Files
claude-mnemonic/internal/db/sqlite/scoring.go
T
lukaszraczylo f79782a008 Release dec 2025 (#15)
* Resolves issue #13

- Switched model to bge-small-en-v1.5
- Added lazy re-embedding
- Added model version tracking per vector
- Added conversion of vectors to the new model

* Add lfs support to the workflow.

* Implements importance scoring with decay + voting #6

* Resolves issue #5 by marking observations as superseeded and scheduled for deletion

* Implement pattern detection #7

* Improve injections and observations accuracy

- Session start: Recent observations for project context (recency-based)
- User prompt: Semantically relevant observations (similarity-based with threshold)

* Added two stage retrieval with bi and cross encoder #8

* Implement query expansion and reformulation #9

* Knowledge graph and relationships ( resolves #4 )

- File Overlap Detection: Detects relationships when observations modify/read the same files
- Concept Overlap Detection: Detects relationships based on shared semantic concepts
- Type Progression Detection: Infers relationships from natural observation type progressions (e.g., discovery → bugfix = "fixes")
- Temporal Proximity Detection: Detects relationships between observations in the same session within 5 minutes
- Narrative Mention Detection: Detects explicit relationship language in narratives (e.g., "fixes", "depends on", "supersedes")

* Add visualisation of the relations to the dashboard.

* fixup! Add visualisation of the relations to the dashboard.

* Update documentation with new settings and screenshots.
2025-12-19 17:57:11 +00:00

