From d964db648a06a553a52c49aea82047e0d352dbd0 Mon Sep 17 00:00:00 2001 From: Mitja Felicijan Date: Wed, 18 Feb 2026 01:58:42 +0100 Subject: Update readme --- prompt.c | 493 --------------------------------------------------------------- 1 file changed, 493 deletions(-) delete mode 100644 prompt.c diff --git a/prompt.c b/prompt.c deleted file mode 100644 index c5bd4cb..0000000 --- a/prompt.c +++ /dev/null @@ -1,493 +0,0 @@ -#include "llama.h" -#include "vectordb.h" -#include "models.h" - -#include -#include -#include -#include -#include - -#define MAX_TOKENS 512 -#define MAX_TOKEN_LEN 32 - -typedef struct { - -} Engine; - -static const char *refusal_text = "I don't have that information."; - -static void llama_log_callback(enum ggml_log_level level, const char *text, void *user_data) { - (void)level; - (void)user_data; - (void)text; -} - -static int is_stopword(const char *token, size_t len) { - static const char *stopwords[] = { - "a", "an", "the", "is", "are", "was", "were", "of", "to", "in", "on", - "for", "with", "and", "or", "not", "if", "then", "else", "from", "by", - "as", "at", "it", "its", "this", "that", "these", "those", "who", "what", - "when", "where", "why", "how", "which", "about", "into", "over", "under", - "be", "been", "being", "do", "does", "did", "but", "so", "than" - }; - for (size_t i = 0; i < sizeof(stopwords) / sizeof(stopwords[0]); i++) { - if (strlen(stopwords[i]) == len && strncmp(stopwords[i], token, len) == 0) { - return 1; - } - } - return 0; -} - -static int token_exists(char tokens[MAX_TOKENS][MAX_TOKEN_LEN], int count, const char *token) { - for (int i = 0; i < count; i++) { - if (strcmp(tokens[i], token) == 0) { - return 1; - } - } - return 0; -} - -static int collect_tokens(const char *text, char tokens[MAX_TOKENS][MAX_TOKEN_LEN]) { - int count = 0; - char buf[MAX_TOKEN_LEN]; - int len = 0; - for (const unsigned char *p = (const unsigned char *)text; ; p++) { - if (isalnum(*p)) { - if (len < MAX_TOKEN_LEN - 1) { - buf[len++] = (char)tolower(*p); - } - } else { - if (len > 0) { - buf[len] = '\0'; - if (len >= 4 && !is_stopword(buf, (size_t)len)) { - if (!token_exists(tokens, count, buf) && count < MAX_TOKENS) { - memcpy(tokens[count], buf, (size_t)len + 1); - tokens[count][MAX_TOKEN_LEN - 1] = '\0'; - count++; - } - } - len = 0; - } - if (*p == '\0') { - break; - } - } - } - return count; -} - -static int has_overlap(const char *a, const char *b) { - if (a == NULL || b == NULL) { - return 0; - } - char tokens[MAX_TOKENS][MAX_TOKEN_LEN]; - int token_count = collect_tokens(b, tokens); - if (token_count == 0) { - return 0; - } - char buf[MAX_TOKEN_LEN]; - int len = 0; - for (const unsigned char *p = (const unsigned char *)a; ; p++) { - if (isalnum(*p)) { - if (len < MAX_TOKEN_LEN - 1) { - buf[len++] = (char)tolower(*p); - } - } else { - if (len > 0) { - buf[len] = '\0'; - if (len >= 4 && !is_stopword(buf, (size_t)len)) { - if (token_exists(tokens, token_count, buf)) { - return 1; - } - } - len = 0; - } - if (*p == '\0') { - break; - } - } - } - return 0; -} - -static int execute_prompt(const char *model_name, const char *prompt, const char *context, int n_predict) { - const model_config *cfg = NULL; - if (model_name != NULL) { - cfg = get_model_by_name(model_name); - if (cfg == NULL) { - fprintf(stderr, "Error: unknown model '%s'\n", model_name); - return 1; - } - } else { - cfg = &models[0]; - } - - if (!has_overlap(prompt, context)) { - printf("------------ Prompt: %s\n", prompt); - printf("------------ Response: %s\n", refusal_text); - return 0; - } - - ggml_backend_load_all(); - - struct llama_model_params model_params = llama_model_default_params(); - model_params.n_gpu_layers = cfg->n_gpu_layers; - model_params.use_mmap = cfg->use_mmap; - - struct llama_model *model = llama_model_load_from_file(cfg->filepath, model_params); - if (model == NULL) { - fprintf(stderr, "Error: unable to load model from %s\n", cfg->filepath); - return 1; - } - - const struct llama_vocab *vocab = llama_model_get_vocab(model); - - const char *system_prefix = "System: Answer using only the Context. If the answer is not explicitly stated in Context, respond exactly: I don't have that information.\n\n"; - const char *context_prefix = "Context:\n"; - const char *prompt_prefix = "\n\nQuestion:\n"; - const char *answer_prefix = "\n\nAnswer:\n"; - size_t context_len = context ? strlen(context) : 0; - size_t prompt_len = strlen(prompt); - size_t full_len = strlen(system_prefix) + strlen(context_prefix) + context_len + strlen(prompt_prefix) + prompt_len + strlen(answer_prefix) + 1; - char *full_prompt = (char *)malloc(full_len); - if (full_prompt == NULL) { - fprintf(stderr, "Error: failed to allocate prompt buffer\n"); - llama_model_free(model); - return 1; - } - snprintf(full_prompt, full_len, "%s%s%s%s%s", system_prefix, context_prefix, context ? context : "", prompt_prefix, prompt); - strncat(full_prompt, answer_prefix, full_len - strlen(full_prompt) - 1); - - int n_prompt = -llama_tokenize(vocab, full_prompt, strlen(full_prompt), NULL, 0, true, true); - llama_token *prompt_tokens = (llama_token *)malloc(n_prompt * sizeof(llama_token)); - if (llama_tokenize(vocab, full_prompt, strlen(full_prompt), prompt_tokens, n_prompt, true, true) < 0) { - fprintf(stderr, "Error: failed to tokenize the prompt\n"); - free(full_prompt); - free(prompt_tokens); - llama_model_free(model); - return 1; - } - - struct llama_context_params ctx_params = llama_context_default_params(); - ctx_params.n_ctx = cfg->n_ctx; - ctx_params.n_batch = cfg->n_batch; - ctx_params.embeddings = cfg->embeddings; - - struct llama_context *ctx = llama_init_from_model(model, ctx_params); - if (ctx == NULL) { - fprintf(stderr, "Error: failed to create the llama_context\n"); - free(full_prompt); - free(prompt_tokens); - llama_model_free(model); - return 1; - } - - struct llama_sampler_chain_params sparams = llama_sampler_chain_default_params(); - struct llama_sampler *smpl = llama_sampler_chain_init(sparams); - llama_sampler_chain_add(smpl, llama_sampler_init_temp(cfg->temperature)); - llama_sampler_chain_add(smpl, llama_sampler_init_min_p(cfg->min_p, 1)); - llama_sampler_chain_add(smpl, llama_sampler_init_dist(cfg->seed)); - - struct llama_batch batch = llama_batch_get_one(prompt_tokens, n_prompt); - - if (llama_model_has_encoder(model)) { - if (llama_encode(ctx, batch)) { - fprintf(stderr, "Error: failed to encode prompt\n"); - llama_sampler_free(smpl); - free(full_prompt); - free(prompt_tokens); - llama_free(ctx); - llama_model_free(model); - return 1; - } - - llama_token decoder_start = llama_model_decoder_start_token(model); - if (decoder_start == LLAMA_TOKEN_NULL) { - decoder_start = llama_vocab_bos(vocab); - } - batch = llama_batch_get_one(&decoder_start, 1); - } - - printf("------------ Prompt: %s\n", prompt); - printf("------------ Response: "); - fflush(stdout); - - int n_pos = 0; - llama_token new_token_id; - size_t out_cap = 256; - size_t out_len = 0; - char *out = (char *)malloc(out_cap); - if (out == NULL) { - fprintf(stderr, "Error: failed to allocate output buffer\n"); - free(full_prompt); - free(prompt_tokens); - llama_sampler_free(smpl); - llama_free(ctx); - llama_model_free(model); - return 1; - } - out[0] = '\0'; - - while (n_pos + batch.n_tokens < n_prompt + n_predict) { - if (llama_decode(ctx, batch)) { - fprintf(stderr, "Error: failed to decode\n"); - break; - } - - n_pos += batch.n_tokens; - - new_token_id = llama_sampler_sample(smpl, ctx, -1); - - if (llama_vocab_is_eog(vocab, new_token_id)) { - break; - } - - char buf[128]; - int n = llama_token_to_piece(vocab, new_token_id, buf, sizeof(buf), 0, true); - if (n < 0) { - fprintf(stderr, "Error: failed to convert token to piece\n"); - break; - } - int stop_at = n; - for (int i = 0; i < n; i++) { - if (buf[i] == '\n') { - stop_at = i; - break; - } - } - if (out_len + (size_t)stop_at + 1 > out_cap) { - while (out_len + (size_t)stop_at + 1 > out_cap) { - out_cap *= 2; - } - char *next = (char *)realloc(out, out_cap); - if (next == NULL) { - fprintf(stderr, "Error: failed to grow output buffer\n"); - break; - } - out = next; - } - memcpy(out + out_len, buf, (size_t)stop_at); - out_len += (size_t)stop_at; - out[out_len] = '\0'; - - if (stop_at != n) { - break; - } - - batch = llama_batch_get_one(&new_token_id, 1); - } - - if (!has_overlap(out, context)) { - strcpy(out, refusal_text); - out_len = strlen(out); - } - - printf("%s\n", out); - - free(full_prompt); - free(prompt_tokens); - free(out); - llama_sampler_free(smpl); - llama_free(ctx); - llama_model_free(model); - - return 0; -} - -static char *generate_context(const char *model_name, const char *context_file, const char *prompt) { - FILE *context_fp = fopen(context_file, "r"); - if (context_fp == NULL) { - fprintf(stderr, "Error: unable to open context file %s\n", context_file); - return NULL; - } - - llama_backend_init(); - - const model_config *cfg = NULL; - if (model_name != NULL) { - cfg = get_model_by_name(model_name); - if (cfg == NULL) { - fprintf(stderr, "Error: unknown model '%s'\n", model_name); - fclose(context_fp); - llama_backend_free(); - return NULL; - } - } else { - cfg = &models[0]; - } - - /* struct llama_model *model = llama_load_model_from_file(cfg->filepath, llama_model_default_params()); */ - struct llama_model *model = llama_model_load_from_file(cfg->filepath, llama_model_default_params()); - if (model == NULL) { - fprintf(stderr, "Error: unable to load embedding model\n"); - fclose(context_fp); - llama_backend_free(); - return NULL; - } - - struct llama_context_params cparams = llama_context_default_params(); - cparams.embeddings = true; - - /* struct llama_context *embed_ctx = llama_new_context_with_model(model, cparams); */ - struct llama_context *embed_ctx = llama_init_from_model(model, cparams); - if (embed_ctx == NULL) { - fprintf(stderr, "Error: failed to create embedding context\n"); - llama_model_free(model); - fclose(context_fp); - llama_backend_free(); - return NULL; - } - - VectorDB db; - vdb_init(&db, embed_ctx); - - char line[1024]; - while (fgets(line, sizeof(line), context_fp) != NULL) { - size_t len = strlen(line); - while (len > 0 && (line[len - 1] == '\n' || line[len - 1] == '\r')) { - line[len - 1] = '\0'; - len--; - } - if (len == 0) { - continue; - } - vdb_add_document(&db, line); - } - - float query[VDB_EMBED_SIZE]; - int results[3]; - - vdb_embed_query(&db, prompt, query); - vdb_search(&db, query, 3, results); - - size_t context_cap = 1024; - size_t context_len = 0; - char *context = (char *)malloc(context_cap); - if (context == NULL) { - fprintf(stderr, "Error: failed to allocate context buffer\n"); - fclose(context_fp); - llama_free(embed_ctx); - llama_model_free(model); - llama_backend_free(); - return NULL; - } - context[0] = '\0'; - - for (int i = 0; i < 3; i++) { - if (results[i] < 0) { - continue; - } - const char *text = db.docs[results[i]].text; - size_t text_len = strlen(text); - size_t need = context_len + text_len + 2; - if (need > context_cap) { - while (need > context_cap) { - context_cap *= 2; - } - char *next = (char *)realloc(context, context_cap); - if (next == NULL) { - fprintf(stderr, "Error: failed to grow context buffer\n"); - free(context); - fclose(context_fp); - llama_free(embed_ctx); - llama_model_free(model); - llama_backend_free(); - return NULL; - } - context = next; - } - memcpy(context + context_len, text, text_len); - context_len += text_len; - context[context_len++] = '\n'; - context[context_len] = '\0'; - } - - fclose(context_fp); - llama_free(embed_ctx); - llama_model_free(model); - llama_backend_free(); - - return context; -} - -static void show_help(const char *prog) { - printf("Usage: %s [OPTIONS]\n", prog); - printf("Options:\n"); - printf(" -m, --model Specify model to use (default: first model)\n"); - printf(" -p, --prompt Specify prompt text (default: \"What is 2+2?\")\n"); - printf(" -b, --build Specify context file\n"); - printf(" -c, --context Specify context file\n"); - printf(" -v, --verbose Enable verbose logging\n"); - printf(" -h, --help Show this help message\n"); -} - -int main(int argc, char **argv) { - /* Engine engine = {}; */ - - - const char *model_name = NULL; - const char *prompt = NULL; - const char *context_file = NULL; - int verbose = 0; - - int n_predict = 64; - - static struct option long_options[] = { - {"model", required_argument, 0, 'm'}, - {"prompt", required_argument, 0, 'p'}, - {"context", required_argument, 0, 'c'}, - {"build", required_argument, 0, 'b'}, - {"verbose", no_argument, 0, 'v'}, - {"help", no_argument, 0, 'h'}, - {0, 0, 0, 0} - }; - - int opt; - int option_index = 0; - while ((opt = getopt_long(argc, argv, "m:p:c:vh", long_options, &option_index)) != -1) { - switch (opt) { - case 'm': - model_name = optarg; - break; - case 'p': - prompt = optarg; - break; - case 'c': - context_file = optarg; - break; - case 'v': - verbose = 1; - break; - case 'h': - show_help(argv[0]); - return 0; - default: - fprintf(stderr, "Usage: %s [-m model] [-p prompt] [-h]\n", argv[0]); - return 1; - } - } - - if (verbose == 0) { - llama_log_set(llama_log_callback, NULL); - } - - if (prompt == NULL) { - printf("Prompt must be provided. Exiting..."); - return 1; - } - - if (context_file == NULL) { - printf("Context file must be provided. Exiting..."); - return 1; - } - - char *context = generate_context(model_name, context_file, prompt); - if (context == NULL) { - return 1; - } - - int rc = execute_prompt(model_name, prompt, context, n_predict); - free(context); - return rc; -} -- cgit v1.2.3