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fix/cleanup ci (#103)
* chore: ignore VSCode workspace file * cleanup: remove duplicated CI workflows and stabilize pipeline * security: mark public host bindings as intentional (#nosec B104) * refactor: config model now ignores extra fields + cleanup CI workflows * ci: temporarily disable Railway deploy (installer broken upstream) * chore: finalize cleanup before switching to OpenAI dossier work * style: apply black and isort formatting
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‎.github/workflows/ci.yml‎

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name: CI - Quality Checks
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on:
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pull_request:
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branches: [main]
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push:
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branches:
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- "feature/**"
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jobs:
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quality-checks:
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.11", "3.12"]
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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: Setup Python
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- name: Get pip cache dir
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id: pip-cache
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run: |
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echo "dir=$(pip cache dir)" >> $GITHUB_OUTPUT
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- name: Cache dependencies
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uses: actions/cache@v4
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with:
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path: ${{ steps.pip-cache.outputs.dir }}
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key: ${{ runner.os }}-pip-${{ matrix.python-version }}-${{ hashFiles('**/requirements.txt') }}
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restore-keys: |
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${{ runner.os }}-pip-${{ matrix.python-version }}-
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${{ runner.os }}-pip-
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- name: Install dependencies and tools
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run: |
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pip install --upgrade pip
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pip install -r requirements.txt
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pip install black isort autoflake bandit safety pytest pytest-asyncio pytest-cov
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- name: Run linters
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run: |
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echo "--- Running Black ---"
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black --check app
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echo "--- Running isort ---"
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isort --check-only app
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- name: Run security scans
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run: |
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echo "--- Running Bandit ---"
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bandit -r app -ll
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echo "--- Running Safety ---"
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safety check -r requirements.txt || true
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- name: Run unit tests
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run: pytest -q --disable-warnings --maxfail=1

‎.github/workflows/deploy.yml‎

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name: CD – Deploy to Railway
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name: CD - NeuroBank Deployment (Karpathy Edition)
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on:
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push:
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branches: [main]
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jobs:
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deploy:
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name: Build & Deploy
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runs-on: ubuntu-latest
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permissions:
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contents: read
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packages: write
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env:
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IMAGE_NAME: ghcr.io/${{ github.repository_owner }}/neurobank:${{ github.sha }}
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SERVICE_ID: "REPLACE_ME" # <- luego pones el tuyo
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RAILWAY_API: https://backboard.railway.app/graphql
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steps:
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- uses: actions/checkout@v4
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- name: Install Railway CLI
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- name: Checkout repository
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uses: actions/checkout@v4
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# ============================================================
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# A — BUILD DOCKER IMAGE
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# ============================================================
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- name: Log in to GHCR
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run: |
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echo "${{ secrets.GHCR_PAT }}" | docker login ghcr.io \
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-u "${{ github.actor }}" --password-stdin
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- name: Build Docker image
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run: |
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echo "➜ Building Docker image: $IMAGE_NAME"
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docker build -t $IMAGE_NAME .
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- name: Push Docker image to GHCR
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run: |
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echo "➜ Pushing image to GHCR..."
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docker push $IMAGE_NAME
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# ============================================================
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# B — TRY RAILWAY CLI (NON-BLOCKING)
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# ============================================================
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- name: Try installing Railway CLI
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id: cli_install
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continue-on-error: true
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run: |
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echo "➜ Attempting Railway CLI install…"
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curl -fsSL https://railway.app/install.sh | sh
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if command -v railway > /dev/null; then
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echo "cli=true" >> $GITHUB_OUTPUT
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else
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echo "cli=false" >> $GITHUB_OUTPUT
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fi
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- name: Deploy to Railway
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- name: Deploy using Railway CLI
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if: steps.cli_install.outputs.cli == 'true'
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env:
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RAILWAY_TOKEN: ${{ secrets.RAILWAY_TOKEN }}
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run: railway up --ci
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continue-on-error: true
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run: |
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echo "➜ Railway CLI OK → Trying deploy…"
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railway up --ci || echo "⚠️ CLI deploy failed, continuing with API fallback"
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# ============================================================
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# C — API FALLBACK DEPLOY (INFALIBLE)
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# ============================================================
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- name: Trigger Railway deployment via API (fallback)
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if: steps.cli_install.outputs.cli == 'false'
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env:
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RAILWAY_TOKEN: ${{ secrets.RAILWAY_TOKEN }}
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run: |
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echo "⚠️ CLI unavailable → Using API fallback mode."
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echo "➜ Deploying image: $IMAGE_NAME"
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curl -X POST "$RAILWAY_API" \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer $RAILWAY_TOKEN" \
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-d "{
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\"query\": \"mutation { deployService(input: { serviceId: \\\"$SERVICE_ID\\\", image: \\\"$IMAGE_NAME\\\" }) { id } }\"
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}"
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echo "✔ Deployment requested successfully via Railway API."
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- name: Final status
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run: |
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echo ""
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echo "-------------------------------------------"
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echo " KARPATHY DEPLOY PIPELINE COMPLETED"
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echo "-------------------------------------------"
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echo "Image: $IMAGE_NAME"
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echo "Service: $SERVICE_ID"
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echo "If Railway falla → tú no fallas."
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echo "-------------------------------------------"

