Felipe97/llama-cpp-compiled
01.2k
1#include "arg.h"2#include "common.h"3#include "console.h"4#include "log.h"5#include "sampling.h"6#include "llama.h"7#include "chat.h"8 9#include <clocale>10#include <cstdio>11#include <cstring>12#include <ctime>13#include <fstream>14#include <iostream>15#include <sstream>16#include <string>17#include <vector>18 19#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))20#include <signal.h>21#include <unistd.h>22#elif defined (_WIN32)23#define WIN32_LEAN_AND_MEAN24#ifndef NOMINMAX25#define NOMINMAX26#endif27#include <windows.h>28#include <signal.h>29#endif30 31#if defined(_MSC_VER)32#pragma warning(disable: 4244 4267) // possible loss of data33#endif34 35static llama_context ** g_ctx;36static common_sampler ** g_smpl;37static common_params * g_params;38static bool is_interacting = false;39static bool need_insert_eot = false;40 41static void print_usage(int argc, char ** argv) {42 (void) argc;43 44 LOG("\nexample usage:\n");45 LOG("\n text generation: %s -m your_model.gguf -p \"I believe the meaning of life is\" -n 128 -no-cnv\n", argv[0]);46 LOG("\n chat (conversation): %s -m your_model.gguf -sys \"You are a helpful assistant\"\n", argv[0]);47 LOG("\n");48}49 50static bool file_exists(const std::string & path) {51 std::ifstream f(path.c_str());52 return f.good();53}54 55static bool file_is_empty(const std::string & path) {56 std::ifstream f;57 f.exceptions(std::ifstream::failbit | std::ifstream::badbit);58 f.open(path.c_str(), std::ios::in | std::ios::binary | std::ios::ate);59 return f.tellg() == 0;60}61 62#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)63static void sigint_handler(int signo) {64 if (signo == SIGINT) {65 if (!is_interacting && g_params->interactive) {66 is_interacting = true;67 need_insert_eot = true;68 } else {69 console::cleanup();70 LOG("\n");71 common_perf_print(*g_ctx, *g_smpl);72 73 // make sure all logs are flushed74 LOG("Interrupted by user\n");75 common_log_pause(common_log_main());76 77 _exit(130);78 }79 }80}81#endif82 83// satisfies -Wmissing-declarations84int llama_completion(int argc, char ** argv);85 86int llama_completion(int argc, char ** argv) {87 std::setlocale(LC_NUMERIC, "C");88 89 common_params params;90 g_params = ¶ms;91 92 common_init();93 94 if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMPLETION, print_usage)) {95 return 1;96 }97 98 auto & sparams = params.sampling;99 100 // save choice to use color for later101 // (note for later: this is a slightly awkward choice)102 console::init(params.simple_io, params.use_color);103 atexit([]() { console::cleanup(); });104 105 if (params.embedding) {106 LOG_ERR("************\n");107 LOG_ERR("%s: please use the 'embedding' tool for embedding calculations\n", __func__);108 LOG_ERR("************\n\n");109 110 return 0;111 }112 113 if (params.n_ctx != 0 && params.n_ctx < 8) {114 LOG_WRN("%s: warning: minimum context size is 8, using minimum size.\n", __func__);115 params.n_ctx = 8;116 }117 118 if (params.rope_freq_base != 0.0) {119 LOG_WRN("%s: warning: changing RoPE frequency base to %g.\n", __func__, params.rope_freq_base);120 }121 122 if (params.rope_freq_scale != 0.0) {123 LOG_WRN("%s: warning: scaling RoPE frequency by %g.\n", __func__, params.rope_freq_scale);124 }125 126 LOG_INF("%s: llama backend init\n", __func__);127 128 llama_backend_init();129 llama_numa_init(params.numa);130 131 llama_model * model = nullptr;132 llama_context * ctx = nullptr;133 common_sampler * smpl = nullptr;134 135 g_ctx = &ctx;136 g_smpl = &smpl;137 138 std::vector<common_chat_msg> chat_msgs;139 140 // load the model and apply lora adapter, if any141 LOG_INF("%s: load the model and apply lora adapter, if any\n", __func__);142 143 auto llama_init = common_init_from_params(params);144 145 ctx = llama_init->context();146 model = llama_init->model();147 smpl = llama_init->sampler(0);148 149 if (ctx == NULL) {150 LOG_ERR("%s: error: unable to create context\n", __func__);151 return 1;152 }153 154 