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run.cpp 35 KB

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  1. #if defined(_WIN32)
  2. # include <windows.h>
  3. # include <io.h>
  4. #else
  5. # include <sys/file.h>
  6. # include <sys/ioctl.h>
  7. # include <unistd.h>
  8. #endif
  9. #if defined(LLAMA_USE_CURL)
  10. # include <curl/curl.h>
  11. #endif
  12. #include <signal.h>
  13. #include <climits>
  14. #include <cstdarg>
  15. #include <cstdio>
  16. #include <cstring>
  17. #include <filesystem>
  18. #include <iostream>
  19. #include <list>
  20. #include <sstream>
  21. #include <string>
  22. #include <vector>
  23. #include "common.h"
  24. #include "json.hpp"
  25. #include "linenoise.cpp/linenoise.h"
  26. #include "llama-cpp.h"
  27. #include "chat-template.hpp"
  28. #if defined(__unix__) || (defined(__APPLE__) && defined(__MACH__)) || defined(_WIN32)
  29. [[noreturn]] static void sigint_handler(int) {
  30. printf("\n\033[0m");
  31. exit(0); // not ideal, but it's the only way to guarantee exit in all cases
  32. }
  33. #endif
  34. GGML_ATTRIBUTE_FORMAT(1, 2)
  35. static std::string fmt(const char * fmt, ...) {
  36. va_list ap;
  37. va_list ap2;
  38. va_start(ap, fmt);
  39. va_copy(ap2, ap);
  40. const int size = vsnprintf(NULL, 0, fmt, ap);
  41. GGML_ASSERT(size >= 0 && size < INT_MAX); // NOLINT
  42. std::string buf;
  43. buf.resize(size);
  44. const int size2 = vsnprintf(const_cast<char *>(buf.data()), buf.size() + 1, fmt, ap2);
  45. GGML_ASSERT(size2 == size);
  46. va_end(ap2);
  47. va_end(ap);
  48. return buf;
  49. }
  50. GGML_ATTRIBUTE_FORMAT(1, 2)
  51. static int printe(const char * fmt, ...) {
  52. va_list args;
  53. va_start(args, fmt);
  54. const int ret = vfprintf(stderr, fmt, args);
  55. va_end(args);
  56. return ret;
  57. }
  58. class Opt {
  59. public:
  60. int init(int argc, const char ** argv) {
  61. ctx_params = llama_context_default_params();
  62. model_params = llama_model_default_params();
  63. context_size_default = ctx_params.n_batch;
  64. ngl_default = model_params.n_gpu_layers;
  65. common_params_sampling sampling;
  66. temperature_default = sampling.temp;
  67. if (argc < 2) {
  68. printe("Error: No arguments provided.\n");
  69. print_help();
  70. return 1;
  71. }
  72. // Parse arguments
  73. if (parse(argc, argv)) {
  74. printe("Error: Failed to parse arguments.\n");
  75. print_help();
  76. return 1;
  77. }
  78. // If help is requested, show help and exit
  79. if (help) {
  80. print_help();
  81. return 2;
  82. }
  83. ctx_params.n_batch = context_size >= 0 ? context_size : context_size_default;
  84. ctx_params.n_ctx = ctx_params.n_batch;
  85. model_params.n_gpu_layers = ngl >= 0 ? ngl : ngl_default;
  86. temperature = temperature >= 0 ? temperature : temperature_default;
  87. return 0; // Success
  88. }
  89. llama_context_params ctx_params;
  90. llama_model_params model_params;
  91. std::string model_;
  92. std::string user;
  93. bool use_jinja = false;
  94. int context_size = -1, ngl = -1;
  95. float temperature = -1;
  96. bool verbose = false;
  97. private:
  98. int context_size_default = -1, ngl_default = -1;
  99. float temperature_default = -1;
  100. bool help = false;
  101. bool parse_flag(const char ** argv, int i, const char * short_opt, const char * long_opt) {
  102. return strcmp(argv[i], short_opt) == 0 || strcmp(argv[i], long_opt) == 0;
  103. }
  104. int handle_option_with_value(int argc, const char ** argv, int & i, int & option_value) {
  105. if (i + 1 >= argc) {
  106. return 1;
  107. }
  108. option_value = std::atoi(argv[++i]);
  109. return 0;
  110. }
  111. int handle_option_with_value(int argc, const char ** argv, int & i, float & option_value) {
  112. if (i + 1 >= argc) {
  113. return 1;
  114. }
  115. option_value = std::atof(argv[++i]);
  116. return 0;
  117. }
  118. int parse(int argc, const char ** argv) {
  119. bool options_parsing = true;
  120. for (int i = 1, positional_args_i = 0; i < argc; ++i) {
  121. if (options_parsing && (strcmp(argv[i], "-c") == 0 || strcmp(argv[i], "--context-size") == 0)) {
  122. if (handle_option_with_value(argc, argv, i, context_size) == 1) {
  123. return 1;
  124. }
  125. } else if (options_parsing &&