325 lines
9.1 KiB
Go

// Package sqlite provides SQLite database operations for claude-mnemonic.
package sqlite
import (
"context"
"database/sql"
"time"
"github.com/lukaszraczylo/claude-mnemonic/pkg/models"
)
// UpdateObservationFeedback updates the user feedback for an observation.
// Feedback values: -1 (thumbs down), 0 (neutral), 1 (thumbs up).
func (s *ObservationStore) UpdateObservationFeedback(ctx context.Context, id int64, feedback int) error {
const query = `
UPDATE observations
SET user_feedback = ?, score_updated_at_epoch = ?
WHERE id = ?
`
_, err := s.store.ExecContext(ctx, query, feedback, time.Now().UnixMilli(), id)
return err
}
// IncrementRetrievalCount increments the retrieval counter for the given observation IDs.
// This is called when observations are returned in search results.
func (s *ObservationStore) IncrementRetrievalCount(ctx context.Context, ids []int64) error {
if len(ids) == 0 {
return nil
}
now := time.Now().UnixMilli()
// Build query with placeholders
// #nosec G202 -- query uses parameterized placeholders, not user input
query := `
UPDATE observations
SET retrieval_count = COALESCE(retrieval_count, 0) + 1,
last_retrieved_at_epoch = ?
WHERE id IN (?` + repeatPlaceholders(len(ids)-1) + `)
`
args := make([]interface{}, 0, len(ids)+1)
args = append(args, now)
for _, id := range ids {
args = append(args, id)
}
_, err := s.store.db.ExecContext(ctx, query, args...)
return err
}
// UpdateImportanceScore updates the importance score for a single observation.
func (s *ObservationStore) UpdateImportanceScore(ctx context.Context, id int64, score float64) error {
const query = `
UPDATE observations
SET importance_score = ?, score_updated_at_epoch = ?
WHERE id = ?
`
_, err := s.store.ExecContext(ctx, query, score, time.Now().UnixMilli(), id)
return err
}
// UpdateImportanceScores bulk updates importance scores for multiple observations.
// This is more efficient than individual updates for batch recalculation.
func (s *ObservationStore) UpdateImportanceScores(ctx context.Context, scores map[int64]float64) error {
if len(scores) == 0 {
return nil
}
tx, err := s.store.db.BeginTx(ctx, nil)
if err != nil {
return err
}
defer tx.Rollback()
now := time.Now().UnixMilli()
stmt, err := tx.PrepareContext(ctx, `
UPDATE observations
SET importance_score = ?, score_updated_at_epoch = ?
WHERE id = ?
`)
if err != nil {
return err
}
defer stmt.Close()
for id, score := range scores {
if _, err := stmt.ExecContext(ctx, score, now, id); err != nil {
return err
}
}
return tx.Commit()
}
// GetObservationsNeedingScoreUpdate returns observations that need their importance score recalculated.
// Returns observations where score_updated_at_epoch is NULL or older than the threshold.
func (s *ObservationStore) GetObservationsNeedingScoreUpdate(ctx context.Context, threshold time.Duration, limit int) ([]*models.Observation, error) {
cutoff := time.Now().Add(-threshold).UnixMilli()
query := `SELECT ` + observationColumns + `
FROM observations
WHERE score_updated_at_epoch IS NULL OR score_updated_at_epoch < ?
ORDER BY created_at_epoch DESC
LIMIT ?
`
rows, err := s.store.QueryContext(ctx, query, cutoff, limit)
if err != nil {
return nil, err
}
defer rows.Close()
return scanObservationRows(rows)
}
// GetConceptWeights returns all concept weights from the database.
func (s *ObservationStore) GetConceptWeights(ctx context.Context) (map[string]float64, error) {
const query = `SELECT concept, weight FROM concept_weights`
rows, err := s.store.QueryContext(ctx, query)
if err != nil {
// Table might not exist in older databases
if err == sql.ErrNoRows {
return models.DefaultConceptWeights, nil
}
return nil, err
}
defer rows.Close()
weights := make(map[string]float64)
for rows.Next() {
var concept string
var weight float64
if err := rows.Scan(&concept, &weight); err != nil {
return nil, err
}
weights[concept] = weight
}
if err := rows.Err(); err != nil {
return nil, err
}
// If no weights found, use defaults
if len(weights) == 0 {
return models.DefaultConceptWeights, nil
}
return weights, nil
}
// UpdateConceptWeight updates a single concept weight.
func (s *ObservationStore) UpdateConceptWeight(ctx context.Context, concept string, weight float64) error {
const query = `
INSERT INTO concept_weights (concept, weight, updated_at)
VALUES (?, ?, datetime('now'))
ON CONFLICT(concept) DO UPDATE SET weight = excluded.weight, updated_at = excluded.updated_at
`
_, err := s.store.ExecContext(ctx, query, concept, weight)
return err
}
// UpdateConceptWeights bulk updates multiple concept weights.
func (s *ObservationStore) UpdateConceptWeights(ctx context.Context, weights map[string]float64) error {
if len(weights) == 0 {
return nil
}
tx, err := s.store.db.BeginTx(ctx, nil)
if err != nil {
return err
}
defer tx.Rollback()
stmt, err := tx.PrepareContext(ctx, `
INSERT INTO concept_weights (concept, weight, updated_at)
VALUES (?, ?, datetime('now'))
ON CONFLICT(concept) DO UPDATE SET weight = excluded.weight, updated_at = excluded.updated_at
`)
if err != nil {
return err
}
defer stmt.Close()
for concept, weight := range weights {
if _, err := stmt.ExecContext(ctx, concept, weight); err != nil {
return err
}
}
return tx.Commit()
}
// GetObservationFeedbackStats returns statistics about user feedback.
func (s *ObservationStore) GetObservationFeedbackStats(ctx context.Context, project string) (*FeedbackStats, error) {
var query string
var args []interface{}
if project == "" {
query = `
SELECT
COUNT(*) as total,
COALESCE(SUM(CASE WHEN user_feedback = 1 THEN 1 ELSE 0 END), 0) as positive,
COALESCE(SUM(CASE WHEN user_feedback = -1 THEN 1 ELSE 0 END), 0) as negative,
COALESCE(SUM(CASE WHEN user_feedback = 0 THEN 1 ELSE 0 END), 0) as neutral,
COALESCE(AVG(COALESCE(importance_score, 1.0)), 0) as avg_score,
COALESCE(AVG(COALESCE(retrieval_count, 0)), 0) as avg_retrieval
FROM observations
`
} else {
query = `
SELECT
COUNT(*) as total,
COALESCE(SUM(CASE WHEN user_feedback = 1 THEN 1 ELSE 0 END), 0) as positive,
COALESCE(SUM(CASE WHEN user_feedback = -1 THEN 1 ELSE 0 END), 0) as negative,
COALESCE(SUM(CASE WHEN user_feedback = 0 THEN 1 ELSE 0 END), 0) as neutral,
COALESCE(AVG(COALESCE(importance_score, 1.0)), 0) as avg_score,
COALESCE(AVG(COALESCE(retrieval_count, 0)), 0) as avg_retrieval
FROM observations
WHERE project = ? OR scope = 'global'
`
args = append(args, project)
}
var stats FeedbackStats
err := s.store.QueryRowContext(ctx, query, args...).Scan(
&stats.Total,
&stats.Positive,
&stats.Negative,
&stats.Neutral,
&stats.AvgScore,
&stats.AvgRetrieval,
)
if err != nil {
return nil, err
}
return &stats, nil
}
// FeedbackStats contains statistics about observation feedback and scoring.
type FeedbackStats struct {
Total int `json:"total"`
Positive int `json:"positive"`
Negative int `json:"negative"`
Neutral int `json:"neutral"`
AvgScore float64 `json:"avg_score"`
AvgRetrieval float64 `json:"avg_retrieval"`
}
// GetTopScoringObservations returns the highest-scoring observations.
func (s *ObservationStore) GetTopScoringObservations(ctx context.Context, project string, limit int) ([]*models.Observation, error) {
var query string
var args []interface{}
if project == "" {
query = `SELECT ` + observationColumns + `
FROM observations
ORDER BY COALESCE(importance_score, 1.0) DESC, created_at_epoch DESC
LIMIT ?
`
args = append(args, limit)
} else {
query = `SELECT ` + observationColumns + `
FROM observations
WHERE project = ? OR scope = 'global'
ORDER BY COALESCE(importance_score, 1.0) DESC, created_at_epoch DESC
LIMIT ?
`
args = append(args, project, limit)
}
rows, err := s.store.QueryContext(ctx, query, args...)
if err != nil {
return nil, err
}
defer rows.Close()
return scanObservationRows(rows)
}
// GetMostRetrievedObservations returns the most frequently retrieved observations.
func (s *ObservationStore) GetMostRetrievedObservations(ctx context.Context, project string, limit int) ([]*models.Observation, error) {
var query string
var args []interface{}
if project == "" {
query = `SELECT ` + observationColumns + `
FROM observations
WHERE retrieval_count > 0
ORDER BY retrieval_count DESC, created_at_epoch DESC
LIMIT ?
`
args = append(args, limit)
} else {
query = `SELECT ` + observationColumns + `
FROM observations
WHERE (project = ? OR scope = 'global') AND retrieval_count > 0
ORDER BY retrieval_count DESC, created_at_epoch DESC
LIMIT ?
`
args = append(args, project, limit)
}
rows, err := s.store.QueryContext(ctx, query, args...)
if err != nil {
return nil, err
}
defer rows.Close()
return scanObservationRows(rows)
}
// ResetObservationScores resets all observation scores to their default values.
// This is useful for testing or when changing the scoring algorithm.
func (s *ObservationStore) ResetObservationScores(ctx context.Context) error {
const query = `
UPDATE observations
SET importance_score = 1.0, score_updated_at_epoch = NULL
`
_, err := s.store.ExecContext(ctx, query)
return err
}