feat(autocomplete): Enhanced Cache Matching PoC

[markijbema]

Overview

This PR introduces an intelligent cache matching system for autocomplete suggestions that significantly improves acceptance rates through fuzzy matching, multi-line awareness, and context similarity scoring.

🎯 Problem

The current cache matching in findMatchingSuggestion only supports exact matches and basic partial typing. This means:

• Users lose cached suggestions due to minor typos
• Similar code contexts don't benefit from previous suggestions
• Multi-line code structures aren't recognized

✨ Solution

Implemented EnhancedCacheMatcher with three intelligent matching strategies:

1. Fuzzy Prefix Matching

Tolerates up to 2 character typos using Levenshtein distance.

Example:

// Cached: "const myVariable = " → "42"
// User types: "const myVaraible = " (typo!)
// ✅ Still matches with ~92% confidence

2. Multi-line Context Awareness

Compares the last 3 lines of code for structural similarity.

Example:

// Cached:
function test() {
  const x = 1;
  const y = |

// User types (different function name):
function demo() {
  const x = 1;
  const y = |

// ✅ Matches based on structure!

3. Context Similarity Scoring

Uses semantic similarity of surrounding code (requires >85% similarity to avoid false positives).

📊 Expected Impact

• Cache hit rate: +15-25% improvement
• User acceptance: +10-15% improvement
• Latency reduction: -50-100ms average (cache vs LLM)
• Cost savings: Fewer LLM API calls

🧪 Testing

• ✅ 33 comprehensive test cases
• ✅ All tests passing
• ✅ Performance validated (<50ms for 100+ cached suggestions)
• ✅ Edge cases covered (unicode, special chars, empty strings)

📁 Files Added

1. EnhancedCacheMatcher.ts (382 lines)

   • Core implementation with all matching strategies
   • Configurable thresholds and feature toggles
   • Performance optimized

2. EnhancedCacheMatcher.spec.ts (502 lines)

   • Comprehensive test suite
   • Tests all matching strategies
   • Performance and edge case testing

3. ENHANCED_CACHE_MATCHING.md (268 lines)

   • Complete documentation
   • Integration guide
   • Usage examples
   • Performance benchmarks

🚀 Integration

The PoC is ready for integration into GhostInlineCompletionProvider. See the documentation for detailed integration instructions.

🔍 Review Focus

• Algorithm correctness and edge cases
• Performance characteristics
• Configuration defaults
• Integration approach

📝 Related

This addresses point #6 from the autocomplete optimization analysis: "Enhanced Cache Matching with fuzzy matching, multi-line awareness, and context similarity scoring."

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