Update readme

1 files changed, 0 insertions, 493 deletions

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 <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <getopt.h>
-#include <ctype.h>
-
-#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 <name>    Specify model to use (default: first model)\n");
-    printf("  -p, --prompt <text>   Specify prompt text (default: \"What is 2+2?\")\n");
-    printf("  -b, --build <file>    Specify context file\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) {
-	/* 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;
-}