Search-Engine

Project Overview

In my latest project, I've developed a web scraping and AI-driven search engine system inspired by Perplexity AI, focusing on efficient data processing and intelligent web analysis.

Key Technical Highlights

Streamlining Data Processing

• Refined text processing techniques
• Improved algorithm speed
• Enhanced text chunking capabilities

Innovative Database Approach

• Implemented an in-code vector database
• Deliberately avoided external databases to reduce latency
• Prioritized direct and fast real-time processing

Performance Optimization

• Utilized parallel processing
• Designed for consistent speed across varying data loads
• Aimed to maintain system responsiveness

Future Development Goals

• Reduce API token usage
• Explore data compression techniques
• Implement potential distributed computing strategies

Technical Challenges

• Managing massive web datasets
• Maintaining data quality during compression
• Balancing processing speed with comprehensive analysis

Project Resources

GitHub Repository: https://github.com/DhruvAjayToshniwal/Search-Engine

The project represents a strategic approach to creating a more efficient, AI-powered search solution with a focus on speed and intelligent data handling.