Files
claude-mnemonic/internal/vector/hybrid/autotuner.go
T
lukaszraczylo 5c2685c7b6 feat(leann-phase2): implement hybrid vector storage and graph-based search (#20)
* feat(leann-phase2): implement hybrid vector storage and graph-based search

- [x] Add AST-aware code chunking for Go, Python, and TypeScript using tree-sitter
- [x] Implement LEANN-inspired hybrid vector storage with hub detection and selective embedding storage (60-80% savings)
- [x] Add observation relationship graph with CSR format and edge detection (file overlap, semantic similarity, temporal, concept)
- [x] Implement graph-aware search with two-level traversal and relationship-based ranking
- [x] Add auto-tuning system for dynamic hub threshold adjustment based on query performance
- [x] Add comprehensive metrics tracking for vector storage, queries, latency, and graph traversals
- [x] Update configuration system with graph and hybrid storage settings
- [x] Add graph stats and vector metrics endpoints to worker service
- [x] Enhance UI sidebar with advanced metrics display and graph visualization
- [x] Optimize struct field alignment throughout codebase for memory efficiency
- [x] Update documentation with LEANN Phase 2 features and performance benefits
- [x] Add tree-sitter dependency for AST parsing

* fix: add fts5 build tag to CI workflow

Pass build-tags: "fts5" to shared workflow to properly compile
sqlite-vec-go-bindings with SQLite FTS5 support.

This fixes test failures in hybrid vector storage tests that require
CGO and FTS5 build tags.

Requires shared-actions@8f7f235 or later.

* docs: add testing documentation and macOS ARM64 known issue

Document the macOS ARM64 CGO linking issue with sqlite-vec-go-bindings
that prevents hybrid package tests from compiling locally.

Added:
- .github/TESTING.md: Comprehensive testing guide with platform-specific
  issues, workarounds, and CI configuration details
- internal/vector/hybrid/README.md: Package-specific documentation
  explaining the macOS limitation
- .github/CI_FIX_SUMMARY.md: Technical details of the CI fix

Key points:
- 41 out of 42 packages test successfully on all platforms
- hybrid package tests fail only on macOS ARM64 (local dev issue)
- Linux CI tests pass with proper build-tags: "fts5" configuration
- Production builds and runtime functionality unaffected

This is a known limitation of sqlite-vec-go-bindings on macOS ARM64
and does not impact CI/CD or production deployments.

* fix: add SQLite busy_timeout to prevent database locked errors

Set PRAGMA busy_timeout=5000 (5 seconds) to allow SQLite to retry
when the database is locked instead of failing immediately.

This fixes race conditions when multiple goroutines try to write
simultaneously, particularly in tests where StoreObservation spawns
async cleanup goroutines.

Root cause:
- StoreObservation launches goroutine -> CleanupOldObservations
- Multiple concurrent cleanups caused "database is locked" errors
- Without busy_timeout, SQLite fails immediately on lock contention

Solution:
- Add 5-second busy timeout for automatic retry on lock
- Standard practice for concurrent SQLite usage
- Works with existing WAL mode configuration

Fixes TestObservationStore_CleanupOldObservations in CI.

* docs: complete summary of all CI test fixes

Comprehensive documentation of all fixes applied:
1. Missing build tags (fts5)
2. Database locked errors (busy_timeout)

All 41/42 packages now pass tests. The hybrid package has a known
macOS ARM64 limitation that doesn't affect CI or production.

No functionality was removed - all fixes are additive only.

* fix: add SQLite driver import to hybrid tests for CGO linking

Add blank import of mattn/go-sqlite3 to hybrid test files to ensure
the SQLite driver is linked into the test binary. This provides the
SQLite symbols that sqlite-vec-go-bindings requires.

Root cause:
- hybrid package imports sqlitevec (transitively depends on sqlite-vec CGO)
- Test binary needs SQLite symbols for linking
- sqlitevec tests already had this import, but hybrid tests didn't
- Without the driver import, linker fails with "undefined symbols"

This fix enables hybrid tests to run with -race flag on all platforms.

Before: 41/42 packages pass (hybrid failed to link)
After:  42/42 packages pass 

Fixes hybrid test compilation on macOS ARM64, Linux, and Windows.

* docs: remove outdated macOS limitation documentation

The hybrid test linking issue has been fixed by adding the SQLite
driver import. All tests now pass on all platforms including macOS.

Removed:
- internal/vector/hybrid/README.md (documented workaround no longer needed)
- .github/TESTING.md (macOS limitation section obsolete)

All 42/42 packages now test successfully with -race flag.