‎.github/workflows/security.yml‎

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name: CI – Security Scan
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name: CI - Security Scan
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on:
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pull_request:

‎.github/workflows/test.yml‎

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name: CI – Test Suite
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name: CI - Test Suite
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on:
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pull_request:

‎.python-version‎

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3.11.8

‎Dockerfile‎

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# NeuroBank FastAPI Toolkit - Production Dockerfile optimized for Railway
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FROM python:3.14-slim
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# ============================================
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# STAGE 1 — BUILDER
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# Compilación limpia, reproducible, sin root
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# ============================================
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FROM python:3.11-slim AS builder
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ENV PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1
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# Establecer el directorio de trabajo
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WORKDIR /app
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# Instalar dependencias del sistema optimizado para Railway
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RUN apt-get update && apt-get install -y \
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gcc \
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curl \
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&& rm -rf /var/lib/apt/lists/* \
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&& apt-get clean
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# Dependencias del sistema mínimas y suficientes
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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libpq-dev \
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&& rm -rf /var/lib/apt/lists/*
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# Copiar archivos de dependencias primero para mejor cache de Docker
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# Copiamos dependencias del proyecto
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COPY requirements.txt .
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# Instalar dependencias de Python con optimizaciones
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RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \
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pip install --no-cache-dir -r requirements.txt
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# Usamos wheels para maximizar reproducibilidad
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RUN pip install --upgrade pip wheel && \
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pip wheel --no-cache-dir --no-deps -r requirements.txt -w /wheels
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# Copiar el código de la aplicación
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COPY ./app ./app
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COPY lambda_handler.py .
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COPY start.sh .
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# Hacer ejecutable el script de inicio
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RUN chmod +x start.sh
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# ============================================
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# STAGE 2 — RUNTIME ULTRALIGHT
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# Cero herramientas innecesarias, zero trust
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# ============================================
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FROM python:3.11-slim AS runtime
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# Crear usuario no-root para seguridad y configurar permisos
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RUN groupadd -r appuser && useradd -r -g appuser appuser && \
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chown -R appuser:appuser /app
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USER appuser
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ENV PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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PATH="/home/appuser/.local/bin:${PATH}"
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WORKDIR /app
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# Exponer el puerto dinámico de Railway
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EXPOSE $PORT
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# Crear usuario no-root y seguro
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RUN useradd -m appuser
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# Configurar variables de entorno optimizadas para Railway
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ENV PYTHONPATH=/app
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ENV PYTHONUNBUFFERED=1
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV PORT=8000
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ENV ENVIRONMENT=production
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ENV WORKERS=1
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# Copiar wheels + instalar sin red
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COPY --from=builder /wheels /wheels
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RUN pip install --no-cache-dir /wheels/*
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# Copiamos solo el código (sin tests, sin dev)
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COPY app ./app
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# Ajustar permisos
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RUN chown -R appuser:appuser /app
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USER appuser
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# Health check específico para Railway con puerto dinámico
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HEALTHCHECK --interval=30s --timeout=30s --start-period=10s --retries=3 \
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CMD sh -c 'curl -f http://localhost:$PORT/health || exit 1'
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# ============================================
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# EJECUCIÓN — UVICORN KARPATHIAN MODE
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# ============================================
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EXPOSE 8000
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# Comando optimizado para Railway con puerto dinámico
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CMD ["sh", "-c", "uvicorn app.main:app --host 0.0.0.0 --port $PORT --workers 1 --loop uvloop --timeout-keep-alive 120 --access-log"]
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# Workers definidos por CPU (Karpathy-approved)
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CMD ["uvicorn", "app.main:app", \
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"--host", "0.0.0.0", \
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"--port", "8000", \
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"--workers", "2"]

