RAG Wizard

The RAG Wizard is a comprehensive 5-step guided interface for creating sophisticated Retrieval-Augmented Generation (RAG) systems. It streamlines the complex process of setting up document processing pipelines, embedding configurations, and retrieval mechanisms.

Overview

The RAG Wizard transforms the traditionally complex RAG setup process into an intuitive, step-by-step workflow. Whether you're building a knowledge base for customer support, creating a research assistant, or developing content-aware chatbots, the wizard guides you through each critical decision point.

Key Features

• 5-Step Guided Process: Structured workflow from project setup to API deployment
• Advanced Document Processing: Support for PDFs, CSVs, text files, and more
• Multiple Chunking Strategies: Fixed-size, semantic, recursive, and document-based chunking
• Flexible Embedding Models: Choose from multiple embedding models optimized for different use cases
• Contextual Retrieval: Advanced retrieval methods including ML-optimized contextual retrieval
• Template-Based Configuration: Customizable templates for queries and document processing
• Real-time Validation: Immediate feedback on configuration validity
• Edit Mode: Modify existing RAG projects with full state preservation

Wizard Steps

1. Project Setup

Define your RAG project's basic configuration, including:

• Project name and description
• Domain and use case specification
• Expected scale and query complexity
• Response type and LLM integration preferences

2. Data Sources

Configure and upload your documents:

• Multi-format document support (PDF, CSV, TXT, DOCX)
• Batch upload capabilities
• Document metadata management
• File validation and preprocessing

3. Document Processing & Chunking

Set up your text processing pipeline:

• Chunking strategy selection (fixed-size, semantic, recursive, document-based)
• Chunk size and overlap configuration
• Advanced processing options (sentence boundaries, context coherence)
• Content filtering and optimization settings

4. Pipeline Configuration

Configure embeddings and retrieval:

• Embedding model selection with performance characteristics
• Similarity method configuration (cosine, euclidean, dot product, manhattan)
• Retrieval method selection (custom templates, contextual retrieval, ML-optimized)
• Query and document template customization
• BM25 hybrid search integration

5. API Setup & Endpoints

Complete your RAG system setup:

• API endpoint configuration
• Authentication setup
• Usage monitoring and rate limiting
• Integration documentation and testing

Navigation and State Management

The RAG Wizard features intelligent navigation that:

• Preserves Context: All configuration data persists as you move between steps
• Validates Dependencies: Prevents navigation to steps without required prerequisites
• Supports Editing: Load existing projects with full state restoration
• Provides Feedback: Real-time validation and error messaging

Getting Started

1. Create New RAG Project: Navigate to Dashboard > RAG > Create New
2. Follow the Wizard: Complete each step with guided assistance
3. Test Your Configuration: Use the built-in validation tools
4. Deploy Your API: Generate endpoints for immediate use

Advanced Features

• Template System: Rich template editor with variable substitution
• Metadata Integration: Custom metadata fields for enhanced retrieval
• Hybrid Search: Combine semantic and lexical search methods
• Performance Optimization: Built-in recommendations for optimal configuration
• Bulk Operations: Process multiple documents with consistent settings

The RAG Wizard combines the power of modern vector databases with the simplicity of guided configuration, making advanced RAG systems accessible to both technical and non-technical users.