Auction Aggregator with React, Express, and GPT-4o Valuation

Project Overview

I built Auction Scout to solve a real problem for a friend trying to find good deals at local auctions without spending hours browsing multiple websites. It pulls auction data from different sources, shows everything in one clean interface, and uses AI to give you instant price estimates on items you're interested in. Whether you're hunting for bargains or managing auctions, it makes the whole process way less tedious.

Auction Scout Interface Modern interface showing auction listings with advanced filtering and search capabilities

Key Features

🔍 Unified Auction Aggregation

Multi-Source Data: Scrapes and normalizes auction data from local auction sites (extensible to more sources)
Decoupled Architecture: React frontend fetches all data from backend, never directly from third-party APIs
Real-Time Updates: Auction data refreshed every 10 minutes automatically
Manual Refresh: Admin-triggered data updates for immediate synchronization

🤖 AI-Powered Price Estimation

Claude Sonnet Integration: Expert-level image identificatio and price estimates using both images and descriptions
Instant Valuation: One-click price estimation for any auction item
Detailed Analysis: Comprehensive valuation reports with market context
Batch Processing: Support for multiple item estimation simultaneously
Cost Optimization: Intelligent caching to minimize API costs

AI Price Estimation AI-powered price estimation feature providing detailed valuation reports

📊 Rich Data Visualization

Table & Card Views: Multiple viewing options for auction items
Image Carousels: High-quality image browsing for detailed item inspection
Advanced Filtering: Multi-parameter search and filtering capabilities
CSV Export: Download auction data for offline analysis and record-keeping

Rich data visualization with image carousels and advanced filtering options

⚡ Performance & Reliability

Scheduled Updates: Automated data refresh using node-cron
Health Monitoring: Real-time system health and metrics endpoints
Caching Strategy: Dual-layer caching (in-memory and Redis) for optimal performance
Error Handling: Comprehensive error logging and user-friendly messages

Architecture & Backend

Backend Infrastructure

Node.js with Express for robust API server architecture
Cheerio for reliable HTML scraping and data extraction
Axios for HTTP requests with retry logic and rate limiting
Luxon for advanced date parsing and manipulation
node-cron for scheduled data refresh operations

Frontend Architecture

React with Vite for fast development and optimized builds
Tailwind CSS for responsive, utility-first styling
shadcn/ui for consistent, accessible component library
lucide-react for modern, professional icons
Custom Hooks for state management and API interactions

Data Management

In-Memory Storage as default with Redis support for persistence
Dual-Layer Caching for AI estimation results to optimize costs and performance
RESTful API Design with clear endpoints for auctions, items, health, and metrics
Extensible Architecture for adding new auction sources

Security Measures

API Security

CORS Configuration: Restricted to known frontend ports for development security
Error Handling: Secure error messages that don't expose system internals

Data Protection

No Sensitive Data Storage: No user authentication or personal information handling
Sanitized Outputs: Clean, validated data responses to frontend

UI/UX Details

Modern React Interface

Responsive Design: Mobile-first approach with desktop optimization
Smooth Animations: Fade-in effects and animated transitions for enhanced UX
Loading States: Clear feedback during data fetching and AI processing
Error Boundaries: Graceful error handling with user-friendly messages

Advanced Features

Image Carousels: Intuitive navigation through multiple item photos
Table/Card Toggle: Flexible viewing options based on user preference
Export Functionality: One-click CSV export with proper file naming
Real-Time Feedback: Live updates during AI estimation and data refresh

Accessibility & Performance

Keyboard Navigation: Full accessibility for keyboard-only users
ARIA Labels: Proper semantic markup for screen readers
Color Contrast: WCAG compliant color schemes
Performance Optimization: Lazy loading, code splitting, and efficient rendering

Technical Challenges Overcome

Resilient Web Scraping

Robust Error Handling: Comprehensive retry logic for unreliable third-party sites
Rate Limiting: Implemented respectful scraping practices to avoid blocking
Data Normalization: Created unified data models from disparate auction sources
Change Detection: Built systems to handle website structure changes gracefully

AI Integration Excellence

Prompt Engineering: Developed sophisticated prompts for accurate price estimation
Cost Optimization: Implemented intelligent caching to minimize OpenAI API costs
Context Awareness: Leveraged both visual and textual information for accurate valuations
Batch Processing: Enabled efficient processing of multiple items simultaneously

Performance Optimization

Caching Strategy: Dual-layer caching system for optimal response times
Frontend Decoupling: Ensured frontend never directly calls third-party APIs
Database Design: Efficient in-memory storage with optional Redis persistence
API Design: RESTful endpoints optimized for frontend consumption

Testing & Quality

Comprehensive Testing: Jest and Supertest coverage for all backend endpoints
Cache Testing: Specific tests for hit/miss scenarios and data integrity
API Reliability: Robust error handling and logging throughout the system
Performance Monitoring: Built-in health checks and metrics collection

Impact and Results

User Empowerment

Informed Bidding: AI-powered valuations help users make confident bidding decisions
Time Savings: Unified platform eliminates need to visit multiple auction sites
Data Access: CSV export enables detailed offline analysis and record-keeping
Real-Time Information: Always up-to-date auction data and item details

Technical Innovation

Scalable Architecture: Extensible design ready for additional auction sources
Cost-Effective AI: Intelligent caching minimizes API costs while maintaining functionality
Reliable Scraping: Robust data collection resistant to third-party site changes
Modern Stack: Cutting-edge technologies ensuring long-term maintainability

Business Value

Market Analysis: Provides valuable insights into auction market trends
Investment Tool: Helps collectors and investors make informed purchasing decisions
Administrative Efficiency: Streamlined data management for auction administrators
Competitive Advantage: AI-powered features differentiate from traditional auction browsers

This project was a fun challenge that really showcased what you can do when you combine smart web scraping, AI, and good old-fashioned problem-solving. Instead of jumping between different auction sites and guessing at values, users now have one place to track everything with AI-powered price estimates that actually make sense.

The coolest part was figuring out how to make web scraping reliable (because auction sites love to change their layouts) and keeping AI costs reasonable while still giving accurate valuations. It's the kind of tool I'd actually use myself if I were browsing auctions, which is always a good sign.