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apiVersion: v1
kind: Pod
metadata:
  name: db
  labels:
    app: postgres
    role: database
    tier: back
spec:
  containers:

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# .trivyignore
# Trivy ignore file for known false positives or accepted risks

# Example: Ignore specific CVE that doesn't affect our use case
# CVE-2023-12345

# Example: Ignore vulnerabilities in specific packages
# pkg:pypi/package-name@version

# Note: Only ignore vulnerabilities after proper risk assessment

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name: CI Pipeline

on:
  push:
    branches: [ "main", "develop" ]

env:
  REGISTRY: docker.io
  IMAGE_NAME: ${{ secrets.DOCKERHUB_USERNAME }}/tech-stack-advisor

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name: CI Pipeline

on:
  push:
    branches: [ "main", "develop" ]

env:
  REGISTRY: docker.io
  IMAGE_NAME: ${{ secrets.DOCKERHUB_USERNAME }}/tech-stack-advisor

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version: '3.8'

services:
  tech-stack-advisor:
    build: .
    ports:
      - "7860:7860"
    environment:
      - ENV=production
    healthcheck:

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name: Goose AI PR Review  

on:
  pull_request:
    types: [opened, synchronize, reopened, labeled]
  workflow_dispatch:
  
permissions:
  contents: write
  pull-requests: write

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You are an expert DevOps engineer reviewing code changes for a machine learning application.

Focus your review on these key areas:

## 🐳 Docker & Containerization
- Dockerfile best practices and optimization
- Multi-stage builds and layer efficiency
- Security considerations (non-root users, minimal base images)
- Health checks and restart policies

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# syntax=docker/dockerfile:1
# BuildKit optimized Dockerfile with advanced caching and multi-arch support

ARG TARGETPLATFORM
ARG BUILDPLATFORM
ARG TARGETOS
ARG TARGETARCH

# Stage 1: Dependencies stage with cache mounts
FROM --platform=$BUILDPLATFORM python:3.11-slim AS dependencies

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# syntax=docker/dockerfile:1
# BuildKit optimized Dockerfile with advanced caching

# Stage 1: Dependencies stage with cache mounts
FROM python:3.11-slim AS dependencies

WORKDIR /app

# Use cache mount for apt packages
RUN --mount=type=cache,target=/var/cache/apt \

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# Multi-stage Dockerfile for Tech Stack Advisor ML App

# Stage 1: Builder stage for training the model
FROM python:3.11-slim AS builder

WORKDIR /app

# Install build dependencies
RUN apt-get update && apt-get install -y \
    gcc \