  126. (strcmp(argv[i], "-n") == 0 || strcmp(argv[i], "-ngl") == 0 || strcmp(argv[i], "--ngl") == 0)) {
  127. if (handle_option_with_value(argc, argv, i, ngl) == 1) {
  128. return 1;
  129. }
  130. } else if (options_parsing && strcmp(argv[i], "--temp") == 0) {
  131. if (handle_option_with_value(argc, argv, i, temperature) == 1) {
  132. return 1;
  133. }
  134. } else if (options_parsing &&
  135. (parse_flag(argv, i, "-v", "--verbose") || parse_flag(argv, i, "-v", "--log-verbose"))) {
  136. verbose = true;
  137. } else if (options_parsing && strcmp(argv[i], "--jinja") == 0) {
  138. use_jinja = true;
  139. } else if (options_parsing && parse_flag(argv, i, "-h", "--help")) {
  140. help = true;
  141. return 0;
  142. } else if (options_parsing && strcmp(argv[i], "--") == 0) {
  143. options_parsing = false;
  144. } else if (positional_args_i == 0) {
  145. if (!argv[i][0] || argv[i][0] == '-') {
  146. return 1;
  147. }
  148. ++positional_args_i;
  149. model_ = argv[i];
  150. } else if (positional_args_i == 1) {
  151. ++positional_args_i;
  152. user = argv[i];
  153. } else {
  154. user += " " + std::string(argv[i]);
  155. }
  156. }
  157. return 0;
  158. }
  159. void print_help() const {
  160. printf(
  161. "Description:\n"
  162. " Runs a llm\n"
  163. "\n"
  164. "Usage:\n"
  165. " llama-run [options] model [prompt]\n"
  166. "\n"
  167. "Options:\n"
  168. " -c, --context-size <value>\n"
  169. " Context size (default: %d)\n"
  170. " -n, -ngl, --ngl <value>\n"
  171. " Number of GPU layers (default: %d)\n"
  172. " --temp <value>\n"
  173. " Temperature (default: %.1f)\n"
  174. " -v, --verbose, --log-verbose\n"
  175. " Set verbosity level to infinity (i.e. log all messages, useful for debugging)\n"
  176. " -h, --help\n"
  177. " Show help message\n"
  178. "\n"
  179. "Commands:\n"
  180. " model\n"
  181. " Model is a string with an optional prefix of \n"
  182. " huggingface:// (hf://), ollama://, https:// or file://.\n"
  183. " If no protocol is specified and a file exists in the specified\n"
  184. " path, file:// is assumed, otherwise if a file does not exist in\n"
  185. " the specified path, ollama:// is assumed. Models that are being\n"
  186. " pulled are downloaded with .partial extension while being\n"
  187. " downloaded and then renamed as the file without the .partial\n"
  188. " extension when complete.\n"
  189. "\n"
  190. "Examples:\n"
  191. " llama-run llama3\n"
  192. " llama-run ollama://granite-code\n"
  193. " llama-run ollama://smollm:135m\n"
  194. " llama-run hf://QuantFactory/SmolLM-135M-GGUF/SmolLM-135M.Q2_K.gguf\n"
  195. " llama-run "
  196. "huggingface://bartowski/SmolLM-1.7B-Instruct-v0.2-GGUF/SmolLM-1.7B-Instruct-v0.2-IQ3_M.gguf\n"
  197. " llama-run https://example.com/some-file1.gguf\n"
  198. " llama-run some-file2.gguf\n"
  199. " llama-run file://some-file3.gguf\n"
  200. " llama-run --ngl 999 some-file4.gguf\n"
  201. " llama-run --ngl 999 some-file5.gguf Hello World\n",
  202. context_size_default, ngl_default, temperature_default);
  203. }
  204. };
  205. struct progress_data {
  206. size_t file_size = 0;
  207. std::chrono::steady_clock::time_point start_time = std::chrono::steady_clock::now();
  208. bool printed = false;
  209. };
  210. static int get_terminal_width() {
  211. #if defined(_WIN32)
  212. CONSOLE_SCREEN_BUFFER_INFO csbi;
  213. GetConsoleScreenBufferInfo(GetStdHandle(STD_OUTPUT_HANDLE), &csbi);
  214. return csbi.srWindow.Right - csbi.srWindow.Left + 1;
  215. #else
  216. struct winsize w;
  217. ioctl(STDOUT_FILENO, TIOCGWINSZ, &w);
  218. return w.ws_col;
  219. #endif
  220. }
  221. #ifdef LLAMA_USE_CURL
  222. class File {
  223. public:
  224. FILE * file = nullptr;
  225. FILE * open(const std::string & filename, const char * mode) {
  226. file = fopen(filename.c_str(), mode);
  227. return file;
  228. }
  229. int lock() {
  230. if (file) {
  231. # ifdef _WIN32
  232. fd = _fileno(file);
  233. hFile = (HANDLE) _get_osfhandle(fd);
  234. if (hFile == INVALID_HANDLE_VALUE) {
  235. fd = -1;
  236. return 1;
  237. }
  238. OVERLAPPED overlapped = {};
  239. if (!LockFileEx(hFile, LOCKFILE_EXCLUSIVE_LOCK | LOCKFILE_FAIL_IMMEDIATELY, 0, MAXDWORD, MAXDWORD,
  240. &overlapped)) {
  241. fd = -1;
  242. return 1;
  243. }
