diff options
Diffstat (limited to 'prompt.c')
| -rw-r--r-- | prompt.c | 408 |
1 files changed, 365 insertions, 43 deletions
@@ -1,55 +1,113 @@ #include "llama.h" +#include "vectordb.h" #include "models.h" + #include <stdio.h> #include <stdlib.h> #include <string.h> #include <getopt.h> +#include <ctype.h> -static void show_help(const char *prog) { - printf("Usage: %s [OPTIONS]\n", prog); - printf("Options:\n"); - printf(" -m, --model <name> Specify model to use (default: first model)\n"); - printf(" -p, --prompt <text> Specify prompt text (default: \"What is 2+2?\")\n"); - printf(" -h, --help Show this help message\n"); -} +#define MAX_TOKENS 512 +#define MAX_TOKEN_LEN 32 -int main(int argc, char **argv) { - const char *model_name = NULL; - const char *prompt = NULL; - - int n_predict = 64; +static const char *refusal_text = "I don't have that information."; - static struct option long_options[] = { - {"model", required_argument, 0, 'm'}, - {"prompt", required_argument, 0, 'p'}, - {"help", no_argument, 0, 'h'}, - {0, 0, 0, 0} +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; +} - int opt; - int option_index = 0; - while ((opt = getopt_long(argc, argv, "m:p:h", long_options, &option_index)) != -1) { - switch (opt) { - case 'm': - model_name = optarg; - break; - case 'p': - prompt = optarg; +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) { + strncpy(tokens[count], buf, MAX_TOKEN_LEN - 1); + tokens[count][MAX_TOKEN_LEN - 1] = '\0'; + count++; + } + } + len = 0; + } + if (*p == '\0') { break; - case 'h': - show_help(argv[0]); - return 0; - default: - fprintf(stderr, "Usage: %s [-m model] [-p prompt] [-h]\n", argv[0]); - return 1; + } } } + return count; +} - if (prompt == NULL) { - printf("Prompt must be provided. Exiting..."); - return 1; +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); @@ -61,6 +119,12 @@ int main(int argc, char **argv) { 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(); @@ -75,10 +139,27 @@ int main(int argc, char **argv) { const struct llama_vocab *vocab = llama_model_get_vocab(model); - int n_prompt = -llama_tokenize(vocab, prompt, strlen(prompt), NULL, 0, true, true); + 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, prompt, strlen(prompt), prompt_tokens, n_prompt, true, true) < 0) { + 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; @@ -92,6 +173,7 @@ int main(int argc, char **argv) { 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; @@ -104,10 +186,15 @@ int main(int argc, char **argv) { 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; } @@ -118,12 +205,25 @@ int main(int argc, char **argv) { batch = llama_batch_get_one(&decoder_start, 1); } - printf("Prompt: %s\n", prompt); - printf("Response: "); + 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)) { @@ -145,18 +245,240 @@ int main(int argc, char **argv) { fprintf(stderr, "Error: failed to convert token to piece\n"); break; } - printf("%.*s", n, buf); - fflush(stdout); + 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); } - printf("\n"); + 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 <name> Specify model to use (default: first model)\n"); + printf(" -p, --prompt <text> Specify prompt text (default: \"What is 2+2?\")\n"); + printf(" -c, --context <text> 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) { + 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'}, + {"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; +} |