🛡️ Supplier Risk Detector - Walmart Hackathon 2025

🚀 AI-Powered Supply Chain Risk Assessment & Geospatial Analytics Platform

Revolutionizing supplier risk management through intelligent automation, real-time analysis, and interactive mapping

🔗 Live Demo • 📖 Documentation • 🚀 Quick Start

🎯 Project Overview

The Supplier Risk Detector is a comprehensive AI-powered platform designed for Walmart's supply chain operations, featuring advanced risk assessment capabilities, real-time analytics, and geospatial visualization. Built for the Walmart Hackathon 2025, this solution addresses critical supply chain challenges through intelligent automation and data-driven insights.

🌟 Key Highlights

🤖 AI-Powered Risk Assessment: Advanced RAG (Retrieval-Augmented Generation) system using LangGraph and OpenAI
🗺️ Interactive Geospatial Analytics: Real-time mapping with 50 Walmart centers and 100+ supplier locations
🎙️ Voice-Enabled Interactions: Natural language processing for hands-free operation
📊 Real-Time Dashboard: Comprehensive analytics with risk metrics and alerts
🔄 Automated Web Scraping: Intelligent data collection from supplier websites
🔐 Enterprise Security: Clerk authentication with role-based access control

🏗️ Architecture Overview

graph TB
    subgraph "Frontend Layer"
        A[Next.js 15 Dashboard] 
        B[Streamlit Map App]
        C[Real-time Chat Interface]
    end
    
    subgraph "API Layer"
        D[FastAPI Backend]
        E[LangGraph Agent System]
        F[Voice Processing API]
    end
    
    subgraph "AI/ML Layer"
        G[OpenAI GPT-4]
        H[Pinecone Vector Store]
        I[Firecrawl Web Scraper]
    end
    
    subgraph "Data Layer"
        J[PostgreSQL Database]
        K[Prisma ORM]
        L[SQLite Development]
    end
    
    A --> D
    B --> L
    C --> D
    D --> E
    E --> G
    E --> H
    E --> I
    D --> J
    J --> K

� Dependency Graphs

🎨 Frontend Dependencies (Next.js)

graph TD
    A[Next.js 15.3.4] --> B[React 18]
    A --> C[TypeScript 5.x]
    A --> D[Tailwind CSS 3.4.17]
    
    E[Authentication] --> F[clerk/nextjs 6.22.0]
    F --> G[User Management]
    F --> H[Session Handling]
    
    I[UI Components] --> J[headlessui/react 1.7.18]
    I --> K[heroicons/react 2.1.1]
    I --> L[lucide-react 0.525.0]
    
    M[Animations] --> N[framer-motion 10.16.5]
    
    O[Data Visualization] --> P[chart.js 4.5.0]
    O --> Q[recharts 2.8.0]
    
    R[Content Rendering] --> S[react-markdown 9.0.1]
    R --> T[remark-gfm 4.0.0]
    
    U[HTTP Client] --> V[axios 1.6.2]
    
    W[Notifications] --> X[react-hot-toast 2.4.1]
    
    Y[Utilities] --> Z[clsx 2.0.0]
    Y --> AA[date-fns 2.30.0]
    
    style A fill:#000,stroke:#fff,stroke-width:3px,color:#fff
    style F fill:#4338ca,stroke:#fff,stroke-width:2px,color:#fff
    style P fill:#10b981,stroke:#fff,stroke-width:2px,color:#fff
    style V fill:#ef4444,stroke:#fff,stroke-width:2px,color:#fff

⚙️ Backend Dependencies (FastAPI + AI)

graph TD
    A[FastAPI 0.104+] --> B[uvicorn 0.24+]
    A --> C[python-dotenv 1.0+]
    A --> D[python-multipart]
    
    E[AI Framework] --> F[langgraph 0.2.16+]
    E --> G[langchain 0.2.16+]
    E --> H[langchain-core 0.2.39+]
    E --> I[langchain-openai 0.1.25+]
    E --> J[langchain-community 0.0.20]
    
    K[OpenAI Services] --> L[openai 1.45+]
    L --> M[GPT-4 API]
    L --> N[Whisper API]
    L --> O[Text-to-Speech]
    