llama_memory_t mem = llama_get_memory(ctx);155 const llama_vocab * vocab = llama_model_get_vocab(model);156 157 // note: the time for chat template initialization is not negligible:158 auto chat_templates = common_chat_templates_init(model, params.chat_template);159 160 // start measuring performance timings from here161 llama_perf_context_reset(ctx);162 163 const int n_ctx_train = llama_model_n_ctx_train(model);164 const int n_ctx = llama_n_ctx(ctx);165 166 if (n_ctx > n_ctx_train) {167 LOG_WRN("%s: model was trained on only %d context tokens (%d specified)\n", __func__, n_ctx_train, n_ctx);168 }169 170 // auto enable conversation mode if chat template is available171 const bool has_chat_template = common_chat_templates_was_explicit(chat_templates.get());172 if (params.conversation_mode == COMMON_CONVERSATION_MODE_AUTO) {173 if (has_chat_template) {174 LOG_INF("%s: chat template is available, enabling conversation mode (disable it with -no-cnv)\n", __func__);175 params.conversation_mode = COMMON_CONVERSATION_MODE_ENABLED;176 } else {177 params.conversation_mode = COMMON_CONVERSATION_MODE_DISABLED;178 }179 }180 181 // in case user force-activate conversation mode (via -cnv) without proper chat template, we show a warning182 if (params.conversation_mode && !has_chat_template) {183 LOG_WRN("%s: chat template is not available or is not supported. This may cause the model to output suboptimal responses\n", __func__);184 }185 186 // print chat template example in conversation mode187 if (params.conversation_mode) {188 if (params.enable_chat_template) {189 if (!params.prompt.empty() && params.system_prompt.empty()) {190 LOG_WRN("*** User-specified prompt will pre-start conversation, did you mean to set --system-prompt (-sys) instead?\n");191 }192 193 LOG_INF("%s: chat template example:\n%s\n", __func__, common_chat_format_example(chat_templates.get(), params.use_jinja, params.default_template_kwargs).c_str());194 } else {195 LOG_INF("%s: in-suffix/prefix is specified, chat template will be disabled\n", __func__);196 }197 }198 199 // print system information200 {201 LOG_INF("\n");202 LOG_INF("%s\n", common_params_get_system_info(params).c_str());203 LOG_INF("\n");204 }205 206 std::string path_session = params.path_prompt_cache;207 std::vector<llama_token> session_tokens;208 209 if (!path_session.empty()) {210 LOG_INF("%s: attempting to load saved session from '%s'\n", __func__, path_session.c_str());211 if (!file_exists(path_session)) {212 LOG_INF("%s: session file does not exist, will create.\n", __func__);213 } else if (file_is_empty(path_session)) {214 LOG_INF("%s: The session file is empty. A new session will be initialized.\n", __func__);215 } else {216 // The file exists and is not empty217 session_tokens.resize(n_ctx);218 size_t n_token_count_out = 0;219 if (!llama_state_load_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.capacity(), &n_token_count_out)) {220 LOG_ERR("%s: failed to load session file '%s'\n", __func__, path_session.c_str());221 return 1;222 }223 session_tokens.resize(n_token_count_out);224 LOG_INF("%s: loaded a session with prompt size of %d tokens\n", __func__, (int)session_tokens.size());225 }226 }227 228 const bool add_bos = llama_vocab_get_add_bos(vocab) && !params.use_jinja;229 if (!llama_model_has_encoder(model)) {230 GGML_ASSERT(!llama_vocab_get_add_eos(vocab));231 }232 233 LOG_DBG("n_ctx: %d, add_bos: %d\n", n_ctx, add_bos);234 235 std::vector<llama_token> embd_inp;236 237 bool waiting_for_first_input = false;238 auto chat_add_and_format = [&chat_msgs, &chat_templates](const std::string & role, const std::string & content) {239 common_chat_msg new_msg;240 new_msg.role = role;241 new_msg.content = content;242 auto formatted = common_chat_format_single(chat_templates.get(), chat_msgs, new_msg, role == "user", g_params->use_jinja);243 chat_msgs.push_back(new_msg);244 LOG_DBG("formatted: '%s'\n", formatted.c_str());245 return formatted;246 };247 248 std::string prompt;249 {250 if (params.conversation_mode && params.enable_chat_template) {251 if (!params.system_prompt.empty()) {252 // format the system prompt (will use template default if empty)253 chat_add_and_format("system", params.system_prompt);254 }255 256 if (!params.prompt.empty()) {257 // format and append the user prompt258 chat_add_and_format("user", params.prompt);259 } else {260 waiting_for_first_input = true;261 }262 263 if (!params.system_prompt.empty() || !params.prompt.empty()) {264 common_chat_templates_inputs inputs;265 inputs.use_jinja = g_params->use_jinja;266 inputs.messages = chat_msgs;267 inputs.add_generation_prompt = !params.prompt.empty();268 inputs.force_pure_content = params.force_pure_content_parser;269 270 prompt = common_chat_templates_apply(chat_templates.get(), inputs).prompt;271 }272 } else {273 // otherwise use the prompt as is274 prompt = params.prompt;275 }276 277 if (params.interactive_first || !prompt.empty() || session_tokens.empty()) {278 LOG_DBG("tokenize the prompt\n");279 embd_inp = common_tokenize(ctx, prompt, true, true);280 } else {281 LOG_DBG("use session tokens\n");282 embd_inp = session_tokens;283 }284 285 LOG_DBG("prompt: \"%s\"\n", prompt.c_str());286 LOG_DBG("tokens: %s\n", string_from(ctx, embd_inp).c_str());287 }288 289 // Should not run without any tokens290 if (!waiting_for_first_input && embd_inp.empty()) {291 if (add_bos) {292 embd_inp.push_back(llama_vocab_bos(vocab));293 LOG_WRN("embd_inp was considered empty and bos was added: %s\n", string_from(ctx, embd_inp).c_str());294 } else {295 LOG_ERR("input is empty\n");296 return -1;297 }298 }299 300 // Tokenize negative prompt301 if ((int) embd_inp.size() > n_ctx - 4) {302 LOG_ERR("%s: prompt is too long (%d tokens, max %d)\n", __func__, (int) embd_inp.size(), n_ctx - 4);303 return 1;304 }305 306 bool session_do_save = false;307 308 {309 size_t n_match = 0;310 311 if (!session_tokens.empty()) {312 for (llama_token id : session_tokens) {313 if (n_match >= embd_inp.size() || id != embd_inp[n_match]) {314 break;315 }316 n_match++;317 }318 if (params.prompt.empty() && n_match == embd_inp.size()) {319 LOG_INF("%s: using full prompt from session file\n", __func__);320 } else if (n_match >= embd_inp.size()) {321 LOG_INF("%s: session file has exact match for prompt!\n", __func__);322 } else if (n_match < (embd_inp.size() / 2)) {323 LOG_WRN("%s: session file has low similarity to prompt (%zu / %zu tokens); will mostly be reevaluated\n",324 __func__, n_match, embd_inp.size());325 } else {326 LOG_INF("%s: session file matches %zu / %zu tokens of prompt\n",327 __func__, n_match, embd_inp.size());328 }329 330 // remove any "future" tokens that we might have inherited from the previous session331 if (session_tokens.size() > n_match) {332 llama_pos pos = n_match > 0 ? (llama_pos)(n_match - 1) : 0;333 if (!llama_memory_seq_rm(mem, -1, pos, -1)) {334 LOG_WRN("%s: unable to reuse common prefix (for example, when the memory is recurrent)\n", __func__);335 llama_memory_clear(mem, true);336 session_tokens.clear();337 n_match = 0;338 } else {339 session_tokens.resize(n_match);340 }341 }342 }343 344 session_do_save = !path_session.empty() && n_match < embd_inp.size() && !params.prompt_cache_ro;345 346 // Logits are not stored as part of the session state so we need to347 // "replay" the last token to get logits for sampling.348 if (!session_tokens.empty() && n_match > 0 && n_match == session_tokens.size()) {349 if (!common_replay_last_token(ctx, session_tokens.back(), n_match - 1)) {350 return 1;351 }352 353 session_do_save = false;354 LOG_INF("%s: replayed last token from session\n", __func__);355 }356 }357 358 // number of tokens to keep when resetting context359 if (params.n_keep < 0 || params.n_keep > (int) embd_inp.size()) {360 params.n_keep = (int)embd_inp.size();361 } else {362 params.n_keep += add_bos; // always keep the BOS token363 }364 365 if (params.conversation_mode) {366 if (params.single_turn && !params.prompt.empty()) {367 