  244. # else
  245. fd = fileno(file);
  246. if (flock(fd, LOCK_EX | LOCK_NB) != 0) {
  247. fd = -1;
  248. return 1;
  249. }
  250. # endif
  251. }
  252. return 0;
  253. }
  254. ~File() {
  255. if (fd >= 0) {
  256. # ifdef _WIN32
  257. if (hFile != INVALID_HANDLE_VALUE) {
  258. OVERLAPPED overlapped = {};
  259. UnlockFileEx(hFile, 0, MAXDWORD, MAXDWORD, &overlapped);
  260. }
  261. # else
  262. flock(fd, LOCK_UN);
  263. # endif
  264. }
  265. if (file) {
  266. fclose(file);
  267. }
  268. }
  269. private:
  270. int fd = -1;
  271. # ifdef _WIN32
  272. HANDLE hFile = nullptr;
  273. # endif
  274. };
  275. class HttpClient {
  276. public:
  277. int init(const std::string & url, const std::vector<std::string> & headers, const std::string & output_file,
  278. const bool progress, std::string * response_str = nullptr) {
  279. std::string output_file_partial;
  280. curl = curl_easy_init();
  281. if (!curl) {
  282. return 1;
  283. }
  284. progress_data data;
  285. File out;
  286. if (!output_file.empty()) {
  287. output_file_partial = output_file + ".partial";
  288. if (!out.open(output_file_partial, "ab")) {
  289. printe("Failed to open file\n");
  290. return 1;
  291. }
  292. if (out.lock()) {
  293. printe("Failed to exclusively lock file\n");
  294. return 1;
  295. }
  296. }
  297. set_write_options(response_str, out);
  298. data.file_size = set_resume_point(output_file_partial);
  299. set_progress_options(progress, data);
  300. set_headers(headers);
  301. perform(url);
  302. if (!output_file.empty()) {
  303. std::filesystem::rename(output_file_partial, output_file);
  304. }
  305. return 0;
  306. }
  307. ~HttpClient() {
  308. if (chunk) {
  309. curl_slist_free_all(chunk);
  310. }
  311. if (curl) {
  312. curl_easy_cleanup(curl);
  313. }
  314. }
  315. private:
  316. CURL * curl = nullptr;
  317. struct curl_slist * chunk = nullptr;
  318. void set_write_options(std::string * response_str, const File & out) {
  319. if (response_str) {
  320. curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, capture_data);
  321. curl_easy_setopt(curl, CURLOPT_WRITEDATA, response_str);
  322. } else {
  323. curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, write_data);
  324. curl_easy_setopt(curl, CURLOPT_WRITEDATA, out.file);
  325. }
  326. }
  327. size_t set_resume_point(const std::string & output_file) {
  328. size_t file_size = 0;
  329. if (std::filesystem::exists(output_file)) {
  330. file_size = std::filesystem::file_size(output_file);
  331. curl_easy_setopt(curl, CURLOPT_RESUME_FROM_LARGE, static_cast<curl_off_t>(file_size));
  332. }
  333. return file_size;
  334. }
  335. void set_progress_options(bool progress, progress_data & data) {
  336. if (progress) {
  337. curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 0L);
  338. curl_easy_setopt(curl, CURLOPT_XFERINFODATA, &data);
  339. curl_easy_setopt(curl, CURLOPT_XFERINFOFUNCTION, update_progress);
  340. }
  341. }
  342. void set_headers(const std::vector<std::string> & headers) {
  343. if (!headers.empty()) {
  344. if (chunk) {
  345. curl_slist_free_all(chunk);
  346. chunk = 0;
  347. }
  348. for (const auto & header : headers) {
  349. chunk = curl_slist_append(chunk, header.c_str());
  350. }
  351. curl_easy_setopt(curl, CURLOPT_HTTPHEADER, chunk);
  352. }
  353. }
  354. void perform(const std::string & url) {
  355. CURLcode res;
  356. curl_easy_setopt(curl, CURLOPT_URL, url.c_str());
  357. curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
  358. curl_easy_setopt(curl, CURLOPT_DEFAULT_PROTOCOL, "https");
  359. curl_easy_setopt(curl, CURLOPT_FAILONERROR, 1L);
  360. res = curl_easy_perform(curl);
  361. if (res != CURLE_OK) {
  362. printe("curl_easy_perform() failed: %s\n", curl_easy_strerror(res));
  363. }
  364. }
  365. static std::string human_readable_time(double seconds) {
  366. int hrs = static_cast<int>(seconds) / 3600;
  367. int mins = (static_cast<int>(seconds) % 3600) / 60;
  368. int secs = static_cast<int>(seconds) % 60;
  369. if (hrs > 0) {
  370. return fmt("%dh %02dm %02ds", hrs, mins, secs);
  371. } else if (mins > 0) {
  372. return fmt("%dm %02ds", mins, secs);
  373. } else {
  374. return fmt("%ds", secs);
  375. }
  376. }
