Files
claude-mnemonic/internal/vector/sqlitevec/client.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

405 lines
10 KiB
Go

// Package sqlitevec provides sqlite-vec based vector database integration for claude-mnemonic.
package sqlitevec
import (
"context"
"database/sql"
"fmt"
"strings"
"sync"
sqlite_vec "github.com/asg017/sqlite-vec-go-bindings/cgo"
"github.com/lukaszraczylo/claude-mnemonic/internal/embedding"
"github.com/rs/zerolog/log"
)
// Client provides vector operations via sqlite-vec.
type Client struct {
db *sql.DB
embedSvc *embedding.Service
mu sync.Mutex
}
// Config holds configuration for the client.
type Config struct {
DB *sql.DB
}
// NewClient creates a new sqlite-vec client.
func NewClient(cfg Config, embedSvc *embedding.Service) (*Client, error) {
if cfg.DB == nil {
return nil, fmt.Errorf("database connection required")
}
if embedSvc == nil {
return nil, fmt.Errorf("embedding service required")
}
return &Client{
db: cfg.DB,
embedSvc: embedSvc,
}, nil
}
// AddDocuments adds documents with their embeddings to the vector store.
func (c *Client) AddDocuments(ctx context.Context, docs []Document) error {
if len(docs) == 0 {
return nil
}
c.mu.Lock()
defer c.mu.Unlock()
// Generate embeddings for all documents
texts := make([]string, len(docs))
for i, doc := range docs {
texts[i] = doc.Content
}
embeddings, err := c.embedSvc.EmbedBatch(texts)
if err != nil {
return fmt.Errorf("generate embeddings: %w", err)
}
// Insert into vectors table with model version tracking
const insertQuery = `
INSERT OR REPLACE INTO vectors (doc_id, embedding, sqlite_id, doc_type, field_type, project, scope, model_version)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
`
// Get current model version for tracking
modelVersion := c.embedSvc.Version()
tx, err := c.db.BeginTx(ctx, nil)
if err != nil {
return fmt.Errorf("begin transaction: %w", err)
}
defer func() {
if err != nil {
_ = tx.Rollback()
}
}()
stmt, err := tx.PrepareContext(ctx, insertQuery)
if err != nil {
return fmt.Errorf("prepare statement: %w", err)
}
defer stmt.Close()
for i, doc := range docs {
// Serialize embedding to blob format
embBlob, err := sqlite_vec.SerializeFloat32(embeddings[i])
if err != nil {
return fmt.Errorf("serialize embedding for %s: %w", doc.ID, err)
}
// Extract metadata
sqliteID, _ := doc.Metadata["sqlite_id"].(int64)
docType, _ := doc.Metadata["doc_type"].(string)
fieldType, _ := doc.Metadata["field_type"].(string)
project, _ := doc.Metadata["project"].(string)
scope, _ := doc.Metadata["scope"].(string)
_, err = stmt.ExecContext(ctx,
doc.ID,
embBlob,
sqliteID,
docType,
fieldType,
project,
scope,
modelVersion,
)
if err != nil {
return fmt.Errorf("insert document %s: %w", doc.ID, err)
}
}
if err = tx.Commit(); err != nil {
return fmt.Errorf("commit transaction: %w", err)
}
log.Debug().Int("count", len(docs)).Str("model", modelVersion).Msg("Added documents to sqlite-vec")
return nil
}
// DeleteDocuments removes documents by their IDs.
func (c *Client) DeleteDocuments(ctx context.Context, ids []string) error {
if len(ids) == 0 {
return nil
}
c.mu.Lock()
defer c.mu.Unlock()
// Build placeholder string
placeholders := make([]string, len(ids))
args := make([]interface{}, len(ids))
for i, id := range ids {
placeholders[i] = "?"
args[i] = id
}
// #nosec G201 -- Placeholders are "?" strings, actual values are parameterized via args
query := fmt.Sprintf("DELETE FROM vectors WHERE doc_id IN (%s)",
strings.Join(placeholders, ","))
_, err := c.db.ExecContext(ctx, query, args...)
if err != nil {
return fmt.Errorf("delete documents: %w", err)
}
log.Debug().Int("count", len(ids)).Msg("Deleted documents from sqlite-vec")
return nil
}
// Query performs a vector similarity search.
func (c *Client) Query(ctx context.Context, query string, limit int, where map[string]any) ([]QueryResult, error) {
c.mu.Lock()
defer c.mu.Unlock()
// Generate query embedding
queryEmb, err := c.embedSvc.Embed(query)
if err != nil {
return nil, fmt.Errorf("embed query: %w", err)
}
// Serialize query embedding
queryBlob, err := sqlite_vec.SerializeFloat32(queryEmb)
if err != nil {
return nil, fmt.Errorf("serialize query embedding: %w", err)
}
// Build query with filters
// vec0 supports WHERE clauses on metadata columns
args := []interface{}{queryBlob}
sqlQuery := `
SELECT
doc_id,
distance,
sqlite_id,
doc_type,
field_type,
project,
scope
FROM vectors
WHERE embedding MATCH ?
