#if defined(_MSC_VER) #define _SILENCE_CXX17_CODECVT_HEADER_DEPRECATION_WARNING #endif #include "common.h" #include "log.h" // Change JSON_ASSERT from assert() to GGML_ASSERT: #define JSON_ASSERT GGML_ASSERT #include "json.hpp" #include "json-schema-to-grammar.h" #include "llama.h" #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #if defined(__APPLE__) && defined(__MACH__) #include #include #endif #if defined(_WIN32) #define WIN32_LEAN_AND_MEAN #ifndef NOMINMAX # define NOMINMAX #endif #include #include #include #include #else #include #include #include #endif #if defined(LLAMA_USE_CURL) #include #include #include #endif #if defined(_MSC_VER) #pragma warning(disable: 4244 4267) // possible loss of data #endif #if defined(LLAMA_USE_CURL) #ifdef __linux__ #include #elif defined(_WIN32) #define PATH_MAX MAX_PATH #else #include #endif #define LLAMA_CURL_MAX_URL_LENGTH 2084 // Maximum URL Length in Chrome: 2083 #endif // LLAMA_USE_CURL using json = nlohmann::ordered_json; // // CPU utils // int32_t cpu_get_num_physical_cores() { #ifdef __linux__ // enumerate the set of thread siblings, num entries is num cores std::unordered_set siblings; for (uint32_t cpu=0; cpu < UINT32_MAX; ++cpu) { std::ifstream thread_siblings("/sys/devices/system/cpu/cpu" + std::to_string(cpu) + "/topology/thread_siblings"); if (!thread_siblings.is_open()) { break; // no more cpus } std::string line; if (std::getline(thread_siblings, line)) { siblings.insert(line); } } if (!siblings.empty()) { return static_cast(siblings.size()); } #elif defined(__APPLE__) && defined(__MACH__) int32_t num_physical_cores; size_t len = sizeof(num_physical_cores); int result = sysctlbyname("hw.perflevel0.physicalcpu", &num_physical_cores, &len, NULL, 0); if (result == 0) { return num_physical_cores; } result = sysctlbyname("hw.physicalcpu", &num_physical_cores, &len, NULL, 0); if (result == 0) { return num_physical_cores; } #elif defined(_WIN32) && (_WIN32_WINNT >= 0x0601) && !defined(__MINGW64__) // windows 7 and later // TODO: windows + arm64 + mingw64 unsigned int n_threads_win = std::thread::hardware_concurrency(); unsigned int default_threads = n_threads_win > 0 ? (n_threads_win <= 4 ? n_threads_win : n_threads_win / 2) : 4; DWORD buffer_size = 0; if (!GetLogicalProcessorInformationEx(RelationProcessorCore, nullptr, &buffer_size)) { if (GetLastError() != ERROR_INSUFFICIENT_BUFFER) { return default_threads; } } std::vector buffer(buffer_size); if (!GetLogicalProcessorInformationEx(RelationProcessorCore, reinterpret_cast(buffer.data()), &buffer_size)) { return default_threads; } int32_t num_physical_cores = 0; PSYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX info = reinterpret_cast(buffer.data()); while (buffer_size > 0) { if (info->Relationship == RelationProcessorCore) { num_physical_cores += info->Processor.GroupCount; } buffer_size -= info->Size; info = reinterpret_cast(reinterpret_cast(info) + info->Size); } return num_physical_cores > 0 ? num_physical_cores : default_threads; #endif unsigned int n_threads = std::thread::hardware_concurrency(); return n_threads > 0 ? (n_threads <= 4 ? n_threads : n_threads / 2) : 4; } #if defined(__x86_64__) && defined(__linux__) && !defined(__ANDROID__) #include static void cpuid(unsigned leaf, unsigned subleaf, unsigned *eax, unsigned *ebx, unsigned *ecx, unsigned *edx) { __asm__("movq\t%%rbx,%%rsi\n\t" "cpuid\n\t" "xchgq\t%%rbx,%%rsi" : "=a"(*eax), "=S"(*ebx), "=c"(*ecx), "=d"(*edx) : "0"(leaf), "2"(subleaf)); } static int pin_cpu(int cpu) { cpu_set_t mask; CPU_ZERO(&mask); CPU_SET(cpu, &mask); return pthread_setaffinity_np(pthread_self(), sizeof(mask), &mask); } static bool is_hybrid_cpu(void) { unsigned eax, ebx, ecx, edx; cpuid(7, 0, &eax, &ebx, &ecx, &edx); return !!(edx & (1u << 15)); } static bool is_running_on_efficiency_core(void) { unsigned eax, ebx, ecx, edx; cpuid(0x1a, 0, &eax, &ebx, &ecx, &edx); int intel_atom = 0x20; int core_type = (eax & 0xff000000u) >> 24; return core_type == intel_atom; } static int cpu_count_math_cpus(int n_cpu) { int result = 0; for (int cpu = 0; cpu < n_cpu; ++cpu) { if (pin_cpu(cpu)) { return -1; } if (is_running_on_efficiency_core()) { continue; // efficiency cores harm lockstep threading } ++cpu; // hyperthreading isn't useful for linear algebra ++result; } return result; } #endif // __x86_64__ && __linux__ /** * Returns number of CPUs on system that are useful for math. */ int32_t cpu_get_num_math() { #if defined(__x86_64__) && defined(__linux__) && !defined(__ANDROID__) int n_cpu = sysconf(_SC_NPROCESSORS_ONLN); if (n_cpu < 1) { return cpu_get_num_physical_cores(); } if (is_hybrid_cpu()) { cpu_set_t affinity; if (!pthread_getaffinity_np(pthread_self(), sizeof(affinity), &affinity)) { int result = cpu_count_math_cpus(n_cpu); pthread_setaffinity_np(pthread_self(), sizeof(affinity), &affinity); if (result > 0) { return result; } } } #endif return cpu_get_num_physical_cores(); } // Helper for setting process priority #if defined(_WIN32) bool set_process_priority(enum ggml_sched_priority prio) { if (prio == GGML_SCHED_PRIO_NORMAL) { return true; } DWORD p = NORMAL_PRIORITY_CLASS; switch (prio) { case GGML_SCHED_PRIO_NORMAL: p = NORMAL_PRIORITY_CLASS; break; case GGML_SCHED_PRIO_MEDIUM: p = ABOVE_NORMAL_PRIORITY_CLASS; break; case GGML_SCHED_PRIO_HIGH: p = HIGH_PRIORITY_CLASS; break; case GGML_SCHED_PRIO_REALTIME: p = REALTIME_PRIORITY_CLASS; break; } if (!SetPriorityClass(GetCurrentProcess(), p)) { LOG_WRN("failed to set process priority class %d : (%d)\n", prio, (int) GetLastError()); return false; } return true; } #else // MacOS and POSIX #include #include bool set_process_priority(enum ggml_sched_priority prio) { if (prio == GGML_SCHED_PRIO_NORMAL) { return true; } int p = 0; switch (prio) { case GGML_SCHED_PRIO_NORMAL: p = 0; break; case GGML_SCHED_PRIO_MEDIUM: p = -5; break; case GGML_SCHED_PRIO_HIGH: p = -10; break; case GGML_SCHED_PRIO_REALTIME: p = -20; break; } if (!setpriority(PRIO_PROCESS, 0, p)) { LOG_WRN("failed to set process priority %d : %s (%d)\n", prio, strerror(errno), errno); return false; } return true; } #endif // // CLI argument parsing // void postprocess_cpu_params(cpu_params& cpuparams, const cpu_params* role_model) { int32_t n_set = 0; if (cpuparams.n_threads < 0) { // Assuming everything about cpuparams is invalid if (role_model != nullptr) { cpuparams = *role_model; } else { cpuparams.n_threads = cpu_get_num_math(); } } for (int32_t i = 0; i < GGML_MAX_N_THREADS; i++) { if (cpuparams.cpumask[i]) { n_set++; } } if (n_set && n_set < cpuparams.n_threads) { // Not enough set bits, may experience performance issues. LOG_WRN("Not enough set bits in CPU mask (%d) to satisfy requested thread count: %d\n", n_set, cpuparams.n_threads); } } bool parse_cpu_range(const std::string & range, bool (&boolmask)[GGML_MAX_N_THREADS]) { size_t dash_loc = range.find('-'); if (dash_loc == std::string::npos) { LOG_ERR("Format of CPU range is invalid! Expected []-[].\n"); return false; } size_t start_i; size_t end_i; if (dash_loc == 0) { start_i = 0; } else { start_i = std::stoull(range.substr(0, dash_loc)); if (start_i >= GGML_MAX_N_THREADS) { LOG_ERR("Start index out of bounds!\n"); return false; } } if (dash_loc == range.length() - 1) { end_i = GGML_MAX_N_THREADS - 1; } else { end_i = std::stoull(range.substr(dash_loc + 1)); if (end_i >= GGML_MAX_N_THREADS) { LOG_ERR("End index out of bounds!\n"); return false; } } for (size_t i = start_i; i <= end_i; i++) { boolmask[i] = true; } return true; } bool parse_cpu_mask(const std::string & mask, bool (&boolmask)[GGML_MAX_N_THREADS]) { // Discard potential 0x prefix size_t start_i = 0; if (mask.length() >= 2 && mask.substr(0, 2) == "0x") { start_i = 2; } size_t num_digits = mask.length() - start_i; if (num_digits > 128) num_digits = 128; size_t end_i = num_digits + start_i; for (size_t i = start_i, n = (num_digits*4 - 1); i < end_i; i++, n-=4) { char c = mask.at(i); int8_t id = c; if ((c >= '0' && c <= '9')) { id -= '0'; } else if (c >= 'a' && c <= 'f') { id -= 'a' - 10; } else if (c >= 'A' && c <= 'F') { id -= 'A' - 10; } else { LOG_ERR("Invalid hex character '%c' at position %d\n", c, int32_t(i)); return false; } boolmask[ n ] = boolmask[ n ] || ((id & 8) != 0); boolmask[n - 1] = boolmask[n - 1] || ((id & 4) != 0); boolmask[n - 2] = boolmask[n - 2] || ((id & 2) != 0); boolmask[n - 3] = boolmask[n - 3] || ((id & 1) != 0); } return true; } void common_init() { llama_log_set([](ggml_log_level level, const char * text, void * /*user_data*/) { if (LOG_DEFAULT_LLAMA <= common_log_verbosity_thold) { common_log_add(common_log_main(), level, "%s", text); } }, NULL); #ifdef NDEBUG const char * build_type = ""; #else const char * build_type = " (debug)"; #endif LOG_INF("build: %d (%s) with %s for %s%s\n", LLAMA_BUILD_NUMBER, LLAMA_COMMIT, LLAMA_COMPILER, LLAMA_BUILD_TARGET, build_type); } std::string common_params_get_system_info(const common_params & params) { std::ostringstream os; os << "system_info: n_threads = " << params.cpuparams.n_threads; if (params.cpuparams_batch.n_threads != -1) { os << " (n_threads_batch = " << params.cpuparams_batch.n_threads << ")"; } #if defined(_WIN32) && (_WIN32_WINNT >= 0x0601) && !defined(__MINGW64__) // windows 7 and later // TODO: windows + arm64 + mingw64 DWORD logicalProcessorCount = GetActiveProcessorCount(ALL_PROCESSOR_GROUPS); os << " / " << logicalProcessorCount << " | " << llama_print_system_info(); #else os << " / " << std::thread::hardware_concurrency() << " | " << llama_print_system_info(); #endif return os.str(); } // // String utils // std::string string_format(const char * fmt, ...) { va_list ap; va_list ap2; va_start(ap, fmt); va_copy(ap2, ap); int size = vsnprintf(NULL, 0, fmt, ap); GGML_ASSERT(size >= 0 && size < INT_MAX); // NOLINT std::vector buf(size + 1); int size2 = vsnprintf(buf.data(), size + 1, fmt, ap2); GGML_ASSERT(size2 == size); va_end(ap2); va_end(ap); return std::string(buf.data(), size); } std::string string_strip(const std::string & str) { size_t start = 0; size_t end = str.size(); while (start < end && std::isspace(str[start])) { start++; } while (end > start && std::isspace(str[end - 1])) { end--; } return str.substr(start, end - start); } std::string string_get_sortable_timestamp() { using clock = std::chrono::system_clock; const clock::time_point current_time = clock::now(); const time_t as_time_t = clock::to_time_t(current_time); char timestamp_no_ns[100]; std::strftime(timestamp_no_ns, 100, "%Y_%m_%d-%H_%M_%S", std::localtime(&as_time_t)); const int64_t ns = std::chrono::duration_cast( current_time.time_since_epoch() % 1000000000).count(); char timestamp_ns[11]; snprintf(timestamp_ns, 11, "%09" PRId64, ns); return std::string(timestamp_no_ns) + "." + std::string(timestamp_ns); } void string_replace_all(std::string & s, const std::string & search, const std::string & replace) { if (search.empty()) { return; } std::string builder; builder.reserve(s.length()); size_t pos = 0; size_t last_pos = 0; while ((pos = s.find(search, last_pos)) != std::string::npos) { builder.append(s, last_pos, pos - last_pos); builder.append(replace); last_pos = pos + search.length(); } builder.append(s, last_pos, std::string::npos); s = std::move(builder); } std::string string_from(bool value) { return value ? "true" : "false"; } std::string string_from(const std::vector & values) { std::stringstream buf; buf << "[ "; bool first = true; for (auto e : values) { if (first) { first = false; } else { buf << ", "; } buf << std::to_string(e); } buf << " ]"; return buf.str(); } std::string string_from(const struct llama_context * ctx, const std::vector & tokens) { std::stringstream buf; buf << "[ "; bool first = true; for (const auto & token : tokens) { if (!first) { buf << ", "; } else { first = false; } auto detokenized = common_token_to_piece(ctx, token); detokenized.erase( std::remove_if( detokenized.begin(), detokenized.end(), [](const unsigned char c) { return !std::isprint(c); }), detokenized.end()); buf << "'" << detokenized << "'" << ":" << std::to_string(token); } buf << " ]"; return buf.str(); } std::string string_from(const struct llama_context * ctx, const struct llama_batch & batch) { std::stringstream buf; buf << "[ "; bool first = true; for (int i = 0; i < batch.n_tokens; ++i) { if (!first) { buf << ", "; } else { first = false; } auto detokenized = common_token_to_piece(ctx, batch.token[i]); detokenized.erase( std::remove_if( detokenized.begin(), detokenized.end(), [](const unsigned char c) { return !std::isprint(c); }), detokenized.end()); buf << "\n" << std::to_string(i) << ":token '" << detokenized << "'" << ":pos " << std::to_string(batch.pos[i]) << ":n_seq_id " << std::to_string(batch.n_seq_id[i]) << ":seq_id " << std::to_string(batch.seq_id[i][0]) << ":logits " << std::to_string(batch.logits[i]); } buf << " ]"; return buf.str(); } void string_process_escapes(std::string & input) { std::size_t input_len = input.length(); std::size_t output_idx = 0; for (std::size_t input_idx = 0; input_idx < input_len; ++input_idx) { if (input[input_idx] == '\\' && input_idx + 1 < input_len) { switch (input[++input_idx]) { case 'n': input[output_idx++] = '\n'; break; case 'r': input[output_idx++] = '\r'; break; case 't': input[output_idx++] = '\t'; break; case '\'': input[output_idx++] = '\''; break; case '\"': input[output_idx++] = '\"'; break; case '\\': input[output_idx++] = '\\'; break; case 'x': // Handle \x12, etc if (input_idx + 2 < input_len) { const char x[3] = { input[input_idx + 1], input[input_idx + 2], 0 }; char *err_p = nullptr; const long val = std::strtol(x, &err_p, 16); if (err_p == x + 2) { input_idx += 2; input[output_idx++] = char(val); break; } } // fall through default: input[output_idx++] = '\\'; input[output_idx++] = input[input_idx]; break; } } else { input[output_idx++] = input[input_idx]; } } input.resize(output_idx); } bool string_parse_kv_override(const char * data, std::vector & overrides) { const char * sep = strchr(data, '='); if (sep == nullptr || sep - data >= 128) { LOG_ERR("%s: malformed KV override '%s'\n", __func__, data); return false; } llama_model_kv_override kvo; std::strncpy(kvo.key, data, sep - data); kvo.key[sep - data] = 0; sep++; if (strncmp(sep, "int:", 4) == 0) { sep += 4; kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; kvo.val_i64 = std::atol(sep); } else if (strncmp(sep, "float:", 6) == 0) { sep += 6; kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT; kvo.val_f64 = std::atof(sep); } else if (strncmp(sep, "bool:", 5) == 0) { sep += 5; kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL; if (std::strcmp(sep, "true") == 0) { kvo.val_bool = true; } else if (std::strcmp(sep, "false") == 0) { kvo.val_bool = false; } else { LOG_ERR("%s: invalid boolean value for KV override '%s'\n", __func__, data); return false; } } else if (strncmp(sep, "str:", 4) == 0) { sep += 4; kvo.tag = LLAMA_KV_OVERRIDE_TYPE_STR; if (strlen(sep) > 127) { LOG_ERR("%s: malformed KV override '%s', value cannot exceed 127 chars\n", __func__, data); return false; } strncpy(kvo.val_str, sep, 127); kvo.val_str[127] = '\0'; } else { LOG_ERR("%s: invalid type for KV override '%s'\n", __func__, data); return false; } overrides.emplace_back(std::move(kvo)); return true; } // // Filesystem utils // // Validate if a filename is safe to use // To validate a full path, split the path by the OS-specific path separator, and validate each part with this function bool fs_validate_filename(const std::string & filename) { if (!filename.length()) { // Empty filename invalid return false; } if (filename.length() > 255) { // Limit at common largest possible filename on Linux filesystems // to avoid unnecessary further validation // (On systems with smaller limits it will be caught by the OS) return false; } std::u32string filename_utf32; try { std::wstring_convert, char32_t> converter; filename_utf32 = converter.from_bytes(filename); // If the reverse conversion mismatches, it means overlong UTF-8 sequences were used, // or invalid encodings were encountered. Reject such attempts std::string filename_reencoded = converter.to_bytes(filename_utf32); if (filename_reencoded != filename) { return false; } } catch (const std::exception &) { return false; } // Check for forbidden codepoints: // - Control characters // - Unicode equivalents of illegal characters // - UTF-16 surrogate pairs // - UTF-8 replacement character // - Byte order mark (BOM) // - Illegal characters: / \ : * ? " < > | for (char32_t c : filename_utf32) { if (c <= 0x1F // Control characters (C0) || c == 0x7F // Control characters (DEL) || (c >= 0x80 && c <= 0x9F) // Control characters (C1) || c == 0xFF0E // Fullwidth Full Stop (period equivalent) || c == 0x2215 // Division Slash (forward slash equivalent) || c == 0x2216 // Set Minus (backslash equivalent) || (c >= 0xD800 && c <= 0xDFFF) // UTF-16 surrogate pairs || c == 0xFFFD // Replacement Character (UTF-8) || c == 0xFEFF // Byte Order Mark (BOM) || c == '/' || c == '\\' || c == ':' || c == '*' // Illegal characters || c == '?' || c == '"' || c == '<' || c == '>' || c == '|') { return false; } } // Reject any leading or trailing ' ', or any trailing '.', these are stripped on Windows and will cause a different filename // Unicode and other whitespace is not affected, only 0x20 space if (filename.front() == ' ' || filename.back() == ' ' || filename.back() == '.') { return false; } // Reject any ".." (currently stricter than necessary, it should be fine to just check for == ".." instead) if (filename.find("..") != std::string::npos) { return false; } // Reject "." if (filename == ".") { return