  377. static std::string human_readable_size(curl_off_t size) {
  378. static const char * suffix[] = { "B", "KB", "MB", "GB", "TB" };
  379. char length = sizeof(suffix) / sizeof(suffix[0]);
  380. int i = 0;
  381. double dbl_size = size;
  382. if (size > 1024) {
  383. for (i = 0; (size / 1024) > 0 && i < length - 1; i++, size /= 1024) {
  384. dbl_size = size / 1024.0;
  385. }
  386. }
  387. return fmt("%.2f %s", dbl_size, suffix[i]);
  388. }
  389. static int update_progress(void * ptr, curl_off_t total_to_download, curl_off_t now_downloaded, curl_off_t,
  390. curl_off_t) {
  391. progress_data * data = static_cast<progress_data *>(ptr);
  392. if (total_to_download <= 0) {
  393. return 0;
  394. }
  395. total_to_download += data->file_size;
  396. const curl_off_t now_downloaded_plus_file_size = now_downloaded + data->file_size;
  397. const curl_off_t percentage = calculate_percentage(now_downloaded_plus_file_size, total_to_download);
  398. std::string progress_prefix = generate_progress_prefix(percentage);
  399. const double speed = calculate_speed(now_downloaded, data->start_time);
  400. const double tim = (total_to_download - now_downloaded) / speed;
  401. std::string progress_suffix =
  402. generate_progress_suffix(now_downloaded_plus_file_size, total_to_download, speed, tim);
  403. int progress_bar_width = calculate_progress_bar_width(progress_prefix, progress_suffix);
  404. std::string progress_bar;
  405. generate_progress_bar(progress_bar_width, percentage, progress_bar);
  406. print_progress(progress_prefix, progress_bar, progress_suffix);
  407. data->printed = true;
  408. return 0;
  409. }
  410. static curl_off_t calculate_percentage(curl_off_t now_downloaded_plus_file_size, curl_off_t total_to_download) {
  411. return (now_downloaded_plus_file_size * 100) / total_to_download;
  412. }
  413. static std::string generate_progress_prefix(curl_off_t percentage) { return fmt("%3ld%% |", static_cast<long int>(percentage)); }
  414. static double calculate_speed(curl_off_t now_downloaded, const std::chrono::steady_clock::time_point & start_time) {
  415. const auto now = std::chrono::steady_clock::now();
  416. const std::chrono::duration<double> elapsed_seconds = now - start_time;
  417. return now_downloaded / elapsed_seconds.count();
  418. }
  419. static std::string generate_progress_suffix(curl_off_t now_downloaded_plus_file_size, curl_off_t total_to_download,
  420. double speed, double estimated_time) {
  421. const int width = 10;
  422. return fmt("%*s/%*s%*s/s%*s", width, human_readable_size(now_downloaded_plus_file_size).c_str(), width,
  423. human_readable_size(total_to_download).c_str(), width, human_readable_size(speed).c_str(), width,
  424. human_readable_time(estimated_time).c_str());
  425. }
  426. static int calculate_progress_bar_width(const std::string & progress_prefix, const std::string & progress_suffix) {
  427. int progress_bar_width = get_terminal_width() - progress_prefix.size() - progress_suffix.size() - 3;
  428. if (progress_bar_width < 1) {
  429. progress_bar_width = 1;
  430. }
  431. return progress_bar_width;
  432. }
  433. static std::string generate_progress_bar(int progress_bar_width, curl_off_t percentage,
  434. std::string & progress_bar) {
  435. const curl_off_t pos = (percentage * progress_bar_width) / 100;
  436. for (int i = 0; i < progress_bar_width; ++i) {
  437. progress_bar.append((i < pos) ? "█" : " ");
  438. }
  439. return progress_bar;
  440. }
  441. static void print_progress(const std::string & progress_prefix, const std::string & progress_bar,
  442. const std::string & progress_suffix) {
  443. printe("\r%*s\r%s%s| %s", get_terminal_width(), " ", progress_prefix.c_str(), progress_bar.c_str(),
  444. progress_suffix.c_str());
  445. }
  446. // Function to write data to a file
  447. static size_t write_data(void * ptr, size_t size, size_t nmemb, void * stream) {
  448. FILE * out = static_cast<FILE *>(stream);
  449. return fwrite(ptr, size, nmemb, out);
  450. }
  451. // Function to capture data into a string
  452. static size_t capture_data(void * ptr, size_t size, size_t nmemb, void * stream) {
  453. std::string * str = static_cast<std::string *>(stream);
  454. str->append(static_cast<char *>(ptr), size * nmemb);
