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#include <stdio.h>
#include <string.h>
#include <math.h>
#include <stdint.h>
#include "llama.h"
#include "vectordb.h"
#include "nonstd.h"
#define VDB_MAGIC 0x31424456u /* "VDB1" */
#define VDB_VERSION 1u
typedef struct {
uint32_t magic;
uint32_t version;
uint32_t embed_size;
uint32_t max_text;
uint32_t count;
} VdbFileHeader;
static float cosine_similarity(float *a, float *b, int n) {
float dot = 0, norm_a = 0, norm_b = 0;
for (int i = 0; i < n; i++) {
dot += a[i] * b[i];
norm_a += a[i] * a[i];
norm_b += b[i] * b[i];
}
return dot / (sqrtf(norm_a) * sqrtf(norm_b) + 1e-8f);
}
static void embed_text(struct llama_context *ctx, const char *text, float *out) {
llama_token tokens[512];
const struct llama_model *model = llama_get_model(ctx);
const struct llama_vocab *vocab = llama_model_get_vocab(model);
int n_tokens = llama_tokenize(vocab, text, strlen(text), tokens, 512, true, true);
if (n_tokens < 0) {
return;
}
struct llama_batch batch = llama_batch_get_one(tokens, n_tokens);
llama_decode(ctx, batch);
const float *emb = llama_get_embeddings(ctx);
memcpy(out, emb, sizeof(float) * VDB_EMBED_SIZE);
}
void vdb_init(VectorDB *db, struct llama_context *embed_ctx) {
memset(db, 0, sizeof(VectorDB));
db->embed_ctx = embed_ctx;
}
void vdb_free(VectorDB *db) {
(void)db;
}
void vdb_add_document(VectorDB *db, const char *text) {
if (db->count >= VDB_MAX_DOCS) {
log_message(stdout, LOG_INFO, "Vector database full");
return;
}
VectorDoc *doc = &db->docs[db->count++];
strncpy(doc->text, text, VDB_MAX_TEXT - 1);
doc->text[VDB_MAX_TEXT - 1] = 0;
log_message(stdout, LOG_INFO, "Embedding doc %d...", db->count);
embed_text(db->embed_ctx, text, doc->embedding);
}
void vdb_embed_query(VectorDB *db, const char *text, float *out_embedding) {
embed_text(db->embed_ctx, text, out_embedding);
}
void vdb_search(VectorDB *db, float *query, int top_k, int *results) {
float best_scores[top_k];
for (int i = 0; i < top_k; i++) {
best_scores[i] = -1.0f;
results[i] = -1;
}
for (int i = 0; i < db->count; i++) {
float score = cosine_similarity(query, db->docs[i].embedding, VDB_EMBED_SIZE);
for (int j = 0; j < top_k; j++) {
if (score > best_scores[j]) {
for (int k = top_k - 1; k > j; k--) {
best_scores[k] = best_scores[k - 1];
results[k] = results[k - 1];
}
best_scores[j] = score;
results[j] = i;
break;
}
}
}
}
int vdb_save(const VectorDB *db, const char *path) {
FILE *fp = fopen(path, "wb");
if (!fp) {
return 1;
}
VdbFileHeader header = {
.magic = VDB_MAGIC,
.version = VDB_VERSION,
.embed_size = VDB_EMBED_SIZE,
.max_text = VDB_MAX_TEXT,
.count = (uint32_t)db->count,
};
if (fwrite(&header, sizeof(header), 1, fp) != 1) {
fclose(fp);
return 2;
}
if (db->count > 0) {
size_t wrote = fwrite(db->docs, sizeof(VectorDoc), (size_t)db->count, fp);
if (wrote != (size_t)db->count) {
fclose(fp);
return 3;
}
}
if (fclose(fp) != 0) {
return 4;
}
return 0;
}
int vdb_load(VectorDB *db, const char *path) {
struct llama_context *ctx = db->embed_ctx;
FILE *fp = fopen(path, "rb");
if (!fp) {
return -1;
}
VdbFileHeader header = {0};
if (fread(&header, sizeof(header), 1, fp) != 1) {
fclose(fp);
return -2;
}
if (header.magic != VDB_MAGIC || header.version != VDB_VERSION) {
fclose(fp);
return -3;
}
if (header.embed_size != VDB_EMBED_SIZE || header.max_text != VDB_MAX_TEXT) {
fclose(fp);
return -4;
}
if (header.count > VDB_MAX_DOCS) {
fclose(fp);
return -5;
}
memset(db, 0, sizeof(VectorDB));
db->embed_ctx = ctx;
db->count = (int)header.count;
if (db->count > 0) {
size_t read = fread(db->docs, sizeof(VectorDoc), (size_t)db->count, fp);
if (read != (size_t)db->count) {
fclose(fp);
return -6;
}
}
if (fclose(fp) != 0) {
return -7;
}
return 0;
}
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