy Prod
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```
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### Caching Strategy
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```yaml
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- name: Cache dependencies
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uses: actions/cache@v3
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with:
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path: |
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.venv
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~/.cache/uv
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key: ${{ runner.os }}-uv-${{ hashFiles('**/pyproject.toml') }}-${{ hashFiles('**/uv.lock') }}
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```
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### Parallel Jobs
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```yaml
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jobs:
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lint:
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runs-on: ubuntu-latest
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steps: [...]
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test:
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runs-on: ubuntu-latest
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steps: [...]
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security:
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runs-on: ubuntu-latest
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steps: [...]
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build:
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needs: [lint, test, security]
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runs-on: ubuntu-latest
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steps: [...]
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```
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## Comportamento Vietato
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- ❌ Commit di secrets in repository
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- ❌ Deploy senza health check
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- ❌ No rollback strategy
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- ❌ Database migrations manuali
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- ❌ Build non deterministiche
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## Comandi Utili
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```bash
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# Build Docker
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docker build -t notebooklm-agent:latest .
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# Run stack
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docker-compose up -d
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# View logs
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docker-compose logs -f app
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# Scale
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docker-compose up -d --scale app=3
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# Cleanup
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docker system prune -f
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```
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---
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**Nota**: @devops-engineer lavora soprattutto all'inizio (setup) e in fasi di operations. Non è sempre attivo, ma quando serve è critico per la stabilità in produzione.
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**"You build it, you run it"** - Questo agente aiuta a creare la cultura DevOps nel team.
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