  455. return size * nmemb;
  456. }
  457. };
  458. #endif
  459. class LlamaData {
  460. public:
  461. llama_model_ptr model;
  462. llama_sampler_ptr sampler;
  463. llama_context_ptr context;
  464. std::vector<llama_chat_message> messages;
  465. std::list<std::string> msg_strs;
  466. std::vector<char> fmtted;
  467. int init(Opt & opt) {
  468. model = initialize_model(opt);
  469. if (!model) {
  470. return 1;
  471. }
  472. context = initialize_context(model, opt);
  473. if (!context) {
  474. return 1;
  475. }
  476. sampler = initialize_sampler(opt);
  477. return 0;
  478. }
  479. private:
  480. #ifdef LLAMA_USE_CURL
  481. int download(const std::string & url, const std::vector<std::string> & headers, const std::string & output_file,
  482. const bool progress, std::string * response_str = nullptr) {
  483. HttpClient http;
  484. if (http.init(url, headers, output_file, progress, response_str)) {
  485. return 1;
  486. }
  487. return 0;
  488. }
  489. #else
  490. int download(const std::string &, const std::vector<std::string> &, const std::string &, const bool,
  491. std::string * = nullptr) {
  492. printe("%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__);
  493. return 1;
  494. }
  495. #endif
  496. int huggingface_dl(const std::string & model, const std::vector<std::string> headers, const std::string & bn) {
  497. // Find the second occurrence of '/' after protocol string
  498. size_t pos = model.find('/');
  499. pos = model.find('/', pos + 1);
  500. if (pos == std::string::npos) {
  501. return 1;
  502. }
  503. const std::string hfr = model.substr(0, pos);
  504. const std::string hff = model.substr(pos + 1);
  505. const std::string url = "https://huggingface.co/" + hfr + "/resolve/main/" + hff;
  506. return download(url, headers, bn, true);
  507. }
  508. int ollama_dl(std::string & model, const std::vector<std::string> headers, const std::string & bn) {
  509. if (model.find('/') == std::string::npos) {
  510. model = "library/" + model;
  511. }
  512. std::string model_tag = "latest";
  513. size_t colon_pos = model.find(':');
  514. if (colon_pos != std::string::npos) {
  515. model_tag = model.substr(colon_pos + 1);
  516. model = model.substr(0, colon_pos);
  517. }
  518. std::string manifest_url = "https://registry.ollama.ai/v2/" + model + "/manifests/" + model_tag;
  519. std::string manifest_str;
  520. const int ret = download(manifest_url, headers, "", false, &manifest_str);
  521. if (ret) {
  522. return ret;
  523. }
  524. nlohmann::json manifest = nlohmann::json::parse(manifest_str);
  525. std::string layer;
  526. for (const auto & l : manifest["layers"]) {
  527. if (l["mediaType"] == "application/vnd.ollama.image.model") {
  528. layer = l["digest"];
  529. break;
  530. }
  531. }
  532. std::string blob_url = "https://registry.ollama.ai/v2/" + model + "/blobs/" + layer;
  533. return download(blob_url, headers, bn, true);
  534. }
  535. std::string basename(const std::string & path) {
  536. const size_t pos = path.find_last_of("/\\");
  537. if (pos == std::string::npos) {
  538. return path;
  539. }
  540. return path.substr(pos + 1);
  541. }
  542. int rm_until_substring(std::string & model_, const std::string & substring) {
  543. const std::string::size_type pos = model_.find(substring);
  544. if (pos == std::string::npos) {
  545. return 1;
  546. }
  547. model_ = model_.substr(pos + substring.size()); // Skip past the substring
  548. return 0;
  549. }
  550. int resolve_model(std::string & model_) {
  551. int ret = 0;
  552. if (string_starts_with(model_, "file://") || std::filesystem::exists(model_)) {
  553. rm_until_substring(model_, "://");
  554. return ret;
  555. }
  556. const std::string bn = basename(model_);
  557. const std::vector<std::string> headers = { "--header",
  558. "Accept: application/vnd.docker.distribution.manifest.v2+json" };
  559. if (string_starts_with(model_, "hf://") || string_starts_with(model_, "huggingface://")) {
  560. rm_until_substring(model_, "://");
  561. ret = huggingface_dl(model_, headers, bn);
  562. } else if (string_starts_with(model_, "hf.co/")) {
  563. rm_until_substring(model_, "hf.co/");
  564. ret = huggingface_dl(model_, headers, bn);
  565. } else if (string_starts_with(model_, "ollama://")) {
