Criminal Code AI - Indonesian Penal Code Legal Analysis

🤖 Advanced AI-powered legal analysis system for Indonesian Criminal Code (KUHP)

🌟 Features

🧠 Advanced AI Legal Analysis

Interactive Legal Consultation - Dynamic questioning system that adapts based on case complexity
Multi-Mode Analysis - Simple chat, interactive analysis, 8-item analysis, and comprehensive flowchart modes
Criminal Code Article Search - Intelligent search through Indonesian Penal Code articles
Case Law Integration - Analysis incorporating relevant Indonesian case law
Penalty Assessment - Automated calculation of potential sentences and legal consequences

An intelligent Next.js application that provides comprehensive criminal law analysis using AI and vector databases. Features interactive legal consultation, PDF document processing, and advanced case analysis frameworks.

📸 Screenshots

Interactive Analysis Mode

Progressive questioning system for systematic legal analysis

Simple Chat Mode

Basic legal consultation with AI-powered responses

Document Management

PDF upload, processing, and management interface

🚀 Quick Start

Prerequisites

Node.js 18.0 or higher
OpenAI API Key (for GPT-4 analysis)
Qdrant Vector Database (Docker recommended)

1. Clone the Repository

git clone https://github.com/yourusername/criminalcode-ai-nextjs.git
cd criminalcode-ai-nextjs

2. Install Dependencies

npm install

3. Set Up Environment Variables

Create a .env.local file in the root directory:

Required Variables

# OpenAI Configuration (Required)
OPENAI_API_KEY=your_openai_api_key

# Qdrant Vector Database Configuration (Required)
QDRANT_HOST=localhost
QDRANT_PORT=6333

# For Qdrant Cloud (Production - Optional)
# QDRANT_URL=https://your-cluster.qdrant.tech:6333
# QDRANT_API_KEY=your_qdrant_cloud_api_key

# Next.js Configuration (Required)
NEXTAUTH_SECRET=your_random_secret_string_32_chars
NEXTAUTH_URL=http://localhost:3000

Optional Variables (Production)

# Vercel Blob Storage (Optional - for production file storage)
# If not provided, uses local filesystem storage
BLOB_READ_WRITE_TOKEN=your_vercel_blob_token_here

# File Upload Limits (Optional)
MAX_FILE_SIZE=52428800  # 50MB default

# Development Settings (Optional)
NODE_ENV=development

Complete .env.local Example

# === REQUIRED CONFIGURATION ===

# OpenAI API Configuration
OPENAI_API_KEY=sk-proj-abcd1234...your-actual-openai-key

# Qdrant Vector Database (Local Development)
QDRANT_HOST=localhost
QDRANT_PORT=6333

# Next.js Security
NEXTAUTH_SECRET=super-secret-string-32-characters-long
NEXTAUTH_URL=http://localhost:3000

# === OPTIONAL CONFIGURATION ===

# Production Qdrant Cloud (uncomment for production)
# QDRANT_URL=https://your-cluster.qdrant.tech:6333
# QDRANT_API_KEY=qr_your-qdrant-cloud-api-key

# Vercel Blob Storage (uncomment for production)
# BLOB_READ_WRITE_TOKEN=vercel_blob_rw_your-token

# File Upload Settings
MAX_FILE_SIZE=52428800

# Environment
NODE_ENV=development

4. Vector Database Setup

Option A: Qdrant Cloud (Recommended for Production)

Create account at Qdrant Cloud
Create a new cluster
Get your cluster URL and API key
Update your .env.local with Qdrant Cloud credentials

Option B: Local Qdrant (Development)

# Start Qdrant with Docker
docker run -p 6333:6333 qdrant/qdrant

# Or with persistent storage
docker run -p 6333:6333 -v $(pwd)/qdrant_storage:/qdrant/storage qdrant/qdrant

# Verify Qdrant is running
curl http://localhost:6333/health

Option C: Docker Compose (Recommended for Local Development)

Create docker-compose.yml:

version: '3.8'
services:
  qdrant:
    image: qdrant/qdrant
    ports:
      - "6333:6333"
    volumes:
      - qdrant_data:/qdrant/storage
    environment:
      - QDRANT__SERVICE__HTTP_PORT=6333
volumes:
  qdrant_data:

Then run:

docker-compose up -d

5. Run the Development Server

npm run dev

6. Open Your Browser

Navigate to http://localhost:3000

You should see the Criminal Code AI interface ready for use! 🎉

🏛️ Features Overview

🔍 Dual Analysis Modes

Interactive Analysis Mode

Progressive questioning system that guides users through systematic legal analysis:

Stage 1: Initial assessment and potential criminal categories
Stage 2: Targeted fact gathering with critical questions
Stage 3: Narrowing down to specific articles with penalty assessment
Stage 4: Final determination with complete legal recommendations

Simple Chat Mode

Basic AI-powered legal consultation
Immediate responses for quick guidance
Enhanced with vector database context
General legal education and information

📄 Document Processing

PDF Upload: Process criminal code documents
Auto-Extraction: Automatically parse articles and chapters
Text Search: Find specific articles with PDF.js integration
Vector Storage: Store content for semantic search

🗄️ Vector Database Integration

Crime Name Master: Searchable criminal offense database
Criminal Code Articles: Full-text legal provisions
Case Law Master: Legal precedents and court decisions
Semantic Search: Find relevant content by meaning, not just keywords

🔧 Advanced Analysis Tools

8-Item Model: Structured criminal case framework
Constituent Element Flowcharts: Interactive decision trees
Multi-Database Search: Cross-reference multiple legal sources
Real-time Analysis: Instant legal insights with AI

🛠️ Technology Stack

Component	Technology	Purpose
Frontend	Next.js 15, React 18, Tailwind CSS	Modern, responsive UI with SSR
Backend	Node.js, API Routes	Server-side processing and APIs
AI/ML	OpenAI GPT-4, text-embedding-ada-002	Legal analysis and semantic embeddings
Vector DB	Qdrant (Rust-based)	High-performance semantic search and metadata storage
PDF Processing	PDF.js, react-pdf, pdf-lib	Document parsing, viewing, and text extraction
File Storage	Hybrid (Local/Vercel Blob)	Automatic storage detection and fallback
UI Components	Lucide Icons, Custom Components	Beautiful, accessible interface
Styling	Tailwind CSS, CSS Modules	Responsive design and dark mode
State Management	React Hooks, Context API	Client-side state and data management

📁 Project Structure

criminalcode-ai-nextjs/
├── src/
│   ├── app/                          # Next.js App Router
│   │   ├── api/
│   │   │   ├── chat/                # Simple chat API endpoint
│   │   │   ├── legal/
│   │   │   │   ├── analyze/         # Interactive analysis API
│   │   │   │   ├── article-content/ # Article content fetching API
│   │   │   │   └── pdfs/            # PDF management API
│   │   │   ├── upload/              # PDF upload processing API
│   │   │   └── init/                # Database initialization API
│   │   ├── globals.css              # Global styles and Tailwind
│   │   ├── layout.js                # App layout and metadata
│   │   └── page.js                  # Main application page
│   ├── components/
│   │   ├── ChatInterface.js         # Main chat interface with condensed responses
│   │   ├── PDFViewer.js             # In-browser PDF viewer with search
│   │   ├── PDFManager.js            # Document management interface
│   │   └── TabNavigation.js         # Tab navigation component
│   └── lib/
│       ├── legal/
│       │   ├── legalAnalyzer.js     # Core AI legal analysis logic
│       │   ├── documentProcessor.js # PDF processing and extraction
│       │   ├── eightItemModel.js    # 8-Item analysis framework
│       │   └── constituentFlowchart.js # Decision tree logic
│       ├── storage/
│       │   └── fileStorage.js       # Hybrid storage system (Local/Blob)
│       └── vector/
│           └── qdrant.js            # Vector database operations
├── public/
│   ├── uploads/                     # Local file storage directory
│   ├── pdf.worker.min.js            # PDF.js worker file
│   ├── pdf.worker.min.mjs           # PDF.js worker (ES module)
│   └── ...                         # Static assets
├── docs/
│   ├── images/                      # Screenshots and documentation
│   └── ...                         # Project documentation
├── .env.local                       # Environment configuration
├── vercel.json                      # Vercel deployment configuration
├── package.json                     # Dependencies and scripts
├── tailwind.config.js               # Tailwind CSS configuration
├── next.config.mjs                  # Next.js configuration
└── README.md                        # Project documentation

Key Features by Directory

`/src/app/api/`

Hybrid storage detection - Automatic Vercel Blob vs Local storage
PDF processing pipeline - Upload → Parse → Vector storage
Interactive analysis engine - Multi-stage legal consultation
Article content retrieval - Dynamic article fetching with metadata

`/src/components/`

Condensed response UI - Smart content parsing with expandable details
In-browser PDF viewer - Search, navigate, and highlight articles
Real-time file management - Upload progress, enable/disable documents
Responsive design - Mobile-friendly interface with dark mode

`/src/lib/`

AI-powered analysis - GPT-4 integration with legal frameworks
Vector search engine - Semantic search through legal documents
Hybrid file storage - Automatic detection and fallback mechanisms
Document processing - PDF parsing with article extraction

