🛡️ Issue Prediction

Catch deployment errors before they reach production.
An intelligent pre-deployment analyzer that executes your project code in isolated sandboxes and uses Groq AI to detect, explain, and recommend fixes for deployment issues.

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🌟 Key Features

• 📦 Automated Zip Analysis: Upload project archives (.zip) for instant pre-flight validation.
• 🐳 Isolated Container Sandbox: Runs real build and dependency commands inside lightweight, restricted Docker containers.
• 🤖 AI-Powered Diagnostics: Integrated with Groq AI to translate complex build traces into human-readable root causes and actionable solutions.
• 🔍 Cross-File Configuration Checking: Detects mismatches across Dockerfiles, docker-compose configurations, and source files.
• 🔑 Environment Variable Audit: Scans code for environment variable references and checks against .env declarations.
• ⚡ Multi-Ecosystem Support: Validates Python (pip), Node.js (npm), Docker, and Docker Compose applications.

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🏗️ Architecture

flowchart LR
    subgraph Client Layer
        UI[Web Dashboard\nNginx :3000]
    end

    subgraph API Layer
        API[FastAPI Service\nUvicorn :8000]
        AUTH[JWT Authentication]
        DB[(SQLite / PostgreSQL)]
    end

    subgraph Execution & AI
        DS[(Docker Engine)]
        SB[Isolated Container Sandbox]
        AI[Groq Llama 3 AI Engine]
    end

    UI -->|Upload Zip / Auth| API
    API <--> DB
    API <--> AUTH
    API -->|Mount & Run| DS
    DS --> SB
    API -->|Logs & Context| AI

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🚀 Quick Start

📋 Prerequisites

• Docker & Docker Compose (version 2.0+)
• Groq API Key (Free key available at console.groq.com)

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📥 1. Clone & Set Up Environment

# Clone the repository
git clone https://github.com/dinu-vishruth/issue_prediction.git
cd issue_prediction

# Create environment configuration file
cp .env.example .env

Edit .env to configure your credentials:

GROQ_API_KEY=your_groq_api_key_here
JWT_SECRET=your_super_secret_jwt_key

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🐳 2. Run with Docker Compose

docker-compose up --build

Access the application services:

• 🌐 Web Interface: http://localhost:3000
• 📚 API Documentation (Swagger): http://localhost:8000/docs
• 🏥 Health Check Endpoint: http://localhost:8000/health

To run in the background (detached mode):

docker-compose up -d --build

To stop all running services:

docker-compose down -v

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🧪 Testing with the Sample Project

The repository includes a pre-configured sample project with intentional errors (sample_project/):

1. Package the sample project:

   cd sample_project
   zip -r ../sample_project.zip .
   cd ..

2. Upload sample_project.zip at http://localhost:3000.

Detected Intentional Errors:

1. ❌ Non-existent package in requirements.txt
2. 🔑 Missing environment variables (DB_PASSWORD, REDIS_URL)
3. 🔌 Port mismatch between Dockerfile (8000) and docker-compose.yml (5000)
4. ⚠️ Missing environment setting (POSTGRES_PASSWORD) in docker-compose.yml

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🛠️ Ecosystem Analysis Engine

Project Type	Analyzed File	Verification Executed
Python	requirements.txt	pip install --dry-run, pip check
Node.js	package.json	npm install --dry-run, npm ls
Docker	Dockerfile	docker build --no-cache
Docker Compose	docker-compose.yml	docker-compose config
Env Variables	.env, .py, .js	Static AST / Regex scan for missing definitions

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🔒 Security & Sandbox Guarantees

All user-submitted code is isolated using strict Docker container constraints:

• 🧱 Read-Only Mounts: Source code is mounted read-only during execution.
• ⚡ Resource Restrictions: Hard limits enforced per analysis run (512MB RAM, 0.5 CPU cores).
• 🌐 Network Isolation: Disables external internet access during command execution.
• ⏱️ Execution Timeouts: Prevents infinite loops or hung processes (30-second default limit).
• 🧹 Automatic Cleanup: Containers and temporary working directories are purged immediately post-analysis.

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💻 Local Development Setup

Backend (FastAPI)

cd backend
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
export GROQ_API_KEY="your_groq_api_key_here"
export JWT_SECRET="your_custom_secret"
uvicorn main:app --reload --host 0.0.0.0 --port 8000

Sandbox Image (Required for local backend runs)

docker build -t deploycheck-sandbox -f Dockerfile.sandbox .

Frontend (Static Web Server)

cd frontend
python3 -m http.server 3000

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🛰️ API Reference

POST /upload

Upload and analyze a project ZIP file.

• Request: multipart/form-data with file field (.zip format)
• Response: JSON payload containing detected files, raw output logs, detected issues, and AI recommendations.

GET /health

Returns backend operational status and Docker daemon availability.

• Response: {"status": "healthy", "docker_available": true}

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📄 License

Distributed under the MIT License. See LICENSE for more information.