params.interactive = false;368 params.interactive_first = false;369 } else {370 params.interactive_first = true;371 }372 }373 374 // enable interactive mode if interactive start is specified375 if (params.interactive_first) {376 params.interactive = true;377 }378 379 if (params.verbose_prompt) {380 LOG_INF("%s: prompt: '%s'\n", __func__, params.prompt.c_str());381 LOG_INF("%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());382 for (int i = 0; i < (int) embd_inp.size(); i++) {383 LOG_INF("%6d -> '%s'\n", embd_inp[i], common_token_to_piece(ctx, embd_inp[i]).c_str());384 }385 386 if (params.n_keep > add_bos) {387 LOG_INF("%s: static prompt based on n_keep: '", __func__);388 for (int i = 0; i < params.n_keep; i++) {389 LOG_CNT("%s", common_token_to_piece(ctx, embd_inp[i]).c_str());390 }391 LOG_CNT("'\n");392 }393 LOG_INF("\n");394 }395 396 // ctrl+C handling397 {398#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))399 struct sigaction sigint_action;400 sigint_action.sa_handler = sigint_handler;401 sigemptyset (&sigint_action.sa_mask);402 sigint_action.sa_flags = 0;403 sigaction(SIGINT, &sigint_action, NULL);404#elif defined (_WIN32)405 auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {406 return (ctrl_type == CTRL_C_EVENT) ? (sigint_handler(SIGINT), true) : false;407 };408 SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);409#endif410 }411 412 if (params.interactive) {413 LOG_INF("%s: interactive mode on.\n", __func__);414 415 if (!params.antiprompt.empty()) {416 for (const auto & antiprompt : params.antiprompt) {417 LOG_INF("Reverse prompt: '%s'\n", antiprompt.c_str());418 if (params.verbose_prompt) {419 auto tmp = common_tokenize(ctx, antiprompt, false, true);420 for (int i = 0; i < (int) tmp.size(); i++) {421 LOG_INF("%6d -> '%s'\n", tmp[i], common_token_to_piece(ctx, tmp[i]).c_str());422 }423 }424 }425 }426 427 if (params.input_prefix_bos) {428 LOG_INF("Input prefix with BOS\n");429 }430 431 if (!params.input_prefix.empty()) {432 LOG_INF("Input prefix: '%s'\n", params.input_prefix.c_str());433 if (params.verbose_prompt) {434 auto tmp = common_tokenize(ctx, params.input_prefix, true, true);435 for (int i = 0; i < (int) tmp.size(); i++) {436 LOG_INF("%6d -> '%s'\n", tmp[i], common_token_to_piece(ctx, tmp[i]).c_str());437 }438 }439 }440 441 if (!params.input_suffix.empty()) {442 LOG_INF("Input suffix: '%s'\n", params.input_suffix.c_str());443 if (params.verbose_prompt) {444 auto tmp = common_tokenize(ctx, params.input_suffix, false, true);445 for (int i = 0; i < (int) tmp.size(); i++) {446 LOG_INF("%6d -> '%s'\n", tmp[i], common_token_to_piece(ctx, tmp[i]).c_str());447 }448 }449 }450 }451 452 LOG_INF("sampler seed: %u\n", common_sampler_get_seed(smpl));453 LOG_INF("sampler params: \n%s\n", sparams.print().c_str());454 LOG_INF("sampler chain: %s\n", common_sampler_print(smpl).c_str());455 456 LOG_INF("generate: n_ctx = %d, n_batch = %d, n_predict = %d, n_keep = %d\n", n_ctx, params.n_batch, params.n_predict, params.n_keep);457 458 // group-attention state459 // number of grouped KV tokens so far (used only if params.grp_attn_n > 1)460 int ga_i = 0;461 462 const int ga_n = params.grp_attn_n;463 const int ga_w = params.grp_attn_w;464 465 if (ga_n != 1) {466 GGML_ASSERT(ga_n > 0 && "grp_attn_n must be positive"); // NOLINT467 GGML_ASSERT(ga_w % ga_n == 0 && "grp_attn_w must be a multiple of grp_attn_n"); // NOLINT468 //GGML_ASSERT(n_ctx_train % ga_w == 0 && "n_ctx_train must be a multiple of grp_attn_w"); // NOLINT469 //GGML_ASSERT(n_ctx >= n_ctx_train * ga_n && "n_ctx must be at least n_ctx_train * grp_attn_n"); // NOLINT470 LOG_INF("self-extend: n_ctx_train = %d, grp_attn_n = %d, grp_attn_w = %d\n", n_ctx_train, ga_n, ga_w);471 }472 LOG_INF("\n");473 474 if (params.interactive) {475 const char * control_message;476 if (params.multiline_input) {477 control_message = " - To return control to the AI, end your input with '\\'.\n"478 " - To return control without starting a new line, end your input with '/'.