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

internal/vector/sqlitevec/client.go

@@ -319,11 +319,11 @@ func (c *Client) NeedsRebuild(ctx context.Context) (bool, string) {
 // StaleVectorInfo contains information about a vector that needs rebuilding.
 type StaleVectorInfo struct {
 	DocID     string
-	SQLiteID  int64
 	DocType   string
 	FieldType string
 	Project   string
 	Scope     string
+	SQLiteID  int64
 }
 
 // GetStaleVectors returns doc_ids of vectors with mismatched or null model versions.

internal/vector/sqlitevec/helpers.go

@@ -12,17 +12,17 @@ const (
 
 // Document represents a document to store with vector embedding.
 type Document struct {
+	Metadata map[string]any
 	ID       string
 	Content  string
-	Metadata map[string]any
 }
 
 // QueryResult represents a search result from vector search.
 type QueryResult struct {
+	Metadata   map[string]any
 	ID         string
 	Distance   float64
-	Similarity float64 // 1.0 = identical, 0.0 = opposite (derived from distance)
-	Metadata   map[string]any
+	Similarity float64
 }
 
 // DistanceToSimilarity converts sqlite-vec cosine distance to similarity score.

internal/vector/sqlitevec/helpers_test.go

@@ -42,10 +42,10 @@ func TestQueryResult_Fields(t *testing.T) {
 
 func TestBuildWhereFilter(t *testing.T) {
 	tests := []struct {
+		expected map[string]interface{}
 		name     string
 		docType  DocType
 		project  string
-		expected map[string]interface{}
 	}{
 		{
 			name:     "empty_filters",
@@ -474,9 +474,9 @@ func TestCopyMetadataMulti(t *testing.T) {
 func TestJoinStrings(t *testing.T) {
 	tests := []struct {
 		name     string
-		strs     []string
 		sep      string
 		expected string
+		strs     []string
 	}{
 		{
 			name:     "empty_slice",
@@ -522,8 +522,8 @@ func TestTruncateString(t *testing.T) {
 	tests := []struct {
 		name     string
 		input    string
-		maxLen   int
 		expected string
+		maxLen   int
 	}{
 		{
 			name:     "shorter_than_max",
@@ -577,10 +577,10 @@ func TestFilterByThreshold(t *testing.T) {
 	tests := []struct {
 		name        string
 		results     []QueryResult
+		expectedIDs []string
 		threshold   float64
 		maxResults  int
 		expectedLen int
-		expectedIDs []string
 	}{
 		{
 			name:        "empty_results",