false; } return true; } // returns true if successful, false otherwise bool fs_create_directory_with_parents(const std::string & path) { #ifdef _WIN32 std::wstring_convert> converter; std::wstring wpath = converter.from_bytes(path); // if the path already exists, check whether it's a directory const DWORD attributes = GetFileAttributesW(wpath.c_str()); if ((attributes != INVALID_FILE_ATTRIBUTES) && (attributes & FILE_ATTRIBUTE_DIRECTORY)) { return true; } size_t pos_slash = 0; // process path from front to back, procedurally creating directories while ((pos_slash = path.find('\\', pos_slash)) != std::string::npos) { const std::wstring subpath = wpath.substr(0, pos_slash); const wchar_t * test = subpath.c_str(); const bool success = CreateDirectoryW(test, NULL); if (!success) { const DWORD error = GetLastError(); // if the path already exists, ensure that it's a directory if (error == ERROR_ALREADY_EXISTS) { const DWORD attributes = GetFileAttributesW(subpath.c_str()); if (attributes == INVALID_FILE_ATTRIBUTES || !(attributes & FILE_ATTRIBUTE_DIRECTORY)) { return false; } } else { return false; } } pos_slash += 1; } return true; #else // if the path already exists, check whether it's a directory struct stat info; if (stat(path.c_str(), &info) == 0) { return S_ISDIR(info.st_mode); } size_t pos_slash = 1; // skip leading slashes for directory creation // process path from front to back, procedurally creating directories while ((pos_slash = path.find('/', pos_slash)) != std::string::npos) { const std::string subpath = path.substr(0, pos_slash); struct stat info; // if the path already exists, ensure that it's a directory if (stat(subpath.c_str(), &info) == 0) { if (!S_ISDIR(info.st_mode)) { return false; } } else { // create parent directories const int ret = mkdir(subpath.c_str(), 0755); if (ret != 0) { return false; } } pos_slash += 1; } return true; #endif // _WIN32 } std::string fs_get_cache_directory() { std::string cache_directory = ""; auto ensure_trailing_slash = [](std::string p) { // Make sure to add trailing slash if (p.back() != DIRECTORY_SEPARATOR) { p += DIRECTORY_SEPARATOR; } return p; }; if (getenv("LLAMA_CACHE")) { cache_directory = std::getenv("LLAMA_CACHE"); } else { #ifdef __linux__ if (std::getenv("XDG_CACHE_HOME")) { cache_directory = std::getenv("XDG_CACHE_HOME"); } else { cache_directory = std::getenv("HOME") + std::string("/.cache/"); } #elif defined(__APPLE__) cache_directory = std::getenv("HOME") + std::string("/Library/Caches/"); #elif defined(_WIN32) cache_directory = std::getenv("LOCALAPPDATA"); #endif // __linux__ cache_directory = ensure_trailing_slash(cache_directory); cache_directory += "llama.cpp"; } return ensure_trailing_slash(cache_directory); } std::string fs_get_cache_file(const std::string & filename) { GGML_ASSERT(filename.find(DIRECTORY_SEPARATOR) == std::string::npos); std::string cache_directory = fs_get_cache_directory(); const bool success = fs_create_directory_with_parents(cache_directory); if (!success) { throw std::runtime_error("failed to create cache directory: " + cache_directory); } return cache_directory + filename; } // // Model utils // struct common_init_result common_init_from_params(common_params & params) { common_init_result iparams; auto mparams = common_model_params_to_llama(params); llama_model * model = nullptr; if (!params.hf_repo.empty() && !params.hf_file.empty()) { model = common_load_model_from_hf(params.hf_repo.c_str(), params.hf_file.c_str(), params.model.c_str(), params.hf_token.c_str(), mparams); } else if (!params.model_url.empty()) { model = common_load_model_from_url(params.model_url.c_str(), params.model.c_str(), params.hf_token.c_str(), mparams); } else { model = llama_load_model_from_file(params.model.c_str(), mparams); } if (model == NULL) { LOG_ERR("%s: failed to load model '%s'\n", __func__, params.model.c_str()); return iparams; } if (params.reranking) { bool ok = true; if (llama_token_bos(model) == LLAMA_TOKEN_NULL) { LOG_WRN("%s: warning: model does not have a BOS token, reranking will not work\n", __func__); ok = false; } if (llama_token_eos(model) == LLAMA_TOKEN_NULL) { LOG_WRN("%s: warning: model does not have an EOS token, reranking will not work\n", __func__); ok = false; } if (llama_token_sep(model) == LLAMA_TOKEN_NULL) { LOG_WRN("%s: warning: model does not have a SEP token, reranking will not work\n", __func__); ok = false; } if (!ok) { llama_free_model(model); return iparams; } } auto cparams = common_context_params_to_llama(params); llama_context * lctx = llama_new_context_with_model(model, cparams); if (lctx == NULL) { LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.c_str()); llama_free_model(model); return iparams; } if (!params.control_vectors.empty()) { if (params.control_vector_layer_start <= 0) params.control_vector_layer_start = 1; if (params.control_vector_layer_end <= 0) params.control_vector_layer_end = llama_n_layer(model); const auto cvec = common_control_vector_load(params.control_vectors); if (cvec.n_embd == -1) { llama_free(lctx); llama_free_model(model); return iparams; } int err = llama_control_vector_apply(lctx, cvec.data.data(), cvec.data.size(), cvec.n_embd, params.control_vector_layer_start, params.control_vector_layer_end); if (err) { llama_free(lctx); llama_free_model(model); return iparams; } } // load and optionally apply lora adapters for (auto & la : params.lora_adapters) { common_lora_adapter_container loaded_la; loaded_la.path = la.path; loaded_la.scale = la.scale; loaded_la.adapter = llama_lora_adapter_init(model, la.path.c_str()); if (loaded_la.adapter == nullptr) { LOG_ERR("%s: failed to apply lora adapter '%s'\n", __func__, la.path.c_str()); llama_free(lctx); llama_free_model(model); return iparams; } iparams.lora_adapters.push_back(loaded_la); // copy to list of loaded adapters } if (!params.lora_init_without_apply) { common_lora_adapters_apply(lctx, iparams.lora_adapters); } if (params.sparams.ignore_eos && llama_token_eos(model) == LLAMA_TOKEN_NULL) { LOG_WRN("%s: warning: model does not have an EOS token, ignoring --ignore-eos\n", __func__); params.sparams.ignore_eos = false; } if (params.warmup) { LOG_WRN("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__); std::vector tmp; llama_token bos = llama_token_bos(model); llama_token eos = llama_token_eos(model); // some models (e.g. T5) don't have a BOS token if (bos != LLAMA_TOKEN_NULL) { tmp.push_back(bos); } if (eos != LLAMA_TOKEN_NULL) { tmp.push_back(eos); } if (tmp.empty()) { tmp.push_back(0); } if (llama_model_has_encoder(model)) { llama_encode(lctx, llama_batch_get_one(tmp.data(), tmp.size())); llama_token decoder_start_token_id = llama_model_decoder_start_token(model); if (decoder_start_token_id == -1) { decoder_start_token_id = bos; } tmp.clear(); tmp.push_back(decoder_start_token_id); } if (llama_model_has_decoder(model)) { llama_decode(lctx, llama_batch_get_one(tmp.data(), std::min(tmp.size(), (size_t) params.n_batch))); } llama_kv_cache_clear(lctx); llama_synchronize(lctx); llama_perf_context_reset(lctx); } iparams.model = model; iparams.context = lctx; return iparams; } void common_lora_adapters_apply(struct llama_context * ctx, std::vector & lora_adapters) { llama_lora_adapter_clear(ctx); for (auto & la : lora_adapters) { if (la.scale != 0.0f) { llama_lora_adapter_set(ctx, la.adapter, la.scale); } } } struct llama_model_params common_model_params_to_llama(const common_params & params) { auto mparams = llama_model_default_params(); if (params.n_gpu_layers != -1) { mparams.n_gpu_layers = params.n_gpu_layers; } mparams.rpc_servers = params.rpc_servers.c_str(); mparams.main_gpu = params.main_gpu; mparams.split_mode = params.split_mode; mparams.tensor_split = params.tensor_split; mparams.use_mmap = params.use_mmap; mparams.use_mlock = params.use_mlock; mparams.check_tensors = params.check_tensors; if (params.kv_overrides.empty()) { mparams.kv_overrides = NULL; } else { GGML_ASSERT(params.kv_overrides.back().key[0] == 0 && "KV overrides not terminated with empty key"); mparams.kv_overrides = params.kv_overrides.data(); } return mparams; } static ggml_type kv_cache_type_from_str(const std::string & s) { if (s == "f32") { return GGML_TYPE_F32; } if (s == "f16") { return GGML_TYPE_F16; } if (s == "bf16") { return GGML_TYPE_BF16; } if (s == "q8_0") { return GGML_TYPE_Q8_0; } if (s == "q4_0") { return GGML_TYPE_Q4_0; } if (s == "q4_1") { return GGML_TYPE_Q4_1; } if (s == "iq4_nl") { return GGML_TYPE_IQ4_NL; } if (s == "q5_0") { return GGML_TYPE_Q5_0; } if (s == "q5_1") { return GGML_TYPE_Q5_1; } throw std::runtime_error("Unsupported cache type: " + s); } struct llama_context_params common_context_params_to_llama(const common_params & params) { auto cparams = llama_context_default_params(); cparams.n_ctx = params.n_ctx; cparams.n_seq_max = params.n_parallel; cparams.n_batch = params.n_batch; cparams.n_ubatch = params.n_ubatch; cparams.n_threads = params.cpuparams.n_threads; cparams.n_threads_batch = params.cpuparams_batch.n_threads == -1 ? params.cpuparams.n_threads : params.cpuparams_batch.n_threads; cparams.logits_all = params.logits_all; cparams.embeddings = params.embedding; cparams.rope_scaling_type = params.rope_scaling_type; cparams.rope_freq_base = params.rope_freq_base; cparams.rope_freq_scale = params.rope_freq_scale; cparams.yarn_ext_factor = params.yarn_ext_factor; cparams.yarn_attn_factor = params.yarn_attn_factor; cparams.yarn_beta_fast = params.yarn_beta_fast; cparams.yarn_beta_slow = params.yarn_beta_slow; cparams.yarn_orig_ctx = params.yarn_orig_ctx; cparams.pooling_type = params.pooling_type; cparams.attention_type = params.attention_type; cparams.defrag_thold = params.defrag_thold; cparams.cb_eval = params.cb_eval; cparams.cb_eval_user_data = params.cb_eval_user_data; cparams.offload_kqv = !params.no_kv_offload; cparams.flash_attn = params.flash_attn; cparams.no_perf = params.no_perf; if (params.reranking) { cparams.embeddings = true; cparams.pooling_type = LLAMA_POOLING_TYPE_RANK; } cparams.type_k = kv_cache_type_from_str(params.cache_type_k); cparams.type_v = kv_cache_type_from_str(params.cache_type_v); return cparams; } struct ggml_threadpool_params ggml_threadpool_params_from_cpu_params(const cpu_params & params) { struct ggml_threadpool_params tpp; ggml_threadpool_params_init(&tpp, params.n_threads); // setup the defaults if (params.mask_valid) { std::memcpy(&tpp.cpumask, ¶ms.cpumask, GGML_MAX_N_THREADS); } tpp.prio = params.priority; tpp.poll = params.poll; tpp.strict_cpu = params.strict_cpu; return tpp; } #ifdef LLAMA_USE_CURL #define CURL_MAX_RETRY 3 #define CURL_RETRY_DELAY_SECONDS 2 static bool starts_with(const std::string & str, const std::string & prefix) { // While we wait for C++20's std::string::starts_with... return str.rfind(prefix, 0) == 0; } static bool curl_perform_with_retry(const std::string& url, CURL* curl, int max_attempts, int retry_delay_seconds) { int remaining_attempts = max_attempts; while (remaining_attempts > 0) { LOG_INF("%s: Trying to download from %s (attempt %d of %d)...\n", __func__ , url.c_str(), max_attempts - remaining_attempts + 1, max_attempts); CURLcode res = curl_easy_perform(curl); if (res == CURLE_OK) { return true; } int exponential_backoff_delay = std::pow(retry_delay_seconds, max_attempts - remaining_attempts) * 1000; LOG_WRN("%s: curl_easy_perform() failed: %s, retrying after %d milliseconds...