* docs: final comprehensive summary of all CI fixes

All three issues now resolved:
1. Missing fts5 build tags
2. Database busy_timeout for concurrent writes
3. Missing SQLite driver import in hybrid tests

Result: 42/42 packages pass with -race on all platforms.

Credit to reviewer for identifying the race detector concern.
2026-01-07 22:03:59 +00:00

310 lines
7.4 KiB
Go

package hybrid
import (
"context"
"sync"
"time"
"github.com/lukaszraczylo/claude-mnemonic/internal/vector/sqlitevec"
"github.com/rs/zerolog/log"
)
// AutoTuner dynamically adjusts hub threshold based on query performance
type AutoTuner struct {
ctx context.Context
client *Client
cancel context.CancelFunc
latencies []time.Duration
wg sync.WaitGroup
queries int64
targetLatency time.Duration
adjustPeriod time.Duration
minThreshold int
maxThreshold int
adjustments int
latenciesMu sync.Mutex
}
// AutoTunerConfig configures the auto-tuner
type AutoTunerConfig struct {
TargetLatency time.Duration // Target p95 latency (default: 50ms)
MinThreshold int // Min hub threshold (default: 2)
MaxThreshold int // Max hub threshold (default: 20)
AdjustPeriod time.Duration // Adjustment frequency (default: 5min)
}
// DefaultAutoTunerConfig returns sensible defaults
func DefaultAutoTunerConfig() AutoTunerConfig {
return AutoTunerConfig{
TargetLatency: 50 * time.Millisecond,
MinThreshold: 2,
MaxThreshold: 20,
AdjustPeriod: 5 * time.Minute,
}
}
// NewAutoTuner creates a new auto-tuner for the hybrid client
func NewAutoTuner(client *Client, cfg AutoTunerConfig) *AutoTuner {
ctx, cancel := context.WithCancel(context.Background())
tuner := &AutoTuner{
client: client,
targetLatency: cfg.TargetLatency,
minThreshold: cfg.MinThreshold,
maxThreshold: cfg.MaxThreshold,
adjustPeriod: cfg.AdjustPeriod,
latencies: make([]time.Duration, 0, 1000),
ctx: ctx,
cancel: cancel,
}
return tuner
}
// Start begins auto-tuning in the background
func (a *AutoTuner) Start() {
a.wg.Add(1)
go a.tuningLoop()
log.Info().
Dur("target_latency", a.targetLatency).
Int("min_threshold", a.minThreshold).
Int("max_threshold", a.maxThreshold).
Dur("adjust_period", a.adjustPeriod).
Msg("Auto-tuner started")
}
// Stop stops the auto-tuner
func (a *AutoTuner) Stop() {
a.cancel()
a.wg.Wait()
log.Info().Msg("Auto-tuner stopped")
}
// RecordQuery records a query latency for analysis
func (a *AutoTuner) RecordQuery(latency time.Duration) {
a.latenciesMu.Lock()
defer a.latenciesMu.Unlock()
a.queries++
a.latencies = append(a.latencies, latency)
// Keep only recent queries (last 1000)
if len(a.latencies) > 1000 {
a.latencies = a.latencies[len(a.latencies)-1000:]
}
}
// tuningLoop periodically adjusts hub threshold
func (a *AutoTuner) tuningLoop() {
defer a.wg.Done()
ticker := time.NewTicker(a.adjustPeriod)
defer ticker.Stop()
for {
select {
case <-a.ctx.Done():
return
case <-ticker.C:
a.adjustThreshold()
}
}
}
// adjustThreshold analyzes recent queries and adjusts hub threshold
func (a *AutoTuner) adjustThreshold() {
a.latenciesMu.Lock()
defer a.latenciesMu.Unlock()
if len(a.latencies) < 10 {
// Not enough data yet
return
}
// Calculate p95 latency
p95 := calculateP95(a.latencies)
currentThreshold := a.client.hubThreshold
log.Debug().
Dur("p95_latency", p95).
Dur("target_latency", a.targetLatency).
Int("current_threshold", currentThreshold).
Int("queries", len(a.latencies)).
Msg("Auto-tuner evaluating performance")
// Determine adjustment direction
var newThreshold int
if p95 > a.targetLatency {
// Too slow - lower threshold (more hubs = faster queries)
adjustment := calculateAdjustment(p95, a.targetLatency)
newThreshold = currentThreshold - adjustment
if newThreshold < a.minThreshold {
newThreshold = a.minThreshold
}
log.Info().
Dur("p95", p95).
