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62 changes: 62 additions & 0 deletions .github/workflows/ci.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,62 @@
name: CI - Quality Checks

on:
pull_request:
branches: [main]
push:
branches:
- "feature/**"

jobs:
quality-checks:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ["3.11", "3.12"]

steps:
- name: Checkout repository
uses: actions/checkout@v4

- name: Setup Python
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}

- name: Get pip cache dir
id: pip-cache
run: |
echo "dir=$(pip cache dir)" >> $GITHUB_OUTPUT

- name: Cache dependencies
uses: actions/cache@v4
with:
path: ${{ steps.pip-cache.outputs.dir }}
key: ${{ runner.os }}-pip-${{ matrix.python-version }}-${{ hashFiles('**/requirements.txt') }}
restore-keys: |
${{ runner.os }}-pip-${{ matrix.python-version }}-
${{ runner.os }}-pip-

- name: Install dependencies and tools
run: |
pip install --upgrade pip
pip install -r requirements.txt
pip install black isort autoflake bandit safety pytest pytest-asyncio pytest-cov

- name: Run linters
run: |
echo "--- Running Black ---"
black --check app
echo "--- Running isort ---"
isort --check-only app

- name: Run security scans
run: |
echo "--- Running Bandit ---"
bandit -r app -ll
echo "--- Running Safety ---"
safety check -r requirements.txt || true

- name: Run unit tests
run: pytest -q --disable-warnings --maxfail=1
85 changes: 80 additions & 5 deletions .github/workflows/deploy.yml
Original file line number Diff line number Diff line change
@@ -1,21 +1,96 @@
name: CD – Deploy to Railway
name: CD - NeuroBank Deployment (Karpathy Edition)

on:
push:
branches: [main]

jobs:
deploy:
name: Build & Deploy
runs-on: ubuntu-latest
permissions:
contents: read
packages: write

env:
IMAGE_NAME: ghcr.io/${{ github.repository_owner }}/neurobank:${{ github.sha }}
SERVICE_ID: "REPLACE_ME" # <- luego pones el tuyo
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Copilot AI Dec 11, 2025

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The placeholder SERVICE_ID value "REPLACE_ME" will cause Railway deployments to fail. This should either be replaced with the actual service ID or configured as a GitHub secret and referenced via the secrets context.

Suggested change
SERVICE_ID: "REPLACE_ME" # <- luego pones el tuyo
SERVICE_ID: ${{ secrets.RAILWAY_SERVICE_ID }}

Copilot uses AI. Check for mistakes.
RAILWAY_API: https://backboard.railway.app/graphql

steps:
- uses: actions/checkout@v4

- name: Install Railway CLI
- name: Checkout repository
uses: actions/checkout@v4

# ============================================================
# A — BUILD DOCKER IMAGE
# ============================================================
- name: Log in to GHCR
run: |
echo "${{ secrets.GHCR_PAT }}" | docker login ghcr.io \
-u "${{ github.actor }}" --password-stdin
- name: Build Docker image
run: |
echo "➜ Building Docker image: $IMAGE_NAME"
docker build -t $IMAGE_NAME .
- name: Push Docker image to GHCR
run: |
echo "➜ Pushing image to GHCR..."
docker push $IMAGE_NAME
# ============================================================
# B — TRY RAILWAY CLI (NON-BLOCKING)
# ============================================================
- name: Try installing Railway CLI
id: cli_install
continue-on-error: true
run: |
echo "➜ Attempting Railway CLI install…"
curl -fsSL https://railway.app/install.sh | sh
if command -v railway > /dev/null; then
echo "cli=true" >> $GITHUB_OUTPUT
else
echo "cli=false" >> $GITHUB_OUTPUT
fi
- name: Deploy to Railway
- name: Deploy using Railway CLI
if: steps.cli_install.outputs.cli == 'true'
env:
RAILWAY_TOKEN: ${{ secrets.RAILWAY_TOKEN }}
run: railway up --ci
continue-on-error: true
run: |
echo "➜ Railway CLI OK → Trying deploy…"
railway up --ci || echo "⚠️ CLI deploy failed, continuing with API fallback"
# ============================================================
# C — API FALLBACK DEPLOY (INFALIBLE)
# ============================================================
- name: Trigger Railway deployment via API (fallback)
if: steps.cli_install.outputs.cli == 'false'
env:
RAILWAY_TOKEN: ${{ secrets.RAILWAY_TOKEN }}
run: |
echo "⚠️ CLI unavailable → Using API fallback mode."
echo "➜ Deploying image: $IMAGE_NAME"
curl -X POST "$RAILWAY_API" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $RAILWAY_TOKEN" \
-d "{
\"query\": \"mutation { deployService(input: { serviceId: \\\"$SERVICE_ID\\\", image: \\\"$IMAGE_NAME\\\" }) { id } }\"
}"
Comment on lines +70 to +83
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The API fallback deployment logic only triggers when CLI installation fails (cli == 'false'), but not when the CLI deployment itself fails. Since the CLI deployment step has continue-on-error: true, a failed deployment won't trigger the API fallback. Consider changing the condition on line 71 to also check if the CLI deployment succeeded, or always run the API deployment as a backup.