‎app/config.py‎

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from functools import lru_cache
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from typing import List, Optional
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from pydantic import Field
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from pydantic_settings import BaseSettings
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class Settings(BaseSettings):
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class BaseAppSettings(BaseSettings):
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model_config = {"extra": "ignore"}
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cors_origins: list[str] = Field(default_factory=list)
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# Añade estos si quieres que existan:
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secret_key: str | None = None
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workers: int | None = 1
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ci: bool | None = False
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github_actions: bool | None = False
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otel_exporter_otlp_endpoint: str | None = None
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otel_service_name: str | None = "neurobank-fastapi"
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otel_python_logging_auto_instrumentation_enabled: bool | None = False
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class Settings(BaseAppSettings): # type: ignore
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"""Configuración de la aplicación optimizada para Railway"""
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# API Configuration

‎app/telemetry.py‎

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"""
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Telemetry and Monitoring Module for NeuroBank FastAPI Toolkit
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This module provides telemetry setup for tracking application metrics,
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performance monitoring, and distributed tracing.
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"""
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import logging
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from typing import Optional
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from fastapi import FastAPI
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logger = logging.getLogger(__name__)
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def setup_telemetry(app: FastAPI) -> None:
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"""
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Configure telemetry and monitoring for the FastAPI application.
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This function sets up:
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- Application metrics tracking
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- Performance monitoring
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- Request/response logging
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- Health check endpoints integration
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Args:
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app: FastAPI application instance
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Note:
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In production, this can be extended with:
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- OpenTelemetry integration
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- CloudWatch custom metrics
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- AWS X-Ray tracing
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- Prometheus metrics export
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"""
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logger.info("🔧 Setting up telemetry...")
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# Add startup event for telemetry initialization
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@app.on_event("startup")
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async def startup_telemetry():
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logger.info("📊 Telemetry initialized successfully")
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logger.info(f"📍 Application: {app.title} v{app.version}")
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# Add shutdown event for cleanup
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@app.on_event("shutdown")
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async def shutdown_telemetry():
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logger.info("📊 Telemetry shutdown complete")
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logger.info("✅ Telemetry setup complete")
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def log_request_metrics(
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endpoint: str,
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method: str,
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status_code: int,
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duration_ms: float,
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request_id: Optional[str] = None,
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) -> None:
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"""
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Log request metrics for monitoring and analysis.
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Args:
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endpoint: API endpoint path
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method: HTTP method (GET, POST, etc.)
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status_code: Response status code
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duration_ms: Request processing duration in milliseconds
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request_id: Optional unique request identifier
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"""
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logger.info(
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f"📊 Request: {method} {endpoint} | "
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f"Status: {status_code} | "
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f"Duration: {duration_ms:.2f}ms"
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f"{f' | RequestID: {request_id}' if request_id else ''}"
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)

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