  566. rm_until_substring(model_, "://");
  567. ret = ollama_dl(model_, headers, bn);
  568. } else if (string_starts_with(model_, "https://")) {
  569. ret = download(model_, headers, bn, true);
  570. } else {
  571. ret = ollama_dl(model_, headers, bn);
  572. }
  573. model_ = bn;
  574. return ret;
  575. }
  576. // Initializes the model and returns a unique pointer to it
  577. llama_model_ptr initialize_model(Opt & opt) {
  578. ggml_backend_load_all();
  579. resolve_model(opt.model_);
  580. printe(
  581. "\r%*s"
  582. "\rLoading model",
  583. get_terminal_width(), " ");
  584. llama_model_ptr model(llama_model_load_from_file(opt.model_.c_str(), opt.model_params));
  585. if (!model) {
  586. printe("%s: error: unable to load model from file: %s\n", __func__, opt.model_.c_str());
  587. }
  588. printe("\r%*s\r", static_cast<int>(sizeof("Loading model")), " ");
  589. return model;
  590. }
  591. // Initializes the context with the specified parameters
  592. llama_context_ptr initialize_context(const llama_model_ptr & model, const Opt & opt) {
  593. llama_context_ptr context(llama_init_from_model(model.get(), opt.ctx_params));
  594. if (!context) {
  595. printe("%s: error: failed to create the llama_context\n", __func__);
  596. }
  597. return context;
  598. }
  599. // Initializes and configures the sampler
  600. llama_sampler_ptr initialize_sampler(const Opt & opt) {
  601. llama_sampler_ptr sampler(llama_sampler_chain_init(llama_sampler_chain_default_params()));
  602. llama_sampler_chain_add(sampler.get(), llama_sampler_init_min_p(0.05f, 1));
  603. llama_sampler_chain_add(sampler.get(), llama_sampler_init_temp(opt.temperature));
  604. llama_sampler_chain_add(sampler.get(), llama_sampler_init_dist(LLAMA_DEFAULT_SEED));
  605. return sampler;
  606. }
  607. };
  608. // Add a message to `messages` and store its content in `msg_strs`
  609. static void add_message(const char * role, const std::string & text, LlamaData & llama_data) {
  610. llama_data.msg_strs.push_back(std::move(text));
  611. llama_data.messages.push_back({ role, llama_data.msg_strs.back().c_str() });
  612. }
  613. // Function to apply the chat template and resize `formatted` if needed
  614. static int apply_chat_template(const common_chat_template & tmpl, LlamaData & llama_data, const bool append, bool use_jinja) {
  615. if (use_jinja) {
  616. json messages = json::array();
  617. for (const auto & msg : llama_data.messages) {
  618. messages.push_back({
  619. {"role", msg.role},
  620. {"content", msg.content},
  621. });
  622. }
  623. try {
  624. auto result = tmpl.apply(messages, /* tools= */ json(), append);
  625. llama_data.fmtted.resize(result.size() + 1);
  626. memcpy(llama_data.fmtted.data(), result.c_str(), result.size() + 1);
  627. return result.size();
  628. } catch (const std::exception & e) {
  629. printe("failed to render the chat template: %s\n", e.what());
  630. return -1;
  631. }
  632. }
  633. int result = llama_chat_apply_template(
  634. tmpl.source().c_str(), llama_data.messages.data(), llama_data.messages.size(), append,
  635. append ? llama_data.fmtted.data() : nullptr, append ? llama_data.fmtted.size() : 0);
  636. if (append && result > static_cast<int>(llama_data.fmtted.size())) {
  637. llama_data.fmtted.resize(result);
  638. result = llama_chat_apply_template(tmpl.source().c_str(), llama_data.messages.data(),
  639. llama_data.messages.size(), append, llama_data.fmtted.data(),
  640. llama_data.fmtted.size());
  641. }
  642. return result;
  643. }
  644. // Function to tokenize the prompt
  645. static int tokenize_prompt(const llama_vocab * vocab, const std::string & prompt,
  646. std::vector<llama_token> & prompt_tokens, const LlamaData & llama_data) {
  647. const bool is_first = llama_get_kv_cache_used_cells(llama_data.context.get()) == 0;
  648. const int n_prompt_tokens = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), NULL, 0, is_first, true);
  649. prompt_tokens.resize(n_prompt_tokens);
  650. if (llama_tokenize(vocab, prompt.c_str(), prompt.size(), prompt_tokens.data(), prompt_tokens.size(), is_first,
  651. true) < 0) {
  652. printe("failed to tokenize the prompt\n");
  653. return -1;
  654. }
  655. return n_prompt_tokens;
  656. }