🔍 API Reference

Legal Analysis API

Endpoint: POST /api/legal/analyze

Interactive Mode

const response = await fetch('/api/legal/analyze', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    mode: 'interactive',
    data: {
      description: 'A person was found with a stolen motorcycle...'
    },
    conversationHistory: [
      'Previous user input',
      'Previous AI response'
    ]
  })
});

Simple Chat

const response = await fetch('/api/chat', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    message: 'What constitutes theft under criminal law?',
    useAdvancedAnalysis: true
  })
});

PDF Management API

Upload: POST /api/upload List: GET /api/legal/pdfs Delete: DELETE /api/legal/pdfs

Article Content API

Fetch Article: POST /api/legal/article-content

{
  "articleNumber": "362",
  "enabledPDFs": ["filename.pdf"]
}

📖 Usage Guide

1. First Time Setup

Start the application following the Quick Start guide
Upload your criminal code PDF documents via the Document Management tab
Enable the PDFs you want to use for analysis
Switch to the Legal Analysis tab to begin consultations

2. Using Interactive Analysis Mode

Choose "Interactive Analysis Mode" for systematic legal consultation
Describe your case in detail
Answer the AI's targeted questions one by one
Receive progressive analysis until final determination

3. Using Simple Chat Mode

Choose "Simple Chat Mode" for quick consultations
Ask general legal questions or describe cases
Get immediate AI-powered responses
Click article badges to view full legal texts

4. Document Management

Upload PDF files (max 50MB each)
Enable/disable documents for analysis
Delete unnecessary files
View upload status and file information

5. Article Viewing

Click any article badge (e.g., "Article 362") in AI responses
View detailed legal provisions and penalties
Use "Open & Search PDF" to jump to exact article location
Access original PDF with highlighted search terms

🔧 Configuration

Environment Variables

Development Setup (.env.local)

# === REQUIRED CONFIGURATION ===

# OpenAI API Configuration
OPENAI_API_KEY=sk-proj-your-actual-openai-api-key

# Qdrant Vector Database (Local Development)
QDRANT_HOST=localhost
QDRANT_PORT=6333

# Next.js Security Configuration
NEXTAUTH_SECRET=your-secure-random-32-character-string
NEXTAUTH_URL=http://localhost:3000

# === OPTIONAL CONFIGURATION ===

# File Upload Settings
MAX_FILE_SIZE=52428800  # 50MB default

# Development Mode
NODE_ENV=development

Production Setup (.env.local)

# === REQUIRED CONFIGURATION ===

# OpenAI API Configuration
OPENAI_API_KEY=sk-proj-your-actual-openai-api-key

# Qdrant Cloud (Production)
QDRANT_URL=https://your-cluster.qdrant.tech:6333
QDRANT_API_KEY=qr_your-qdrant-cloud-api-key

# Next.js Security Configuration
NEXTAUTH_SECRET=your-secure-random-32-character-string
NEXTAUTH_URL=https://your-domain.vercel.app

# === OPTIONAL CONFIGURATION ===

# Vercel Blob Storage (for file uploads)
BLOB_READ_WRITE_TOKEN=vercel_blob_rw_your-token

# File Upload Settings
MAX_FILE_SIZE=52428800  # 50MB default

# Production Mode
NODE_ENV=production

Storage Configuration

The system uses a hybrid storage approach:

Local Development

Files: Stored in public/uploads/ directory
Metadata: Stored in Qdrant vector database
Auto-detection: No BLOB token = local storage

Production (Vercel)

With BLOB_READ_WRITE_TOKEN: Uses Vercel Blob Storage
Without BLOB token: Falls back to local storage
Metadata: Always stored in Qdrant vector database

Qdrant Setup Options

Option 1: Local Docker Setup

# Basic setup
docker run -p 6333:6333 qdrant/qdrant

# With persistent storage
docker run -p 6333:6333 -v $(pwd)/qdrant_storage:/qdrant/storage qdrant/qdrant

Option 2: Docker Compose Setup

version: '3.8'
services:
  qdrant:
    image: qdrant/qdrant
    ports:
      - "6333:6333"
    volumes:
      - qdrant_data:/qdrant/storage
    environment:
      - QDRANT__SERVICE__HTTP_PORT=6333
volumes:
  qdrant_data:

Option 3: Qdrant Cloud Setup (Recommended for Production)

Sign up at Qdrant Cloud
Create a new cluster
Copy the cluster URL and API key
Update your .env.local with the cloud credentials

🔐 Legal Disclaimers

⚖️ Important Notice: This system is designed for:

Legal education and research purposes
Academic analysis and study
Professional legal assistance (not replacement)
Case preparation and preliminary analysis

This system does NOT provide legal advice. Always consult qualified legal counsel for actual legal matters.

