Building a Perplexity-like System
Presenter
Saurabh Lal Saxena is an advanced RAG architect specializing in sophisticated search and retrieval implementations. He has made significant contributions to the Austin LangChain community through his expertise in developing complex document processing systems and advanced RAG architectures.
Connect with Saurabh:
- GitHub: @saurabhlalsaxena
Lab Overview
Learn how to build a Perplexity-like search and response system using LangChain, implementing advanced search capabilities and response generation.
Lab Materials
Key Topics
- Search system architecture
- Response generation
- Knowledge integration
- User experience optimization
- Performance tuning
Features
- Advanced search capabilities
- Context-aware responses
- Knowledge integration
- Real-time processing
- User interaction
Technical Components
- Search implementation
- Response generation
- Knowledge base integration
- User interface
- Performance optimization
Implementation Steps
- Search system setup
- Response pipeline creation
- Knowledge integration
- Interface development
- Performance tuning
- Testing and validation
Best Practices
- Search optimization
- Response quality
- Knowledge management
- User experience
- Performance tuning
Use Cases
- Information retrieval
- Question answering
- Knowledge exploration
- Research assistance
- Learning support
Prerequisites
- Basic understanding of:
- Search systems
- LLMs
- Python programming
- Web development
- Development environment setup