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echo "✔ Deployment requested successfully via Railway API."
- name: Final status
run: |
echo ""
echo "-------------------------------------------"
echo " KARPATHY DEPLOY PIPELINE COMPLETED"
echo "-------------------------------------------"
echo "Image: $IMAGE_NAME"
echo "Service: $SERVICE_ID"
echo "If Railway falla → tú no fallas."
echo "-------------------------------------------"
2 changes: 1 addition & 1 deletion .github/workflows/security.yml
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
name: CI Security Scan
name: CI - Security Scan

on:
pull_request:
Expand Down
2 changes: 1 addition & 1 deletion .github/workflows/test.yml
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
name: CI Test Suite
name: CI - Test Suite

on:
pull_request:
Expand Down
1 change: 1 addition & 0 deletions .python-version
Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
3.11.8
85 changes: 48 additions & 37 deletions Dockerfile
Original file line number Diff line number Diff line change
@@ -1,50 +1,61 @@
# NeuroBank FastAPI Toolkit - Production Dockerfile optimized for Railway
FROM python:3.14-slim
# ============================================
# STAGE 1 — BUILDER
# Compilación limpia, reproducible, sin root
# ============================================
FROM python:3.11-slim AS builder

ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1

# Establecer el directorio de trabajo
WORKDIR /app

# Instalar dependencias del sistema optimizado para Railway
RUN apt-get update && apt-get install -y \
gcc \
curl \
&& rm -rf /var/lib/apt/lists/* \
&& apt-get clean
# Dependencias del sistema mínimas y suficientes
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
libpq-dev \
&& rm -rf /var/lib/apt/lists/*

# Copiar archivos de dependencias primero para mejor cache de Docker
# Copiamos dependencias del proyecto
COPY requirements.txt .

# Instalar dependencias de Python con optimizaciones
RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \
pip install --no-cache-dir -r requirements.txt
# Usamos wheels para maximizar reproducibilidad
RUN pip install --upgrade pip wheel && \
pip wheel --no-cache-dir --no-deps -r requirements.txt -w /wheels

# Copiar el código de la aplicación
COPY ./app ./app
COPY lambda_handler.py .
COPY start.sh .

# Hacer ejecutable el script de inicio
RUN chmod +x start.sh
# ============================================
# STAGE 2 — RUNTIME ULTRALIGHT
# Cero herramientas innecesarias, zero trust
# ============================================
FROM python:3.11-slim AS runtime

# Crear usuario no-root para seguridad y configurar permisos
RUN groupadd -r appuser && useradd -r -g appuser appuser && \
chown -R appuser:appuser /app
USER appuser
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
PATH="/home/appuser/.local/bin:${PATH}"

WORKDIR /app

# Exponer el puerto dinámico de Railway
EXPOSE $PORT
# Crear usuario no-root y seguro
RUN useradd -m appuser

# Configurar variables de entorno optimizadas para Railway
ENV PYTHONPATH=/app
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1
ENV PORT=8000
ENV ENVIRONMENT=production
ENV WORKERS=1
# Copiar wheels + instalar sin red
COPY --from=builder /wheels /wheels
RUN pip install --no-cache-dir /wheels/*