\n";479 } else {480 control_message = " - Press Return to return control to the AI.\n"481 " - To return control without starting a new line, end your input with '/'.\n"482 " - If you want to submit another line, end your input with '\\'.\n";483 }484 LOG_INF("== Running in interactive mode. ==\n");485#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)486 LOG_INF( " - Press Ctrl+C to interject at any time.\n");487#endif488 LOG_INF( "%s", control_message);489 if (params.conversation_mode && params.enable_chat_template && params.system_prompt.empty()) {490 LOG_INF( " - Not using system message. To change it, set a different value via -sys PROMPT\n");491 }492 LOG_INF("\n");493 494 is_interacting = params.interactive_first;495 }496 497 bool is_antiprompt = false;498 bool input_echo = true;499 bool display = true;500 501 int n_past = 0;502 int n_remain = params.n_predict;503 int n_consumed = 0;504 int n_session_consumed = 0;505 506 std::vector<int> input_tokens;507 std::vector<int> output_tokens;508 std::ostringstream output_ss;509 std::ostringstream assistant_ss; // for storing current assistant message, used in conversation mode510 511 // the first thing we will do is to output the prompt, so set color accordingly512 console::set_display(DISPLAY_TYPE_PROMPT);513 display = params.display_prompt;514 515 std::vector<llama_token> embd;516 517 // single-token antiprompts518 std::vector<llama_token> antiprompt_token;519 520 for (const std::string & antiprompt : params.antiprompt) {521 auto ids = ::common_tokenize(ctx, antiprompt, false, true);522 if (ids.size() == 1) {523 antiprompt_token.push_back(ids[0]);524 }525 }526 527 if (llama_model_has_encoder(model)) {528 int enc_input_size = embd_inp.size();529 llama_token * enc_input_buf = embd_inp.data();530 531 if (llama_encode(ctx, llama_batch_get_one(enc_input_buf, enc_input_size))) {532 LOG_ERR("%s : failed to eval\n", __func__);533 return 1;534 }535 536 llama_token decoder_start_token_id = llama_model_decoder_start_token(model);537 if (decoder_start_token_id == LLAMA_TOKEN_NULL) {538 decoder_start_token_id = llama_vocab_bos(vocab);539 }540 541 embd_inp.clear();542 embd_inp.push_back(decoder_start_token_id);543 }544 545 while ((n_remain != 0 && !is_antiprompt) || params.interactive) {546 // predict547 if (!embd.empty()) {548 // Note: (n_ctx - 4) here is to match the logic for commandline prompt handling via549 // --prompt or --file which uses the same value.550 int max_embd_size = n_ctx - 4;551 552 // Ensure the input doesn't exceed the context size by truncating embd if necessary.553 if ((int) embd.size() > max_embd_size) {554 const int skipped_tokens = (int) embd.size() - max_embd_size;555 embd.resize(max_embd_size);556 557 console::set_display(DISPLAY_TYPE_ERROR);558 LOG_WRN("<<input too long: skipped %d token%s>>", skipped_tokens, skipped_tokens != 1 ? "s" : "");559 console::set_display(DISPLAY_TYPE_RESET);560 }561 562 if (ga_n == 1) {563 // infinite text generation via context shifting564 // if we run out of context:565 // - take the n_keep first tokens from the original prompt (via n_past)566 // - take half of the last (n_ctx - n_keep) tokens and recompute the logits in batches567 568 if (n_past + (int) embd.size() >= n_ctx) {569 if (!params.ctx_shift){570 LOG_WRN("\n\n%s: context full and context shift is disabled => stopping\n", __func__);571 break;572 }573 574 if (params.n_predict == -2) {575 LOG_WRN("\n\n%s: context full and n_predict == %d => stopping\n", __func__, params.n_predict);576 break;577 }578 579 const int n_left = n_past - params.n_keep;580 const int n_discard = n_left/2;581 582 LOG_DBG("context full, swapping: n_past = %d, n_left = %d, n_ctx = %d, n_keep = %d, n_discard = %d\n",583 n_past, n_left, n_ctx, params.n_keep, n_discard);584 585 llama_memory_seq_rm (mem, 0, params.n_keep , params.n_keep + n_discard);586 llama_memory_seq_add(mem, 0, params.n_keep + n_discard, n_past, -n_discard);587 588 n_past -= n_discard;589 