Files
Maven/internal/memory/store.go
T
claude dd91c6961c recall: a re-tapped fact drops its superseded vector (V-493)
The fact vector id carries a timestamp, so tapping the same key twice added a
row instead of replacing one and recall then scored the old value against the
current one. CorrectValue and VoidLatestFact already prune the key; an ordinary
re-tap is the third way a value is superseded and it did not.

actionFact now prunes fact:<key>: before inserting, so exactly one vector
survives per key. InMemoryStore gained the matching DeletePrefix, because a
test double that quietly kept both rows would pass a test the daemon fails.

The prune is best-effort and silent on a store that cannot do it: the fact row
is the truth, and a stale vector costs a wrong recall, not a lost fact.
2026-08-05 02:32:03 +04:00

208 lines
6.0 KiB
Go

package memory
import (
"context"
"sort"
"strings"
"sync"
)
// NonRecallPrefix — rows whose id starts with this are excluded from Search by
// every backend. Speaker voiceprints live in the same vector table as notes and
// facts (internal/speaker writes them under this prefix), and they are not
// recall material: a voiceprint has no text to read back and surfacing one as a
// note hit leaks a name attached to a biometric.
//
// Reading them through Catalog.ByPrefix was documented as what keeps them out
// of recall. It is not. It controls how speaker code reads its own rows and
// says nothing about what Search scores. What actually kept them out was that
// cosine returns 0 on a width mismatch, so a 192-dim voiceprint scored 0
// against a 384-dim query. That is a coincidence of two model choices — some
// x-vector exports are 384-dim — and not an invariant. This is the invariant.
const NonRecallPrefix = "speaker:"
// Result is a single search hit.
type Result struct {
ID string
Score float64
Meta map[string]string
}
// Store is a vector memory interface.
type Store interface {
Insert(ctx context.Context, id string, vec []float32, meta map[string]string) error
Search(ctx context.Context, vec []float32, topK int) ([]Result, error)
}
// Record is a stored vector read back whole — id, vector and metadata — as
// opposed to Result, which is a search hit and carries a score instead of the
// vector.
type Record struct {
ID string
Vec []float32
Meta map[string]string
}
// Catalog is a Store that can also be enumerated by id prefix and deleted from.
//
// Search is not enough for every user of the vector table. Speaker profiles
// (internal/speaker) need to list exactly their own rows without scoring
// anything, because listing enrolled voices is not a similarity question, and
// they need Delete because a voiceprint is data about a person and "forget this
// voice" has to actually remove it. Note and fact recall use plain Store and are
// unaffected.
type Catalog interface {
Store
// ByPrefix returns every row whose id starts with prefix, in no particular
// order. An empty prefix returns everything.
ByPrefix(ctx context.Context, prefix string) ([]Record, error)
// Delete removes one row by id. Deleting a row that is not there is not an
// error: the caller asked for it to be gone and it is gone.
Delete(ctx context.Context, id string) error
}
// item is a single stored vector with metadata.
type item struct {
id string
vec []float32
meta map[string]string
}
// InMemoryStore implements Store with cosine similarity search.
type InMemoryStore struct {
mu sync.RWMutex
items []item
}
// compile-time check: InMemoryStore satisfies Catalog.
var _ Catalog = (*InMemoryStore)(nil)
func NewInMemoryStore() *InMemoryStore {
return &InMemoryStore{}
}
// Insert upserts by id, matching the persistent store.MemoryStore: a repeated
// id replaces the prior row rather than accumulating a second copy. Re-indexing
// a note is an update, and re-enrolling a voice must replace the old voiceprint
// rather than leave it searchable.
func (s *InMemoryStore) Insert(_ context.Context, id string, vec []float32, meta map[string]string) error {
s.mu.Lock()
defer s.mu.Unlock()
for i := range s.items {
if s.items[i].id == id {
s.items[i] = item{id: id, vec: vec, meta: meta}
return nil
}
}
s.items = append(s.items, item{id: id, vec: vec, meta: meta})
return nil
}
// ByPrefix implements Catalog.
func (s *InMemoryStore) ByPrefix(_ context.Context, prefix string) ([]Record, error) {
s.mu.RLock()
defer s.mu.RUnlock()
var out []Record
for _, it := range s.items {
if !strings.HasPrefix(it.id, prefix) {
continue
}
// Copy the metadata too. Returning it.meta by reference let a caller
// mutating the returned map edit the stored row, and the persistent
// backend unmarshals fresh, so the two disagreed.
meta := make(map[string]string, len(it.meta))
for k, v := range it.meta {
meta[k] = v
}
out = append(out, Record{ID: it.id, Vec: append([]float32(nil), it.vec...), Meta: meta})
}
return out, nil
}
// Delete implements Catalog.
func (s *InMemoryStore) Delete(_ context.Context, id string) error {
s.mu.Lock()
defer s.mu.Unlock()
for i := range s.items {
if s.items[i].id == id {
s.items = append(s.items[:i], s.items[i+1:]...)
return nil
}
}
return nil
}
// DeletePrefix removes every row whose id starts with prefix and returns how
// many went. It matches store.MemoryStore's method so a test double and the
// real index agree about superseding a fact (Vikunja #493) — a double that
// silently kept the old vectors would pass a test the daemon fails.
func (s *InMemoryStore) DeletePrefix(_ context.Context, prefix string) (int64, error) {
s.mu.Lock()
defer s.mu.Unlock()
kept := s.items[:0]
var n int64
for _, it := range s.items {
if strings.HasPrefix(it.id, prefix) {
n++
continue
}
kept = append(kept, it)
}
s.items = kept
return n, nil
}
func (s *InMemoryStore) Search(_ context.Context, vec []float32, topK int) ([]Result, error) {
s.mu.RLock()
defer s.mu.RUnlock()
if topK <= 0 {
topK = 10
}
type scored struct {
id string
score float64
meta map[string]string
}
scores := make([]scored, 0, len(s.items))
for _, it := range s.items {
if strings.HasPrefix(it.id, NonRecallPrefix) {
continue
}
score := cosine(vec, it.vec)
scores = append(scores, scored{id: it.id, score: score, meta: it.meta})
}
sort.Slice(scores, func(i, j int) bool {
return scores[i].score > scores[j].score // descending
})
if topK > len(scores) {
topK = len(scores)
}
out := make([]Result, topK)
for i := 0; i < topK; i++ {
out[i] = Result{
ID: scores[i].id,
Score: scores[i].score,
Meta: scores[i].meta,
}
}
return out, nil
}
// cosine similarity (dot product, assumes L2-normalized vectors).
func cosine(a, b []float32) float64 {
if len(a) != len(b) || len(a) == 0 {
return 0
}
var dot float64
for i := range a {
dot += float64(a[i]) * float64(b[i])
}
return dot
}