    P[Web Scraping] --> Q[firecrawl-py 0.0.20]
    P --> R[requests 2.31+]
    P --> S[beautifulsoup4 4.12.2+]
    P --> T[lxml 4.9.0+]
    
    U[Data Processing] --> V[pandas 2.0+]
    U --> W[numpy 1.24+]
    
    X[Vector Database] --> Y[pinecone 3.2.2]
    
    Z[Database ORM] --> AA[prisma 0.11+]
    Z --> BB[psycopg2]
    
    CC[Async Support] --> DD[asyncio 3.4.3]
    CC --> EE[aiohttp 3.9.0]
    
    FF[Validation] --> GG[pydantic 2.5.0]
    
    style A fill:#009688,stroke:#fff,stroke-width:3px,color:#fff
    style F fill:#673ab7,stroke:#fff,stroke-width:2px,color:#fff
    style L fill:#ff9800,stroke:#fff,stroke-width:2px,color:#fff
    style Y fill:#e91e63,stroke:#fff,stroke-width:2px,color:#fff
    style AA fill:#2196f3,stroke:#fff,stroke-width:2px,color:#fff

🗺️ Map Application Dependencies (Streamlit)

graph TD
    A[Streamlit 1.28+] --> B[Interactive Web App]
    A --> C[Real-time Updates]
    
    D[Mapping Core] --> E[folium]
    D --> F[streamlit-folium]
    F --> G[Map Rendering]
    F --> H[User Interactions]
    
    I[Geospatial] --> J[Distance Calculations]
    I --> K[Path Routing]
    I --> L[Coordinate Processing]
    
    M[Database] --> N[SQLite Local]
    M --> O[PostgreSQL Production]
    O --> P[Neon Cloud]
    
    Q[Data Processing] --> R[pandas]
    Q --> S[numpy]
    
    T[Environment] --> U[python-dotenv]
    
    V[Database Setup] --> W[setup_database.py]
    V --> X[setup_neon.py]
    
    Y[Core Features] --> Z[Risk Visualization]
    Y --> AA[Center-Supplier Mapping]
    Y --> BB[Interactive Filtering]
    Y --> CC[Distance Analytics]
    
    style A fill:#ff4b4b,stroke:#fff,stroke-width:3px,color:#fff
    style E fill:#2e8b57,stroke:#fff,stroke-width:2px,color:#fff
    style O fill:#1e88e5,stroke:#fff,stroke-width:2px,color:#fff
    style Z fill:#ff6b35,stroke:#fff,stroke-width:2px,color:#fff

�🚀 Features

🎯 Core Risk Assessment Engine

🔍 Intelligent Web Analysis

Automated Website Scraping: Advanced Firecrawl integration for comprehensive data extraction
Multi-depth Analysis: Configurable crawling depth for thorough supplier evaluation
Real-time Processing: Asynchronous processing for rapid risk assessment
Content Normalization: Smart URL handling and content standardization

🧠 AI-Powered Risk Scoring

Multi-factor Analysis: Financial, operational, compliance, and sustainability metrics
Dynamic Risk Classification: High/Medium/Low risk categorization with detailed explanations
Contextual Recommendations: Actionable insights based on identified risk factors
Historical Trend Analysis: Pattern recognition for predictive risk modeling

🗺️ Advanced Geospatial Analytics

📍 Interactive Risk Mapping

50 Walmart Distribution Centers: Complete network visualization with hierarchical display
100+ Supplier Locations: Comprehensive supplier network with risk-based color coding
Smart Path Visualization: Purple routing lines to nearest Walmart centers with real-time distance calculations
Interactive Risk Filtering: Dynamic filtering by risk levels (High/Medium/Low)

🛣️ Intelligent Routing System

Nearest Center Calculation: Automated routing to closest Walmart distribution center
Distance Analytics: Real-time distance display directly on map paths (km measurements)
One-Click Analysis: Instant supplier analysis with path visualization on marker selection
Multi-style Mapping: OpenStreetMap, CartoDB Positron, and Dark Matter themes

💬 Conversational AI Interface

🎙️ Voice-Enabled Interactions

Speech-to-Text Processing: OpenAI Whisper integration for natural voice input
Text-to-Speech Output: AI-generated audio responses for hands-free operation
Multilingual Support: Global supplier communication capabilities
Context-Aware Responses: Supplier-specific conversation history and insights