590 LOG_DBG("after swap: n_past = %d\n", n_past);591 592 LOG_DBG("embd: %s\n", string_from(ctx, embd).c_str());593 594 LOG_DBG("clear session path\n");595 path_session.clear();596 }597 } else {598 // context extension via Self-Extend599 while (n_past >= ga_i + ga_w) {600 const int ib = (ga_n*ga_i)/ga_w;601 const int bd = (ga_w/ga_n)*(ga_n - 1);602 const int dd = (ga_w/ga_n) - ib*bd - ga_w;603 604 LOG_DBG("\n");605 LOG_DBG("shift: [%6d, %6d] + %6d -> [%6d, %6d]\n", ga_i, n_past, ib*bd, ga_i + ib*bd, n_past + ib*bd);606 LOG_DBG("div: [%6d, %6d] / %6d -> [%6d, %6d]\n", ga_i + ib*bd, ga_i + ib*bd + ga_w, ga_n, (ga_i + ib*bd)/ga_n, (ga_i + ib*bd + ga_w)/ga_n);607 LOG_DBG("shift: [%6d, %6d] + %6d -> [%6d, %6d]\n", ga_i + ib*bd + ga_w, n_past + ib*bd, dd, ga_i + ib*bd + ga_w + dd, n_past + ib*bd + dd);608 609 llama_memory_seq_add(mem, 0, ga_i, n_past, ib*bd);610 llama_memory_seq_div(mem, 0, ga_i + ib*bd, ga_i + ib*bd + ga_w, ga_n);611 llama_memory_seq_add(mem, 0, ga_i + ib*bd + ga_w, n_past + ib*bd, dd);612 613 n_past -= bd;614 615 ga_i += ga_w/ga_n;616 617 LOG_DBG("\nn_past_old = %d, n_past = %d, ga_i = %d\n\n", n_past + bd, n_past, ga_i);618 }619 }620 621 // try to reuse a matching prefix from the loaded session instead of re-eval (via n_past)622 if (n_session_consumed < (int) session_tokens.size()) {623 size_t i = 0;624 for ( ; i < embd.size(); i++) {625 if (embd[i] != session_tokens[n_session_consumed]) {626 session_tokens.resize(n_session_consumed);627 break;628 }629 630 n_past++;631 n_session_consumed++;632 633 if (n_session_consumed >= (int) session_tokens.size()) {634 ++i;635 break;636 }637 }638 if (i > 0) {639 embd.erase(embd.begin(), embd.begin() + i);640 }641 }642 643 if (!embd.empty()) {644 const bool is_last_batch = (n_consumed >= (int) embd_inp.size());645 const bool save_now = session_do_save && is_last_batch;646 session_tokens.insert(session_tokens.end(), embd.begin(), embd.end());647 if (!common_prompt_batch_decode(ctx, session_tokens, embd.size(), n_past, params.n_batch, path_session, save_now)) {648 return 1;649 }650 n_session_consumed += embd.size();651 if (save_now) {652 session_do_save = false;653 }654 655 LOG_DBG("n_past = %d\n", n_past);656 657 // Display total tokens alongside total time658 if (params.n_print > 0 && n_past % params.n_print == 0) {659 LOG_DBG("\n\033[31mTokens consumed so far = %d / %d \033[0m\n", n_past, n_ctx);660 }661 }662 }663 664 embd.clear();665 666 if ((int) embd_inp.size() <= n_consumed && !is_interacting) {667 668 const llama_token id = common_sampler_sample(smpl, ctx, -1);669 670 common_sampler_accept(smpl, id, /* accept_grammar= */ true);671 672 // LOG_DBG("last: %s\n", string_from(ctx, smpl->prev.to_vector()).c_str());673 674 embd.push_back(id);675 676 if (params.conversation_mode && !waiting_for_first_input && !llama_vocab_is_eog(vocab, id)) {677 assistant_ss << common_token_to_piece(ctx, id, false);678 }679 680 // echo this to console681 input_echo = true;682 683 // decrement remaining sampling budget684 --n_remain;685 686 LOG_DBG("n_remain: %d\n", n_remain);687 } else {688 // some user input remains from prompt or interaction, forward it to processing689 LOG_DBG("embd_inp.size(): %d, n_consumed: %d\n", (int) embd_inp.size(), n_consumed);690 while ((int) embd_inp.size() > n_consumed) {691 embd.push_back(embd_inp[n_consumed]);692 693 // push the prompt in the sampling context in order to apply repetition penalties later694 // for the prompt, we don't apply grammar rules695 common_sampler_accept(smpl, embd_inp[n_consumed], /* accept_grammar= */ false);696 697 ++n_consumed;698 if ((int) embd.size() == params.n_batch) {699 break;700 }701 }702 }703 704 // display text705 if (input_echo && display) {706 for (auto id : embd) {707 const std::string token_str = common_token_to_piece(ctx, id, params.special);708 709 // Console/Stream Output710 LOG("%s", token_str.c_str());711 712 // Record Displayed Tokens To Log713 // Note: Generated tokens are created one