Int("old_threshold", currentThreshold).
Int("new_threshold", newThreshold).
Msg("Auto-tuner: Lowering hub threshold (too slow)")
} else if p95 < a.targetLatency*8/10 {
// Too fast - raise threshold (fewer hubs = more savings)
// Only adjust if significantly faster (20% margin)
adjustment := calculateAdjustment(a.targetLatency, p95)
newThreshold = currentThreshold + adjustment
if newThreshold > a.maxThreshold {
newThreshold = a.maxThreshold
}
log.Info().
Dur("p95", p95).
Int("old_threshold", currentThreshold).
Int("new_threshold", newThreshold).
Msg("Auto-tuner: Raising hub threshold (room for savings)")
} else {
// Within acceptable range, no adjustment needed
log.Debug().
Dur("p95", p95).
Int("threshold", currentThreshold).
Msg("Auto-tuner: Performance acceptable, no adjustment")
return
}
// Apply adjustment
if newThreshold != currentThreshold {
a.client.hubThreshold = newThreshold
a.adjustments++
// Clear latency history after adjustment
a.latencies = make([]time.Duration, 0, 1000)
log.Info().
Int("threshold", newThreshold).
Int("total_adjustments", a.adjustments).
Msg("Hub threshold adjusted by auto-tuner")
}
}
// calculateP95 computes the 95th percentile latency
func calculateP95(latencies []time.Duration) time.Duration {
if len(latencies) == 0 {
return 0
}
// Sort latencies
sorted := make([]time.Duration, len(latencies))
copy(sorted, latencies)
// Simple bubble sort (small dataset)
n := len(sorted)
for i := 0; i < n-1; i++ {
for j := 0; j < n-i-1; j++ {
if sorted[j] > sorted[j+1] {
sorted[j], sorted[j+1] = sorted[j+1], sorted[j]
}
}
}
// Return 95th percentile
idx := int(float64(len(sorted)) * 0.95)
if idx >= len(sorted) {
idx = len(sorted) - 1
}
return sorted[idx]
}
// calculateAdjustment determines how much to adjust threshold
func calculateAdjustment(actual, target time.Duration) int {
// Calculate percentage difference
diff := float64(actual-target) / float64(target)
// Adjust more aggressively for larger differences
if diff > 0.5 || diff < -0.5 {
return 3 // Large adjustment
} else if diff > 0.2 || diff < -0.2 {
return 2 // Medium adjustment
}
return 1 // Small adjustment
}
// GetStats returns auto-tuner statistics
func (a *AutoTuner) GetStats() AutoTunerStats {
a.latenciesMu.Lock()
defer a.latenciesMu.Unlock()
stats := AutoTunerStats{
CurrentThreshold: a.client.hubThreshold,
TargetLatency: a.targetLatency,
TotalQueries: a.queries,
TotalAdjustments: a.adjustments,
RecentQueries: len(a.latencies),
}
if len(a.latencies) > 0 {
stats.P95Latency = calculateP95(a.latencies)
// Calculate average
var total time.Duration
for _, lat := range a.latencies {
total += lat
}
stats.AvgLatency = total / time.Duration(len(a.latencies))
}
return stats
}
// AutoTunerStats contains auto-tuner statistics
type AutoTunerStats struct {
CurrentThreshold int
TargetLatency time.Duration
P95Latency time.Duration
AvgLatency time.Duration
TotalQueries int64
TotalAdjustments int
RecentQueries int
}
// AutoTunedClient wraps Client with automatic performance tuning
type AutoTunedClient struct {
*Client
tuner *AutoTuner
}
// Query wraps the underlying Query call with latency tracking
func (a *AutoTunedClient) Query(ctx context.Context, query string, limit int, where map[string]any) ([]sqlitevec.QueryResult, error) {
start := time.Now()
results, err := a.Client.Query(ctx, query, limit, where)
latency := time.Since(start)
a.tuner.RecordQuery(latency)
return results, err
}
// WithAutoTuning wraps a hybrid client with auto-tuning enabled
func WithAutoTuning(client *Client, cfg AutoTunerConfig) *AutoTunedClient {
tuner := NewAutoTuner(client, cfg)
tuner.Start()
return &AutoTunedClient{
Client: client,
tuner: tuner,
}
}
// Stop stops the auto-tuner
func (a *AutoTunedClient) StopTuning() {
a.tuner.Stop()
}