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Keep each MMR candidate's similarity to the selection as a running maximum #11

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Merged
vlasky merged 1 commit into from
Oct 28, 2026
Merged

Keep each MMR candidate's similarity to the selection as a running maximum #11

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35 changes: 19 additions & 16 deletions sqlite-vec.c
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Original file line number Diff line number Diff line change
Expand Up @@ -7761,7 +7761,7 @@ static int vec0_mmr_rerank(
f32 *relevance = NULL;
i64 *out_rowids = NULL;
f32 *out_distances = NULL;
void **out_vectors = NULL;
f32 *max_sim = NULL;
u8 *selected = NULL;

// 2. Load vectors from shadow tables
Expand All @@ -7784,15 +7784,20 @@ static int vec0_mmr_rerank(
relevance[i] = 1.0f - (topk_distances[i] / max_dist);
}

// 4. Greedy MMR selection
// 4. Greedy MMR selection. max_sim[i] is candidate i's highest similarity
// to the results selected so far, raised against each new selection
// alone, so a step measures each remaining candidate once.
out_rowids = sqlite3_malloc64(k_target * sizeof(i64));
out_distances = sqlite3_malloc64(k_target * sizeof(f32));
out_vectors = sqlite3_malloc64(k_target * sizeof(void *));
max_sim = sqlite3_malloc64(k_used * sizeof(f32));
selected = sqlite3_malloc64(k_used);
if (!out_rowids || !out_distances || !out_vectors || !selected) {
if (!out_rowids || !out_distances || !max_sim || !selected) {
rc = SQLITE_NOMEM; goto cleanup;
}
memset(selected, 0, k_used);
for (i64 i = 0; i < k_used; i++) {
max_sim[i] = 0.0f;
}

i64 n_selected = 0;
for (i64 step = 0; step < k_target && step < k_used; step++) {
Expand All @@ -7802,17 +7807,8 @@ static int vec0_mmr_rerank(
for (i64 i = 0; i < k_used; i++) {
if (selected[i]) continue;

// max similarity to already-selected results
f32 max_sim = 0.0f;
for (i64 j = 0; j < step; j++) {
f32 d = vec0_compute_distance(vector_column,
vectors[i], out_vectors[j]);
f32 sim = 1.0f - (d / max_dist);
if (sim > max_sim) max_sim = sim;
}

f32 mmr_score = mmr_lambda * relevance[i]
- (1.0f - mmr_lambda) * max_sim;
- (1.0f - mmr_lambda) * max_sim[i];
if (mmr_score > best_mmr) {
best_mmr = mmr_score;
best_idx = i;
Expand All @@ -7823,8 +7819,15 @@ static int vec0_mmr_rerank(
selected[best_idx] = 1;
out_rowids[step] = topk_rowids[best_idx];
out_distances[step] = topk_distances[best_idx];
out_vectors[step] = vectors[best_idx];
n_selected++;

for (i64 i = 0; i < k_used; i++) {
if (selected[i]) continue;
f32 d = vec0_compute_distance(vector_column,
vectors[i], vectors[best_idx]);
f32 sim = 1.0f - (d / max_dist);
if (sim > max_sim[i]) max_sim[i] = sim;
}
}

// 5. Copy only the actually-selected entries back to input arrays
Expand All @@ -7844,7 +7847,7 @@ static int vec0_mmr_rerank(
sqlite3_free(relevance);
sqlite3_free(out_rowids);
sqlite3_free(out_distances);
sqlite3_free(out_vectors);
sqlite3_free(max_sim);
sqlite3_free(selected);
return rc;
}
Expand Down