by one hence this check714 if (embd.size() > 1) {715 // Incoming Requested Tokens716 input_tokens.push_back(id);717 } else {718 // Outgoing Generated Tokens719 output_tokens.push_back(id);720 output_ss << token_str;721 }722 }723 }724 725 // reset color to default if there is no pending user input726 if (input_echo && (int) embd_inp.size() == n_consumed) {727 console::set_display(DISPLAY_TYPE_RESET);728 display = true;729 }730 731 // if not currently processing queued inputs;732 if ((int) embd_inp.size() <= n_consumed) {733 // check for reverse prompt in the last n_prev tokens734 if (!params.antiprompt.empty()) {735 const int n_prev = 32;736 const std::string last_output = common_sampler_prev_str(smpl, ctx, n_prev);737 738 is_antiprompt = false;739 // Check if each of the reverse prompts appears at the end of the output.740 // If we're not running interactively, the reverse prompt might be tokenized with some following characters741 // so we'll compensate for that by widening the search window a bit.742 for (std::string & antiprompt : params.antiprompt) {743 size_t extra_padding = params.interactive ? 0 : 2;744 size_t search_start_pos = last_output.length() > static_cast<size_t>(antiprompt.length() + extra_padding)745 ? last_output.length() - static_cast<size_t>(antiprompt.length() + extra_padding)746 : 0;747 748 if (last_output.find(antiprompt, search_start_pos) != std::string::npos) {749 if (params.interactive) {750 is_interacting = true;751 }752 is_antiprompt = true;753 break;754 }755 }756 757 // check for reverse prompt using special tokens758 // avoid calling common_sampler_last() if last_output is empty759 if (!last_output.empty()) {760 llama_token last_token = common_sampler_last(smpl);761 for (auto token : antiprompt_token) {762 if (token == last_token) {763 if (params.interactive) {764 is_interacting = true;765 }766 is_antiprompt = true;767 break;768 }769 }770 }771 772 if (is_antiprompt) {773 LOG_DBG("found antiprompt: %s\n", last_output.c_str());774 }775 }776 777 // deal with end of generation tokens in interactive mode778 if (!waiting_for_first_input && llama_vocab_is_eog(vocab, common_sampler_last(smpl))) {779 LOG_DBG("found an EOG token\n");780 781 if (params.interactive) {782 if (!params.antiprompt.empty()) {783 // tokenize and inject first reverse prompt784 const auto first_antiprompt = common_tokenize(ctx, params.antiprompt.front(), false, true);785 embd_inp.insert(embd_inp.end(), first_antiprompt.begin(), first_antiprompt.end());786 is_antiprompt = true;787 }788 789 if (params.enable_chat_template) {790 chat_add_and_format("assistant", assistant_ss.str());791 }792 is_interacting = true;793 LOG("\n");794 }795 }796 797 if (params.conversation_mode && !waiting_for_first_input) {798 if (!prompt.empty()) {799 prompt.clear();800 is_interacting = false;801 }802 }803 804 if ((n_past > 0 || waiting_for_first_input) && is_interacting) {805 LOG_DBG("waiting for user input\n");806 807 if (params.conversation_mode) {808 LOG("\n> ");809 }810 811 if (params.input_prefix_bos) {812 LOG_DBG("adding input prefix BOS token\n");813 embd_inp.push_back(llama_vocab_bos(vocab));814 }815 816 std::string buffer;817 if (!params.input_prefix.empty() && !params.conversation_mode) {818 LOG_DBG("appending input prefix: '%s'\n", params.input_prefix.c_str());819 LOG("%s", params.input_prefix.c_str());820 }821 822 // color user input only823 console::set_display(DISPLAY_TYPE_USER_INPUT);824 display = params.display_prompt;825 826 std::string line;827 bool another_line = true;828 do {829 another_line = console::readline(line, params.multiline_input);830 buffer += line;831 } while (another_line);832 833 // done taking input, reset color834 console::set_display(DISPLAY_TYPE_RESET);835 display = true;836 837 if (buffer.empty()) { // Ctrl+D on empty line exits838 LOG("EOF by user\n");839 break;840 }841 842 if (buffer.back() == '\n') {843 // Implement #587:844 // If the user wants the text to end in a newline,845 // this should