💭 Smart Chat System

RAG-Enhanced Responses: Vector store integration for accurate, contextual answers
Supplier-Specific Context: Personalized conversations based on analysis history
Real-time Query Processing: Instant responses to complex supplier inquiries
Source Attribution: Transparent citation of information sources

📊 Enterprise Dashboard

📈 Real-Time Analytics

Risk Metrics Overview: High-level KPIs with trend indicators
Alert Management System: Proactive risk notifications and escalations
Historical Analysis Tracking: Complete audit trail of supplier assessments
Comparative Risk Analysis: Side-by-side supplier risk comparisons

🎛️ Advanced Controls

Multi-tab Navigation: Organized access to Overview, Suppliers, and Risk Analysis
Dynamic Filtering: Real-time data filtering and sorting capabilities
Export Functionality: Comprehensive reporting and data export options
User Management: Role-based access control with Clerk authentication

🛠️ Tech Stack

🎨 Frontend Technologies

# Core Framework
Next.js 15.3.4              # React-based web framework
TypeScript 5.x               # Type-safe JavaScript
Tailwind CSS 3.4.17         # Utility-first CSS framework

# UI Components & Libraries
@clerk/nextjs 6.22.0        # Authentication & user management
@headlessui/react 1.7.18    # Accessible UI components
@heroicons/react 2.1.1      # Beautiful SVG icons
framer-motion 10.16.5       # Smooth animations
lucide-react 0.525.0        # Additional icon library

# Data Visualization
chart.js 4.5.0              # Chart rendering
recharts 2.8.0              # React chart components
react-markdown 9.0.1        # Markdown rendering
remark-gfm 4.0.0            # GitHub Flavored Markdown

# Geospatial Mapping (Streamlit App)
streamlit 1.28+             # Interactive web apps
folium                      # Interactive maps
streamlit-folium            # Streamlit-Folium integration

⚙️ Backend Technologies

# Core Framework
FastAPI 0.104+              # Modern Python web framework
uvicorn 0.24+               # ASGI server
python-dotenv 1.0+          # Environment management

# AI & Machine Learning
langgraph 0.2.16+           # Advanced AI agent workflows
langchain 0.2.16+           # LLM application framework
langchain-core 0.2.39+      # Core LangChain components
langchain-openai 0.1.25+    # OpenAI integration
openai 1.45+                # OpenAI API client

# Web Scraping & Data Processing
firecrawl-py 0.0.20         # Advanced web scraping
requests 2.31+              # HTTP client
beautifulsoup4 4.12.2+      # HTML parsing
pandas 2.0+                 # Data manipulation
numpy 1.24+                 # Numerical computing

# Vector Database & Storage
pinecone 3.2.2              # Vector database for embeddings
langchain-community 0.0.20  # Community integrations

🗄️ Database & ORM

# Database Systems
PostgreSQL 13+              # Production database
SQLite 3.x                  # Development database
prisma 0.11+                # Modern database toolkit
psycopg2                    # PostgreSQL adapter

# Database Management
@prisma/client 6.11.0       # Prisma client for TypeScript
prisma-client-py            # Prisma client for Python

🐳 DevOps & Deployment

# Containerization
Docker                      # Container platform
Docker Compose              # Multi-container orchestration

# Development Tools
ESLint 8.x                  # JavaScript linting
TypeScript 5.x              # Static type checking
PostCSS 8.4+                # CSS processing
Autoprefixer 10.4+          # CSS vendor prefixing

🚀 Quick Start

📋 Prerequisites

# Required Software
Node.js 18+ (with npm/yarn)
Python 3.8+
PostgreSQL 13+ (or SQLite for development)
Docker & Docker Compose (optional)
Git

🔑 Environment Setup

Clone the Repository

git clone https://github.com/prash08484/Supplier-Risk-Detector2.git
cd Supplier-Risk-Detector2

Environment Configuration

# Create environment file
cp .env.example .env

# Configure required variables
OPENAI_API_KEY=your_openai_api_key
FIRECRAWL_API_KEY=your_firecrawl_api_key
PINECONE_API_KEY=your_pinecone_api_key
PINECONE_INDEX_NAME=supplier-risk-index
DATABASE_URL=postgresql://user:password@localhost:5432/supplier_risk_db
NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=your_clerk_publishable_key
CLERK_SECRET_KEY=your_clerk_secret_key