  657. // Check if we have enough space in the context to evaluate this batch
  658. static int check_context_size(const llama_context_ptr & ctx, const llama_batch & batch) {
  659. const int n_ctx = llama_n_ctx(ctx.get());
  660. const int n_ctx_used = llama_get_kv_cache_used_cells(ctx.get());
  661. if (n_ctx_used + batch.n_tokens > n_ctx) {
  662. printf("\033[0m\n");
  663. printe("context size exceeded\n");
  664. return 1;
  665. }
  666. return 0;
  667. }
  668. // convert the token to a string
  669. static int convert_token_to_string(const llama_vocab * vocab, const llama_token token_id, std::string & piece) {
  670. char buf[256];
  671. int n = llama_token_to_piece(vocab, token_id, buf, sizeof(buf), 0, true);
  672. if (n < 0) {
  673. printe("failed to convert token to piece\n");
  674. return 1;
  675. }
  676. piece = std::string(buf, n);
  677. return 0;
  678. }
  679. static void print_word_and_concatenate_to_response(const std::string & piece, std::string & response) {
  680. printf("%s", piece.c_str());
  681. fflush(stdout);
  682. response += piece;
  683. }
  684. // helper function to evaluate a prompt and generate a response
  685. static int generate(LlamaData & llama_data, const std::string & prompt, std::string & response) {
  686. const llama_vocab * vocab = llama_model_get_vocab(llama_data.model.get());
  687. std::vector<llama_token> tokens;
  688. if (tokenize_prompt(vocab, prompt, tokens, llama_data) < 0) {
  689. return 1;
  690. }
  691. // prepare a batch for the prompt
  692. llama_batch batch = llama_batch_get_one(tokens.data(), tokens.size());
  693. llama_token new_token_id;
  694. while (true) {
  695. check_context_size(llama_data.context, batch);
  696. if (llama_decode(llama_data.context.get(), batch)) {
  697. printe("failed to decode\n");
  698. return 1;
  699. }
  700. // sample the next token, check is it an end of generation?
  701. new_token_id = llama_sampler_sample(llama_data.sampler.get(), llama_data.context.get(), -1);
  702. if (llama_vocab_is_eog(vocab, new_token_id)) {
  703. break;
  704. }
  705. std::string piece;
  706. if (convert_token_to_string(vocab, new_token_id, piece)) {
  707. return 1;
  708. }
  709. print_word_and_concatenate_to_response(piece, response);
  710. // prepare the next batch with the sampled token
  711. batch = llama_batch_get_one(&new_token_id, 1);
  712. }
  713. printf("\033[0m");
  714. return 0;
  715. }
  716. static int read_user_input(std::string & user_input) {
  717. static const char * prompt_prefix = "> ";
  718. #ifdef WIN32
  719. printf(
  720. "\r%*s"
  721. "\r\033[0m%s",
  722. get_terminal_width(), " ", prompt_prefix);
  723. std::getline(std::cin, user_input);
  724. if (std::cin.eof()) {
  725. printf("\n");
  726. return 1;
  727. }
  728. #else
  729. std::unique_ptr<char, decltype(&std::free)> line(const_cast<char *>(linenoise(prompt_prefix)), free);
  730. if (!line) {
  731. return 1;
  732. }
  733. user_input = line.get();
  734. #endif
  735. if (user_input == "/bye") {
  736. return 1;
  737. }
  738. if (user_input.empty()) {
  739. return 2;
  740. }
  741. #ifndef WIN32
  742. linenoiseHistoryAdd(line.get());
  743. #endif
  744. return 0; // Should have data in happy path
  745. }
  746. // Function to generate a response based on the prompt
  747. static int generate_response(LlamaData & llama_data, const std::string & prompt, std::string & response,
  748. const bool stdout_a_terminal) {
  749. // Set response color
  750. if (stdout_a_terminal) {
  751. printf("\033[33m");
  752. }
  753. if (generate(llama_data, prompt, response)) {
  754. printe("failed to generate response\n");
  755. return 1;
  756. }
  757. // End response with color reset and newline
  758. printf("\n%s", stdout_a_terminal ? "\033[0m" : "");
  759. return 0;
  760. }
  761. // Helper function to apply the chat template and handle errors
  762. static int apply_chat_template_with_error_handling(const common_chat_template & tmpl, LlamaData & llama_data, const bool append, int & output_length, bool use_jinja) {
  763. const int new_len = apply_chat_template(tmpl, llama_data, append, use_jinja);
  764. if (new_len < 0) {
  765. printe("failed to apply the chat template\n");
  766. return -1;
  767. }
  768. output_length = new_len;