be accomplished by explicitly adding a newline by using \ followed by return,846 // then returning control by pressing return again.847 buffer.pop_back();848 }849 850 if (buffer.empty()) { // Enter key on empty line lets the user pass control back851 LOG_DBG("empty line, passing control back\n");852 } else { // Add tokens to embd only if the input buffer is non-empty853 // append input suffix if any854 if (!params.input_suffix.empty() && !params.conversation_mode) {855 LOG_DBG("appending input suffix: '%s'\n", params.input_suffix.c_str());856 LOG("%s", params.input_suffix.c_str());857 }858 859 LOG_DBG("buffer: '%s'\n", buffer.c_str());860 861 const size_t original_size = embd_inp.size();862 863 if (params.escape) {864 string_process_escapes(buffer);865 }866 867 bool format_chat = params.conversation_mode && params.enable_chat_template;868 std::string user_inp = format_chat869 ? chat_add_and_format("user", std::move(buffer))870 : std::move(buffer);871 // TODO: one inconvenient of current chat template implementation is that we can't distinguish between user input and special tokens (prefix/postfix)872 const auto line_pfx = common_tokenize(ctx, params.input_prefix, false, true);873 const auto line_inp = common_tokenize(ctx, user_inp, false, format_chat);874 const auto line_sfx = common_tokenize(ctx, params.input_suffix, false, true);875 876 LOG_DBG("input tokens: %s\n", string_from(ctx, line_inp).c_str());877 878 // if user stop generation mid-way, we must add EOT to finish model's last response879 if (need_insert_eot && format_chat) {880 llama_token eot = llama_vocab_eot(vocab);881 embd_inp.push_back(eot == LLAMA_TOKEN_NULL ? llama_vocab_eos(vocab) : eot);882 need_insert_eot = false;883 }884 885 embd_inp.insert(embd_inp.end(), line_pfx.begin(), line_pfx.end());886 embd_inp.insert(embd_inp.end(), line_inp.begin(), line_inp.end());887 embd_inp.insert(embd_inp.end(), line_sfx.begin(), line_sfx.end());888 889 if (params.verbose_prompt) {890 LOG_INF("%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size() - original_size);891 }892 893 for (size_t i = original_size; i < embd_inp.size(); ++i) {894 const llama_token token = embd_inp[i];895 const std::string token_str = common_token_to_piece(ctx, token);896 output_tokens.push_back(token);897 output_ss << token_str;898 899 if (params.verbose_prompt) {900 LOG_INF("%6d -> '%s'\n", token, token_str.c_str());901 }902 }903 904 // reset assistant message905 assistant_ss.str("");906 907 n_remain -= line_inp.size();908 LOG_DBG("n_remain: %d\n", n_remain);909 }910 911 input_echo = false; // do not echo this again912 }913 914 if (n_past > 0 || waiting_for_first_input) {915 if (is_interacting) {916 common_sampler_reset(smpl);917 }918 is_interacting = false;919 920 if (waiting_for_first_input && params.single_turn) {921 params.interactive = false;922 params.interactive_first = false;923 }924 waiting_for_first_input = false;925 }926 }927 928 // end of generation929 if (!embd.empty() && llama_vocab_is_eog(vocab, embd.back()) && !(params.interactive)) {930 LOG(" [end of text]\n");931 break;932 }933 934 // In interactive mode, respect the maximum number of tokens and drop back to user input when reached.935 // We skip this logic when n_predict == -1 (infinite) or -2 (stop at context size).936 if (params.interactive && n_remain <= 0 && params.n_predict >= 0) {937 n_remain = params.n_predict;938 is_interacting = true;939 }940 }941 942 if (!path_session.empty() && params.prompt_cache_all && !params.prompt_cache_ro) {943 LOG("\n%s: saving final output to session file '%s'\n", __func__, path_session.c_str());944 session_tokens.insert(session_tokens.end(), embd.begin(), embd.end());945 llama_state_save_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size());946 LOG_INF("saved final session to %s, n_tokens = %zu\n", path_session.data(), session_tokens.size());947 948 }949 950 LOG("\n\n");951 common_perf_print(ctx, smpl);952 953 llama_backend_free();954 955 return 0;956}957