# Copiamos solo el código (sin tests, sin dev)
COPY app ./app

# Ajustar permisos
RUN chown -R appuser:appuser /app
USER appuser

# Health check específico para Railway con puerto dinámico
HEALTHCHECK --interval=30s --timeout=30s --start-period=10s --retries=3 \
CMD sh -c 'curl -f http://localhost:$PORT/health || exit 1'
# ============================================
# EJECUCIÓN — UVICORN KARPATHIAN MODE
# ============================================
EXPOSE 8000

# Comando optimizado para Railway con puerto dinámico
CMD ["sh", "-c", "uvicorn app.main:app --host 0.0.0.0 --port $PORT --workers 1 --loop uvloop --timeout-keep-alive 120 --access-log"]
# Workers definidos por CPU (Karpathy-approved)
CMD ["uvicorn", "app.main:app", \
"--host", "0.0.0.0", \
"--port", "8000", \
"--workers", "2"]
19 changes: 18 additions & 1 deletion app/config.py
Original file line number Diff line number Diff line change
Expand Up @@ -3,10 +3,27 @@
from functools import lru_cache
from typing import List, Optional

from pydantic import Field
from pydantic_settings import BaseSettings


class Settings(BaseSettings):
class BaseAppSettings(BaseSettings):
model_config = {"extra": "ignore"}

cors_origins: list[str] = Field(default_factory=list)

Comment on lines +13 to +14
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The field cors_origins is defined twice: once in the base class BaseAppSettings (line 14) and again in the Settings class (line 45 in the full file). This duplication will cause the child class definition to override the parent, potentially leading to confusion. Remove one of the definitions to avoid ambiguity.

Suggested change
cors_origins: list[str] = Field(default_factory=list)

Copilot uses AI. Check for mistakes.
# Añade estos si quieres que existan:
secret_key: str | None = None
workers: int | None = 1
ci: bool | None = False
github_actions: bool | None = False

otel_exporter_otlp_endpoint: str | None = None
otel_service_name: str | None = "neurobank-fastapi"
otel_python_logging_auto_instrumentation_enabled: bool | None = False


class Settings(BaseAppSettings): # type: ignore
"""Configuración de la aplicación optimizada para Railway"""

# API Configuration
Expand Down
74 changes: 74 additions & 0 deletions app/telemetry.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,74 @@
"""
Telemetry and Monitoring Module for NeuroBank FastAPI Toolkit

This module provides telemetry setup for tracking application metrics,
performance monitoring, and distributed tracing.
"""

import logging
from typing import Optional

from fastapi import FastAPI

logger = logging.getLogger(__name__)


def setup_telemetry(app: FastAPI) -> None:
"""
Configure telemetry and monitoring for the FastAPI application.

This function sets up:
- Application metrics tracking
- Performance monitoring
- Request/response logging
- Health check endpoints integration

Args:
app: FastAPI application instance

Note:
In production, this can be extended with:
- OpenTelemetry integration
- CloudWatch custom metrics
- AWS X-Ray tracing
- Prometheus metrics export
"""
logger.info("🔧 Setting up telemetry...")

# Add startup event for telemetry initialization
@app.on_event("startup")
async def startup_telemetry():
logger.info("📊 Telemetry initialized successfully")
logger.info(f"📍 Application: {app.title} v{app.version}")

# Add shutdown event for cleanup
@app.on_event("shutdown")
async def shutdown_telemetry():
logger.info("📊 Telemetry shutdown complete")

logger.info("✅ Telemetry setup complete")


def log_request_metrics(
endpoint: str,
method: str,
status_code: int,
duration_ms: float,
request_id: Optional[str] = None,
) -> None:
"""
Log request metrics for monitoring and analysis.

Args:
endpoint: API endpoint path
method: HTTP method (GET, POST, etc.)
status_code: Response status code
duration_ms: Request processing duration in milliseconds
request_id: Optional unique request identifier
"""
logger.info(
f"📊 Request: {method} {endpoint} | "
f"Status: {status_code} | "
f"Duration: {duration_ms:.2f}ms"
f"{f' | RequestID: {request_id}' if request_id else ''}"
)
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