  769. return 0;
  770. }
  771. // Helper function to handle user input
  772. static int handle_user_input(std::string & user_input, const std::string & user) {
  773. if (!user.empty()) {
  774. user_input = user;
  775. return 0; // No need for interactive input
  776. }
  777. return read_user_input(user_input); // Returns true if input ends the loop
  778. }
  779. static bool is_stdin_a_terminal() {
  780. #if defined(_WIN32)
  781. HANDLE hStdin = GetStdHandle(STD_INPUT_HANDLE);
  782. DWORD mode;
  783. return GetConsoleMode(hStdin, &mode);
  784. #else
  785. return isatty(STDIN_FILENO);
  786. #endif
  787. }
  788. static bool is_stdout_a_terminal() {
  789. #if defined(_WIN32)
  790. HANDLE hStdout = GetStdHandle(STD_OUTPUT_HANDLE);
  791. DWORD mode;
  792. return GetConsoleMode(hStdout, &mode);
  793. #else
  794. return isatty(STDOUT_FILENO);
  795. #endif
  796. }
  797. // Function to handle user input
  798. static int get_user_input(std::string & user_input, const std::string & user) {
  799. while (true) {
  800. const int ret = handle_user_input(user_input, user);
  801. if (ret == 1) {
  802. return 1;
  803. }
  804. if (ret == 2) {
  805. continue;
  806. }
  807. break;
  808. }
  809. return 0;
  810. }
  811. // Main chat loop function
  812. static int chat_loop(LlamaData & llama_data, const std::string & user, bool use_jinja) {
  813. int prev_len = 0;
  814. llama_data.fmtted.resize(llama_n_ctx(llama_data.context.get()));
  815. auto chat_templates = common_chat_templates_from_model(llama_data.model.get(), "");
  816. GGML_ASSERT(chat_templates.template_default);
  817. static const bool stdout_a_terminal = is_stdout_a_terminal();
  818. while (true) {
  819. // Get user input
  820. std::string user_input;
  821. if (get_user_input(user_input, user) == 1) {
  822. return 0;
  823. }
  824. add_message("user", user.empty() ? user_input : user, llama_data);
  825. int new_len;
  826. if (apply_chat_template_with_error_handling(*chat_templates.template_default, llama_data, true, new_len, use_jinja) < 0) {
  827. return 1;
  828. }
  829. std::string prompt(llama_data.fmtted.begin() + prev_len, llama_data.fmtted.begin() + new_len);
  830. std::string response;
  831. if (generate_response(llama_data, prompt, response, stdout_a_terminal)) {
  832. return 1;
  833. }
  834. if (!user.empty()) {
  835. break;
  836. }
  837. add_message("assistant", response, llama_data);
  838. if (apply_chat_template_with_error_handling(*chat_templates.template_default, llama_data, false, prev_len, use_jinja) < 0) {
  839. return 1;
  840. }
  841. }
  842. return 0;
  843. }
  844. static void log_callback(const enum ggml_log_level level, const char * text, void * p) {
  845. const Opt * opt = static_cast<Opt *>(p);
  846. if (opt->verbose || level == GGML_LOG_LEVEL_ERROR) {
  847. printe("%s", text);
  848. }
  849. }
  850. static std::string read_pipe_data() {
  851. std::ostringstream result;
  852. result << std::cin.rdbuf(); // Read all data from std::cin
  853. return result.str();
  854. }
  855. static void ctrl_c_handling() {
  856. #if defined(__unix__) || (defined(__APPLE__) && defined(__MACH__))
  857. struct sigaction sigint_action;
  858. sigint_action.sa_handler = sigint_handler;
  859. sigemptyset(&sigint_action.sa_mask);
  860. sigint_action.sa_flags = 0;
  861. sigaction(SIGINT, &sigint_action, NULL);
  862. #elif defined(_WIN32)
  863. auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
  864. return (ctrl_type == CTRL_C_EVENT) ? (sigint_handler(SIGINT), true) : false;
  865. };
  866. SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
  867. #endif
  868. }
  869. int main(int argc, const char ** argv) {
  870. ctrl_c_handling();
  871. Opt opt;
  872. const int ret = opt.init(argc, argv);
  873. if (ret == 2) {
  874. return 0;
  875. } else if (ret) {
  876. return 1;
  877. }
  878. if (!is_stdin_a_terminal()) {
  879. if (!opt.user.empty()) {
  880. opt.user += "\n\n";
  881. }
  882. opt.user += read_pipe_data();
  883. }
  884. llama_log_set(log_callback, &opt);
  885. LlamaData llama_data;
  886. if (llama_data.init(opt)) {
  887. return 1;
  888. }
  889. if (chat_loop(llama_data, opt.user, opt.use_jinja)) {
  890. return 1;
  891. }
  892. return 0;
  893. }