🏃‍♂️ Running the Application

Option 1: Docker Deployment (Recommended)

# Start all services
docker-compose up -d

# Access applications
Frontend Dashboard: http://localhost:3000
Backend API: http://localhost:8000
API Documentation: http://localhost:8000/docs

Option 2: Manual Development Setup

Backend Setup:

cd backend

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Database setup
prisma generate
prisma db push

# Start backend server
uvicorn main:app --reload --host 0.0.0.0 --port 8000

Frontend Setup:

cd frontend

# Install dependencies
npm install

# Start development server
npm run dev

Geospatial Map Application:

cd map

# Install Python dependencies
pip install -r requirements.txt

# Configure database (choose one)
# Option 1: PostgreSQL (Production)
python setup_neon.py

# Option 2: SQLite (Development)
python setup_database.py

# Launch Streamlit app
streamlit run app.py

📱 Application Interfaces

🎯 Main Dashboard (http://localhost:3000)

Overview Tab: Risk metrics, recent alerts, and supplier summaries
Suppliers Tab: Supplier management and new analysis forms
Risk Analysis Tab: Detailed risk assessment interface with AI chat

🗺️ Geospatial Analytics (Streamlit App)

Interactive Map: 50 Walmart centers + 100+ suppliers with risk visualization
Path Analytics: Real-time routing to nearest distribution centers
Risk Filtering: Dynamic filtering by risk levels
Distance Calculations: Precise measurements displayed on map paths

🔧 API Documentation (http://localhost:8000/docs)

Interactive API Explorer: Complete FastAPI documentation
Real-time Testing: Built-in API testing interface
Schema Validation: Comprehensive request/response schemas

🎛️ Key Features Deep Dive

🔍 Supplier Risk Analysis Engine

The core analysis engine leverages advanced AI to evaluate supplier websites:

# Example analysis workflow
supplier_data = await analyze_supplier({
    "url": "https://supplier-website.com",
    "include_links": True,
    "max_depth": 2
})

# Returns comprehensive risk assessment
{
    "supplier_name": "Example Corp",
    "risk_score": 75,
    "risk_level": "Medium",
    "key_findings": [
        "Strong financial performance",
        "Limited ESG reporting",
        "Compliance gaps in data privacy"
    ],
    "recommendations": [
        "Request detailed ESG metrics",
        "Verify GDPR compliance status",
        "Establish quarterly financial reviews"
    ]
}

🗺️ Geospatial Risk Mapping

Interactive mapping with real-time risk visualization:

# Map features showcase
- 🏪 50 Walmart Distribution Centers (Blue markers)
- 🏬 100+ Supplier Locations (Risk-coded: Red/Yellow/Green)
- 🛣️ Smart routing to nearest centers (Purple paths)
- 📏 Real-time distance calculations (Kilometers)
- 🎯 One-click supplier analysis
- 🎨 Multiple map themes (OpenStreetMap, CartoDB, etc.)

💬 AI-Powered Chat Interface

Natural language interaction with supplier data:

// Voice + Text chat capabilities
const chatResponse = await sendChatMessage({
    url: "supplier-url",
    question: "What are the main compliance risks?",
    chat_history: previousMessages
});

// Returns AI-generated insights
{
    "answer": "Based on analysis, main compliance risks include...",
    "sources": ["website-section-1", "website-section-2"],
    "confidence": 0.92
}

📊 Database Schema

🏗️ Core Data Models

model Supplier {
  id           String    @id @default(cuid())
  url          String?   @unique
  name         String    @default("Unknown Supplier")
  riskScore    String    @default("0")
  summary      String    @default("")
  flags        String[]  @default([])
  analysisData Json?
  createdAt    DateTime  @default(now())
  updatedAt    DateTime  @updatedAt
  chats        ChatLog[]
}

model ChatLog {
  id        String    @id @default(cuid())
  url       String?
  question  String
  answer    String
  sources   String[]
  createdAt DateTime  @default(now())
  supplier  Supplier? @relation(fields: [url], references: [url])
}