\n", __func__, curl_easy_strerror(res), exponential_backoff_delay); remaining_attempts--; std::this_thread::sleep_for(std::chrono::milliseconds(exponential_backoff_delay)); } LOG_ERR("%s: curl_easy_perform() failed after %d attempts\n", __func__, max_attempts); return false; } static bool common_download_file(const std::string & url, const std::string & path, const std::string & hf_token) { // Initialize libcurl std::unique_ptr curl(curl_easy_init(), &curl_easy_cleanup); if (!curl) { LOG_ERR("%s: error initializing libcurl\n", __func__); return false; } bool force_download = false; // Set the URL, allow to follow http redirection curl_easy_setopt(curl.get(), CURLOPT_URL, url.c_str()); curl_easy_setopt(curl.get(), CURLOPT_FOLLOWLOCATION, 1L); // Check if hf-token or bearer-token was specified if (!hf_token.empty()) { std::string auth_header = "Authorization: Bearer "; auth_header += hf_token.c_str(); struct curl_slist *http_headers = NULL; http_headers = curl_slist_append(http_headers, auth_header.c_str()); curl_easy_setopt(curl.get(), CURLOPT_HTTPHEADER, http_headers); } #if defined(_WIN32) // CURLSSLOPT_NATIVE_CA tells libcurl to use standard certificate store of // operating system. Currently implemented under MS-Windows. curl_easy_setopt(curl.get(), CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA); #endif // Check if the file already exists locally struct stat model_file_info; auto file_exists = (stat(path.c_str(), &model_file_info) == 0); // If the file exists, check its JSON metadata companion file. std::string metadata_path = path + ".json"; nlohmann::json metadata; std::string etag; std::string last_modified; if (file_exists) { // Try and read the JSON metadata file (note: stream autoclosed upon exiting this block). std::ifstream metadata_in(metadata_path); if (metadata_in.good()) { try { metadata_in >> metadata; LOG_INF("%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), metadata.dump().c_str()); if (metadata.contains("url") && metadata.at("url").is_string()) { auto previous_url = metadata.at("url").get(); if (previous_url != url) { LOG_ERR("%s: Model URL mismatch: %s != %s\n", __func__, url.c_str(), previous_url.c_str()); return false; } } if (metadata.contains("etag") && metadata.at("etag").is_string()) { etag = metadata.at("etag"); } if (metadata.contains("lastModified") && metadata.at("lastModified").is_string()) { last_modified = metadata.at("lastModified"); } } catch (const nlohmann::json::exception & e) { LOG_ERR("%s: error reading metadata file %s: %s\n", __func__, metadata_path.c_str(), e.what()); return false; } } } else { LOG_INF("%s: no previous model file found %s\n", __func__, path.c_str()); } // Send a HEAD request to retrieve the etag and last-modified headers struct common_load_model_from_url_headers { std::string etag; std::string last_modified; }; common_load_model_from_url_headers headers; { typedef size_t(*CURLOPT_HEADERFUNCTION_PTR)(char *, size_t, size_t, void *); auto header_callback = [](char * buffer, size_t /*size*/, size_t n_items, void * userdata) -> size_t { common_load_model_from_url_headers *headers = (common_load_model_from_url_headers *) userdata; static std::regex header_regex("([^:]+): (.*)\r\n"); static std::regex etag_regex("ETag", std::regex_constants::icase); static std::regex last_modified_regex("Last-Modified", std::regex_constants::icase); std::string header(buffer, n_items); std::smatch match; if (std::regex_match(header, match, header_regex)) { const std::string & key = match[1]; const std::string & value = match[2]; if (std::regex_match(key, match, etag_regex)) { headers->etag = value; } else if (std::regex_match(key, match, last_modified_regex)) { headers->last_modified = value; } } return n_items; }; curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 1L); // will trigger the HEAD verb curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 1L); // hide head request progress curl_easy_setopt(curl.get(), CURLOPT_HEADERFUNCTION, static_cast(header_callback)); curl_easy_setopt(curl.get(), CURLOPT_HEADERDATA, &headers); bool was_perform_successful = curl_perform_with_retry(url, curl.get(), CURL_MAX_RETRY, CURL_RETRY_DELAY_SECONDS); if (!was_perform_successful) { return false; } long http_code = 0; curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &http_code); if (http_code != 200) { // HEAD not supported, we don't know if the file has changed // force trigger downloading force_download = true; LOG_ERR("%s: HEAD invalid http status code received: %ld\n", __func__, http_code); } } bool should_download = !file_exists || force_download; if (!should_download) { if (!etag.empty() && etag != headers.etag) { LOG_WRN("%s: ETag header is different (%s != %s): triggering a new download\n", __func__, etag.c_str(), headers.etag.c_str()); should_download = true; } else if (!last_modified.empty() && last_modified != headers.last_modified) { LOG_WRN("%s: Last-Modified header is different (%s != %s): triggering a new download\n", __func__, last_modified.c_str(), headers.last_modified.c_str()); should_download = true; } } if (should_download) { std::string path_temporary = path + ".downloadInProgress"; if (file_exists) { LOG_WRN("%s: deleting previous downloaded file: %s\n", __func__, path.c_str()); if (remove(path.c_str()) != 0) { LOG_ERR("%s: unable to delete file: %s\n", __func__, path.c_str()); return false; } } // Set the output file struct FILE_deleter { void operator()(FILE * f) const { fclose(f); } }; std::unique_ptr outfile(fopen(path_temporary.c_str(), "wb")); if (!outfile) { LOG_ERR("%s: error opening local file for writing: %s\n", __func__, path.c_str()); return false; } typedef size_t(*CURLOPT_WRITEFUNCTION_PTR)(void * data, size_t size, size_t nmemb, void * fd); auto write_callback = [](void * data, size_t size, size_t nmemb, void * fd) -> size_t { return fwrite(data, size, nmemb, (FILE *)fd); }; curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 0L); curl_easy_setopt(curl.get(), CURLOPT_WRITEFUNCTION, static_cast(write_callback)); curl_easy_setopt(curl.get(), CURLOPT_WRITEDATA, outfile.get()); // display download progress curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 0L); // helper function to hide password in URL auto llama_download_hide_password_in_url = [](const std::string & url) -> std::string { std::size_t protocol_pos = url.find("://"); if (protocol_pos == std::string::npos) { return url; // Malformed URL } std::size_t at_pos = url.find('@', protocol_pos + 3); if (at_pos == std::string::npos) { return url; // No password in URL } return url.substr(0, protocol_pos + 3) + "********" + url.substr(at_pos); }; // start the download LOG_INF("%s: trying to download model from %s to %s (server_etag:%s, server_last_modified:%s)...