🚦 Troubleshooting

Common Issues

"Failed to connect to Qdrant"

Ensure Qdrant is running on port 6333
Check firewall settings
Verify QDRANT_HOST and QDRANT_PORT in .env.local

"OpenAI API Error"

Verify your OPENAI_API_KEY is valid
Check your OpenAI account has credits
Ensure API key has GPT-4 access

"PDF Upload Failed"

Check file size (max 50MB)
Ensure PDF is not password protected
Verify upload directory permissions

"Article not found in PDF"

Try uploading the correct criminal code document
Check if PDF contains the article number
Enable more PDF documents in Document Management

Development Issues

Port 3000 already in use

npx kill-port 3000
# or
lsof -ti:3000 | xargs kill

Clear Qdrant database

curl -X DELETE http://localhost:6333/collections/criminal_code_articles
curl -X DELETE http://localhost:6333/collections/crime_name_master

🤝 Contributing

We welcome contributions! Please follow these steps:

Fork the repository
Create a feature branch
```
git checkout -b feature/amazing-feature
```
Make your changes
Commit your changes
```
git commit -m 'Add amazing feature'
```
Push to the branch
```
git push origin feature/amazing-feature
```
Open a Pull Request

Development Guidelines

Follow existing code style
Add tests for new features
Update documentation as needed
Ensure all tests pass before submitting

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🌟 Future Enhancements

Multi-language support (Japanese criminal code)
Advanced UI for 8-Item Model and Flowcharts
Case law precedent integration
Document comparison and analysis
Export to legal document formats
Mobile app development
Integration with legal practice management systems
Batch document processing capabilities

📞 Support

Documentation: Check this README and inline code comments
Issues: Use GitHub Issues for bug reports and feature requests
Questions: Start a GitHub Discussion for usage questions

Built with ⚖️ for legal professionals, researchers, and students

Criminal Code AI - Making legal analysis accessible through artificial intelligence

Name		Name	Last commit message	Last commit date
Latest commit History 54 Commits
.github/workflows		.github/workflows
.vercel		.vercel
docs/images		docs/images
public		public
src		src
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
eslint.config.mjs		eslint.config.mjs
jsconfig.json		jsconfig.json
next.config.mjs		next.config.mjs
package-lock.json		package-lock.json
package.json		package.json
postcss.config.mjs		postcss.config.mjs
vercel.json		vercel.json

License

doni404/criminalcode-ai-nextjs

Folders and files

Latest commit

History

Repository files navigation

Criminal Code AI - Indonesian Penal Code Legal Analysis

🌟 Features

🧠 Advanced AI Legal Analysis

📸 Screenshots

Interactive Analysis Mode

Simple Chat Mode

Document Management

🚀 Quick Start

Prerequisites

1. Clone the Repository

2. Install Dependencies

3. Set Up Environment Variables

Required Variables

Optional Variables (Production)

Complete .env.local Example

4. Vector Database Setup

Option A: Qdrant Cloud (Recommended for Production)

Option B: Local Qdrant (Development)

Option C: Docker Compose (Recommended for Local Development)

5. Run the Development Server

6. Open Your Browser

🏛️ Features Overview

🔍 Dual Analysis Modes

Interactive Analysis Mode

Simple Chat Mode

📄 Document Processing

🗄️ Vector Database Integration

🔧 Advanced Analysis Tools

🛠️ Technology Stack

📁 Project Structure

Key Features by Directory

/src/app/api/

/src/components/

/src/lib/

🔍 API Reference

Legal Analysis API

Interactive Mode

Simple Chat

PDF Management API

Article Content API

📖 Usage Guide

1. First Time Setup

2. Using Interactive Analysis Mode

3. Using Simple Chat Mode

4. Document Management

5. Article Viewing

🔧 Configuration

Environment Variables

Development Setup (.env.local)

Production Setup (.env.local)

Storage Configuration

Local Development

Production (Vercel)

Qdrant Setup Options

Option 1: Local Docker Setup

Option 2: Docker Compose Setup

Option 3: Qdrant Cloud Setup (Recommended for Production)

🔐 Legal Disclaimers

🚦 Troubleshooting

Common Issues

"Failed to connect to Qdrant"

"OpenAI API Error"

"PDF Upload Failed"

"Article not found in PDF"

Development Issues

Port 3000 already in use

Clear Qdrant database

🤝 Contributing

Development Guidelines

📄 License

🌟 Future Enhancements

📞 Support

About

Resources

`/src/app/api/`

`/src/components/`

`/src/lib/`

Packages