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VecturaKit Documentation

Welcome to VecturaKit's documentation hub. This directory contains comprehensive guides for understanding and using VecturaKit's features.

Available Documentation

Indexed Storage Guide

Purpose: Learn about VecturaKit's memory management strategies

Topics Covered:

  • Memory strategy options (automatic, fullMemory, indexed)
  • When to use each strategy
  • Configuration examples
  • IndexedVecturaStorage protocol implementation
  • Performance considerations for large-scale datasets

Target Audience: Developers integrating VecturaKit

When to Read:

  • Setting up VecturaKit for the first time
  • Choosing the right memory strategy
  • Working with large datasets (> 10K documents)
  • Implementing custom storage providers

Performance Test Results

Purpose: Understand VecturaKit's performance characteristics

Topics Covered:

  • Benchmark results for different strategies
  • Performance metrics (latency, memory, throughput)
  • Scaling characteristics
  • Parameter tuning recommendations
  • Platform-specific considerations

Target Audience: Users evaluating VecturaKit, developers optimizing performance

When to Read:

  • Evaluating VecturaKit for your use case
  • Understanding expected performance
  • Choosing optimal configurations
  • Planning for dataset growth

Quick Facts:

  • Search Latency (1K docs): ~10ms average, <12ms P99
  • Memory Usage: ~180-200 KB per document (fullMemory mode)
  • Initialization: Sub-millisecond
  • Tested on: Apple Silicon (M-series), macOS 14.0+

Quick Navigation

For New Users

  1. Getting Started: See Main README
  2. Choose Memory Strategy: Read Indexed Storage Guide
  3. Understand Performance: Review Test Results

For Developers

  1. Memory Strategies: Indexed Storage Guide
  2. Performance Testing: Tests/PerformanceTests/
  3. Test Results: Performance

For Decision Makers

  1. Performance Overview: Test Results Summary
  2. Scaling Capabilities: See "Scaling Characteristics" section in test results
  3. Platform Support: Check Main README

Documentation Structure

Docs/
├── README.md                      # This file - Documentation index
├── INDEXED_STORAGE_GUIDE.md       # Memory strategy implementation guide
└── TEST_RESULTS_SUMMARY.md        # Detailed performance test results

Additional Resources:

Find What You Need

Memory & Storage Questions

Q: How do I choose between fullMemory and indexed mode? → Indexed Storage Guide - See "Choosing a Memory Strategy"

Q: How much memory will VecturaKit use? → Performance Results - See "Memory Usage" section

Q: Can VecturaKit handle 100K documents? → Indexed Storage Guide + Performance Results

Performance Questions

Q: How fast is search? → Performance Results - See benchmark data

Q: How do I optimize for my use case? → Performance Results - See "Parameter Tuning" section

Q: What are the scaling characteristics? → Performance Results - See "Scaling Characteristics"

Implementation Questions

Q: How do I implement IndexedVecturaStorage? → Indexed Storage Guide - See implementation examples

Q: How do I run performance tests? → Tests/PerformanceTests/

Q: What are best practices? → Indexed Storage Guide + Performance Results

Performance Summary

Quick reference for VecturaKit's performance (fullMemory mode, 1K documents):

Metric Value
Search Latency (P99) < 12 ms
Initialization < 1 ms
Memory per Document ~180-200 KB
Document Addition 150-200 docs/sec

Platform: Apple Silicon (M-series), macOS 14.0+

See full test results for detailed benchmarks.

For Contributors

Documentation Guidelines

  1. Keep docs up-to-date: Update after significant changes
  2. User-focused: Write for users, not just developers
  3. Examples: Include code examples where helpful
  4. Accuracy: Verify technical details before publishing

Adding Documentation

  1. Create new .md file in appropriate location
  2. Update this README.md to include it
  3. Add cross-references from related docs
  4. Test all code examples

External Resources

Last Updated: 2025-10-30 Documentation Version: 2.0