\n", __func__, llama_download_hide_password_in_url(url).c_str(), path.c_str(), headers.etag.c_str(), headers.last_modified.c_str()); bool was_perform_successful = curl_perform_with_retry(url, curl.get(), CURL_MAX_RETRY, CURL_RETRY_DELAY_SECONDS); if (!was_perform_successful) { return false; } long http_code = 0; curl_easy_getinfo (curl.get(), CURLINFO_RESPONSE_CODE, &http_code); if (http_code < 200 || http_code >= 400) { LOG_ERR("%s: invalid http status code received: %ld\n", __func__, http_code); return false; } // Causes file to be closed explicitly here before we rename it. outfile.reset(); // Write the updated JSON metadata file. metadata.update({ {"url", url}, {"etag", headers.etag}, {"lastModified", headers.last_modified} }); std::ofstream(metadata_path) << metadata.dump(4); LOG_INF("%s: file metadata saved: %s\n", __func__, metadata_path.c_str()); if (rename(path_temporary.c_str(), path.c_str()) != 0) { LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str()); return false; } } return true; } struct llama_model * common_load_model_from_url( const char * model_url, const char * path_model, const char * hf_token, const struct llama_model_params & params) { // Basic validation of the model_url if (!model_url || strlen(model_url) == 0) { LOG_ERR("%s: invalid model_url\n", __func__); return NULL; } if (!common_download_file(model_url, path_model, hf_token)) { return NULL; } // check for additional GGUFs split to download int n_split = 0; { struct gguf_init_params gguf_params = { /*.no_alloc = */ true, /*.ctx = */ NULL, }; auto * ctx_gguf = gguf_init_from_file(path_model, gguf_params); if (!ctx_gguf) { LOG_ERR("\n%s: failed to load input GGUF from %s\n", __func__, path_model); return NULL; } auto key_n_split = gguf_find_key(ctx_gguf, LLM_KV_SPLIT_COUNT); if (key_n_split >= 0) { n_split = gguf_get_val_u16(ctx_gguf, key_n_split); } gguf_free(ctx_gguf); } if (n_split > 1) { char split_prefix[PATH_MAX] = {0}; char split_url_prefix[LLAMA_CURL_MAX_URL_LENGTH] = {0}; // Verify the first split file format // and extract split URL and PATH prefixes { if (!llama_split_prefix(split_prefix, sizeof(split_prefix), path_model, 0, n_split)) { LOG_ERR("\n%s: unexpected model file name: %s n_split=%d\n", __func__, path_model, n_split); return NULL; } if (!llama_split_prefix(split_url_prefix, sizeof(split_url_prefix), model_url, 0, n_split)) { LOG_ERR("\n%s: unexpected model url: %s n_split=%d\n", __func__, model_url, n_split); return NULL; } } // Prepare download in parallel std::vector> futures_download; for (int idx = 1; idx < n_split; idx++) { futures_download.push_back(std::async(std::launch::async, [&split_prefix, &split_url_prefix, &n_split, hf_token](int download_idx) -> bool { char split_path[PATH_MAX] = {0}; llama_split_path(split_path, sizeof(split_path), split_prefix, download_idx, n_split); char split_url[LLAMA_CURL_MAX_URL_LENGTH] = {0}; llama_split_path(split_url, sizeof(split_url), split_url_prefix, download_idx, n_split); return common_download_file(split_url, split_path, hf_token); }, idx)); } // Wait for all downloads to complete for (auto & f : futures_download) { if (!f.get()) { return NULL; } } } return llama_load_model_from_file(path_model, params); } struct llama_model * common_load_model_from_hf( const char * repo, const char * model, const char * path_model, const char * hf_token, const struct llama_model_params & params) { // construct hugging face model url: // // --repo ggml-org/models --file tinyllama-1.1b/ggml-model-f16.gguf // https://huggingface.co/ggml-org/models/resolve/main/tinyllama-1.1b/ggml-model-f16.gguf // // --repo TheBloke/Mixtral-8x7B-v0.1-GGUF --file mixtral-8x7b-v0.1.Q4_K_M.gguf // https://huggingface.co/TheBloke/Mixtral-8x7B-v0.1-GGUF/resolve/main/mixtral-8x7b-v0.1.Q4_K_M.gguf // std::string model_url = "https://huggingface.co/"; model_url += repo; model_url += "/resolve/main/"; model_url += model; return common_load_model_from_url(model_url.c_str(), path_model, hf_token, params); } #else struct llama_model * common_load_model_from_url( const char * /*model_url*/, const char * /*path_model*/, const char * /*hf_token*/, const struct llama_model_params & /*params*/) { LOG_WRN("%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__); return nullptr; } struct llama_model * common_load_model_from_hf( const char * /*repo*/, const char * /*model*/, const char * /*path_model*/, const char * /*hf_token*/, const struct llama_model_params & /*params*/) { LOG_WRN("%s: llama.cpp built without libcurl, downloading from Hugging Face not supported.