`
// Add filters - these work with vec0 metadata columns
if docType, ok := where["doc_type"].(string); ok && docType != "" {
sqlQuery += " AND doc_type = ?"
args = append(args, docType)
}
if project, ok := where["project"].(string); ok && project != "" {
// Include project-specific OR global scope
sqlQuery += " AND (project = ? OR scope = 'global')"
args = append(args, project)
}
sqlQuery += " ORDER BY distance LIMIT ?"
args = append(args, limit)
rows, err := c.db.QueryContext(ctx, sqlQuery, args...)
if err != nil {
return nil, fmt.Errorf("query vectors: %w", err)
}
defer rows.Close()
var results []QueryResult
for rows.Next() {
var r QueryResult
var sqliteID int64
var docType, fieldType, project, scope sql.NullString
if err := rows.Scan(&r.ID, &r.Distance, &sqliteID, &docType, &fieldType, &project, &scope); err != nil {
return nil, fmt.Errorf("scan row: %w", err)
}
r.Similarity = DistanceToSimilarity(r.Distance)
r.Metadata = map[string]any{
"sqlite_id": float64(sqliteID), // Keep as float64 for compatibility
"doc_type": docType.String,
"field_type": fieldType.String,
"project": project.String,
"scope": scope.String,
}
results = append(results, r)
}
if err = rows.Err(); err != nil {
return nil, fmt.Errorf("iterate rows: %w", err)
}
log.Debug().
Str("query", truncateString(query, 50)).
Int("results", len(results)).
Msg("Vector search completed")
return results, nil
}
// IsConnected always returns true (no external process).
func (c *Client) IsConnected() bool {
return c.db != nil
}
// Close is a no-op (db managed externally).
func (c *Client) Close() error {
return nil
}
// truncateString truncates a string to maxLen characters.
func truncateString(s string, maxLen int) string {
if len(s) <= maxLen {
return s
}
return s[:maxLen] + "..."
}
// Count returns the total number of vectors in the store.
func (c *Client) Count(ctx context.Context) (int64, error) {
c.mu.Lock()
defer c.mu.Unlock()
var count int64
err := c.db.QueryRowContext(ctx, "SELECT COUNT(*) FROM vectors").Scan(&count)
if err != nil {
return 0, fmt.Errorf("count vectors: %w", err)
}
return count, nil
}
// ModelVersion returns the current embedding model version.
func (c *Client) ModelVersion() string {
return c.embedSvc.Version()
}
// NeedsRebuild checks if vectors need to be rebuilt due to model version change.
// Returns true if:
// - The vectors table is empty
// - Any vectors have a different model_version than the current model
func (c *Client) NeedsRebuild(ctx context.Context) (bool, string) {
c.mu.Lock()
defer c.mu.Unlock()
currentModel := c.embedSvc.Version()
// Check total count
var totalCount int64
err := c.db.QueryRowContext(ctx, "SELECT COUNT(*) FROM vectors").Scan(&totalCount)
if err != nil {
log.Warn().Err(err).Msg("Failed to count vectors for rebuild check")
return false, ""
}
if totalCount == 0 {
return true, "empty"
}
// Check for vectors with different model version
var staleCount int64
err = c.db.QueryRowContext(ctx,
"SELECT COUNT(*) FROM vectors WHERE model_version != ? OR model_version IS NULL",
currentModel,
).Scan(&staleCount)
if err != nil {
log.Warn().Err(err).Msg("Failed to count stale vectors")
return false, ""
}
if staleCount > 0 {
return true, fmt.Sprintf("model_mismatch:%d", staleCount)
}
return false, ""
}
// StaleVectorInfo contains information about a vector that needs rebuilding.
type StaleVectorInfo struct {
DocID string
DocType string
FieldType string
Project string
Scope string
SQLiteID int64
}
// GetStaleVectors returns doc_ids of vectors with mismatched or null model versions.
// This enables granular rebuild - only re-embedding documents that need updating.
func (c *Client) GetStaleVectors(ctx context.Context) ([]StaleVectorInfo, error) {
c.mu.Lock()
defer c.mu.Unlock()
currentModel := c.embedSvc.Version()
query := `
SELECT doc_id, sqlite_id, doc_type, field_type, project, scope
FROM vectors
WHERE model_version != ? OR model_version IS NULL
`
rows, err := c.db.QueryContext(ctx, query, currentModel)
if err != nil {
return nil, fmt.Errorf("query stale vectors: %w", err)
}
defer rows.Close()
var results []StaleVectorInfo
for rows.Next() {
var info StaleVectorInfo
var sqliteID sql.NullInt64
var docType, fieldType, project, scope sql.NullString
if err := rows.Scan(&info.DocID, &sqliteID, &docType, &fieldType, &project, &scope); err != nil {
return nil, fmt.Errorf("scan row: %w", err)
}
info.SQLiteID = sqliteID.Int64
info.DocType = docType.String
info.FieldType = fieldType.String
info.Project = project.String
info.Scope = scope.String
results = append(results, info)
}
if err = rows.Err(); err != nil {
return nil, fmt.Errorf("iterate rows: %w", err)
}
return results, nil
}
// DeleteVectorsByDocIDs removes vectors by their doc_ids.
// Used for granular rebuild - delete stale vectors before re-adding.
func (c *Client) DeleteVectorsByDocIDs(ctx context.Context, docIDs []string) error {
if len(docIDs) == 0 {
return nil
}
c.mu.Lock()
defer c.mu.Unlock()
// Build placeholder string
placeholders := make([]string, len(docIDs))
args := make([]interface{}, len(docIDs))
for i, id := range docIDs {
placeholders[i] = "?"
args[i] = id
}
// #nosec G201 -- Placeholders are "?" strings, actual values are parameterized via args
query := fmt.Sprintf("DELETE FROM vectors WHERE doc_id IN (%s)",
strings.Join(placeholders, ","))
_, err := c.db.ExecContext(ctx, query, args...)
if err != nil {
return fmt.Errorf("delete vectors by doc_ids: %w", err)
}
log.Debug().Int("count", len(docIDs)).Msg("Deleted stale vectors by doc_id")
return nil
}