🔒 Security Features

🛡️ Authentication & Authorization

Clerk Integration: Enterprise-grade authentication
Role-Based Access: Hierarchical permission system
Session Management: Secure token handling
API Security: JWT-based API authentication

🔐 Data Protection

Environment Variables: Secure configuration management
Database Encryption: Encrypted data at rest
HTTPS Enforcement: Secure data transmission
Input Validation: Comprehensive request sanitization

🧪 Testing Strategy

🔬 Comprehensive Testing Suite

# Backend Testing
cd backend
pytest tests/ -v --cov=.

# Frontend Testing
cd frontend
npm test
npm run test:e2e

# Integration Testing
docker-compose -f docker-compose.test.yml up --abort-on-container-exit

📈 Performance Optimization

⚡ Speed Enhancements

Async Processing: Non-blocking operations throughout
Vector Store Caching: Optimized similarity searches
Database Indexing: Strategic database optimization
CDN Integration: Fast static asset delivery

📊 Monitoring & Analytics

Health Check Endpoints: Comprehensive system monitoring
Performance Metrics: Real-time performance tracking
Error Tracking: Detailed error reporting and analysis
Usage Analytics: User behavior insights

🚀 Deployment Guide

🌐 Production Deployment

Docker Production Setup

# Production environment
docker-compose -f docker-compose.prod.yml up -d

# SSL/HTTPS configuration
# Configure reverse proxy (nginx/caddy)
# Set up domain and certificates

Cloud Deployment Options

Frontend: Vercel, Netlify, AWS Amplify
Backend: Railway, Render, AWS ECS, Google Cloud Run
Database: Neon, Supabase, AWS RDS, Google Cloud SQL
Vector Store: Pinecone (managed service)

🤝 Contributing

🛠️ Development Workflow

Fork & Clone: Fork the repository and clone locally
Branch Strategy: Create feature branches from main
Code Standards: Follow ESLint/Prettier configurations
Testing: Ensure comprehensive test coverage
Documentation: Update relevant documentation
Pull Request: Submit detailed pull requests

📝 Code Style Guidelines

# Frontend linting
npm run lint
npm run format

# Backend formatting
black backend/
flake8 backend/
mypy backend/

🎯 Walmart Hackathon 2025 - Solution Impact

🏆 Business Value Proposition

💰 Cost Reduction

Automated Risk Assessment: 90% reduction in manual analysis time
Proactive Risk Mitigation: Early warning system prevents costly supply chain disruptions
Operational Efficiency: Streamlined supplier onboarding and monitoring

📊 Enhanced Decision Making

Data-Driven Insights: AI-powered recommendations for supplier selection
Real-Time Risk Monitoring: Continuous assessment of supplier health
Geospatial Intelligence: Location-based risk analysis and optimization

🌍 Scalability & Innovation

Global Supply Chain Support: Multi-language and multi-region capabilities
AI-First Architecture: Cutting-edge technology stack for future expansion
Open Integration: API-first design for seamless third-party integrations

🎯 Competitive Advantages

🚀 Speed: Real-time analysis vs. traditional weeks-long assessments
🎯 Accuracy: AI-powered insights vs. manual subjective evaluations
📊 Comprehensiveness: Multi-dimensional risk analysis vs. single-metric approaches
🗺️ Visualization: Interactive geospatial analytics vs. static reports
💬 Accessibility: Natural language interface vs. complex dashboards

📞 Support & Contact

🆘 Getting Help

📚 Documentation: Project Wiki
🐛 Bug Reports: Issue Tracker
💬 Discussions: GitHub Discussions
📧 Contact: Project Team

🏅 Team Credits

Walmart Hackathon 2025 Team

🎯 Project Lead: SupritR21
🤝 Collaborator: Prash08484
🤝 Collaborator: Ashutosh123

📄 License

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

🌟 Star this repository if you find it helpful!

Made with ❤️ for Walmart Hackathon 2025

🔗 Live Demo • 📖 Documentation • 🚀 Quick Start • 🤝 Contributing

Name		Name	Last commit message	Last commit date
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backend		backend
docker		docker
frontend		frontend
map		map
.gitignore		.gitignore
README.md		README.md

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