\n", __func__); return nullptr; } #endif // LLAMA_USE_CURL // // Batch utils // void common_batch_clear(struct llama_batch & batch) { batch.n_tokens = 0; } void common_batch_add( struct llama_batch & batch, llama_token id, llama_pos pos, const std::vector & seq_ids, bool logits) { GGML_ASSERT(batch.seq_id[batch.n_tokens] && "llama_batch size exceeded"); batch.token [batch.n_tokens] = id; batch.pos [batch.n_tokens] = pos; batch.n_seq_id[batch.n_tokens] = seq_ids.size(); for (size_t i = 0; i < seq_ids.size(); ++i) { batch.seq_id[batch.n_tokens][i] = seq_ids[i]; } batch.logits [batch.n_tokens] = logits; batch.n_tokens++; } // // Vocab utils // std::vector common_tokenize( const struct llama_context * ctx, const std::string & text, bool add_special, bool parse_special) { return common_tokenize(llama_get_model(ctx), text, add_special, parse_special); } std::vector common_tokenize( const struct llama_model * model, const std::string & text, bool add_special, bool parse_special) { // upper limit for the number of tokens int n_tokens = text.length() + 2 * add_special; std::vector result(n_tokens); n_tokens = llama_tokenize(model, text.data(), text.length(), result.data(), result.size(), add_special, parse_special); if (n_tokens < 0) { result.resize(-n_tokens); int check = llama_tokenize(model, text.data(), text.length(), result.data(), result.size(), add_special, parse_special); GGML_ASSERT(check == -n_tokens); } else { result.resize(n_tokens); } return result; } std::string common_token_to_piece(const struct llama_context * ctx, llama_token token, bool special) { std::string piece; piece.resize(piece.capacity()); // using string internal cache, 15 bytes + '\n' const int n_chars = llama_token_to_piece(llama_get_model(ctx), token, &piece[0], piece.size(), 0, special); if (n_chars < 0) { piece.resize(-n_chars); int check = llama_token_to_piece(llama_get_model(ctx), token, &piece[0], piece.size(), 0, special); GGML_ASSERT(check == -n_chars); } else { piece.resize(n_chars); } return piece; } std::string common_detokenize(llama_context * ctx, const std::vector & tokens, bool special) { std::string text; text.resize(std::max(text.capacity(), tokens.size())); int32_t n_chars = llama_detokenize(llama_get_model(ctx), tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special); if (n_chars < 0) { text.resize(-n_chars); n_chars = llama_detokenize(llama_get_model(ctx), tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special); GGML_ASSERT(n_chars <= (int32_t)text.size()); // whitespace trimming is performed after per-token detokenization } text.resize(n_chars); // NOTE: the original tokenizer decodes bytes after collecting the pieces. return text; } // // Chat template utils // bool common_chat_verify_template(const std::string & tmpl) { llama_chat_message chat[] = {{"user", "test"}}; int res = llama_chat_apply_template(nullptr, tmpl.c_str(), chat, 1, true, nullptr, 0); return res >= 0; } std::string common_chat_apply_template(const struct llama_model * model, const std::string & tmpl, const std::vector & msgs, bool add_ass) { int alloc_size = 0; bool fallback = false; // indicate if we must fallback to default chatml std::vector chat; for (auto & msg : msgs) { chat.push_back({msg.role.c_str(), msg.content.c_str()}); alloc_size += (msg.role.size() + msg.content.size()) * 1.25; } const char * ptr_tmpl = tmpl.empty() ? nullptr : tmpl.c_str(); std::vector buf(alloc_size); // run the first time to get the total output length int32_t res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), add_ass, buf.data(), buf.size()); // error: chat template is not supported if (res < 0) { if (ptr_tmpl != nullptr) { // if the custom "tmpl" is not supported, we throw an error // this is a bit redundant (for good), since we're not sure if user validated the custom template with llama_chat_verify_template() throw std::runtime_error("this custom template is not supported"); } else { // If the built-in template is not supported, we default to chatml res = llama_chat_apply_template(nullptr, "chatml", chat.data(), chat.size(), add_ass, buf.data(), buf.size()); fallback = true; } } // if it turns out that our buffer is too small, we resize it if ((size_t) res > buf.size()) { buf.resize(res); res = llama_chat_apply_template( fallback ? nullptr : model, fallback ? "chatml" : ptr_tmpl, chat.data(), chat.size(), add_ass, buf.data(), buf.size()); } std::string formatted_chat(buf.data(), res); return formatted_chat; } std::string common_chat_format_single(const struct llama_model * model, const std::string & tmpl, const std::vector & past_msg, const common_chat_msg & new_msg, bool add_ass) { std::ostringstream ss; auto fmt_past_msg = past_msg.empty() ? "" : common_chat_apply_template(model, tmpl, past_msg, false); std::vector chat_new(past_msg); // if the past_msg ends with a newline, we must preserve it in the formatted version if (add_ass && !fmt_past_msg.empty() && fmt_past_msg.back() == '\n') { ss << "\n"; }; // format chat with new_msg chat_new.push_back(new_msg); auto fmt_new_msg = common_chat_apply_template(model, tmpl, chat_new, add_ass); // get the diff part ss << fmt_new_msg.substr(fmt_past_msg.size(), fmt_new_msg.size() - fmt_past_msg.size()); return ss.str(); } std::string common_chat_format_example(const struct llama_model * model, const std::string & tmpl) { std::vector msgs = { {"system", "You are a helpful assistant"}, {"user", "Hello"}, {"assistant", "Hi there"}, {"user", "How are you?"}, }; return common_chat_apply_template(model, tmpl, msgs, true); } // // KV cache utils // void common_kv_cache_dump_view(const llama_kv_cache_view & view, int row_size) { static const char slot_chars[] = ".123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+"; printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d", view.n_cells, view.n_seq_max, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx); llama_kv_cache_view_cell * c_curr = view.cells; llama_seq_id * cs_curr = view.cells_sequences; for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) { if (i % row_size == 0) { printf("\n%5d: ", i); } int seq_count = 0; for (int j = 0; j < view.n_seq_max; j++) { if (cs_curr[j] >= 0) { seq_count++; } } putchar(slot_chars[std::min(sizeof(slot_chars) - 2, size_t(seq_count))]); } printf("\n=== Done dumping\n"); } void common_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_size) { static const char slot_chars[] = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"; printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d\n", view.n_cells, view.n_seq_max, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx); std::unordered_map seqs; llama_kv_cache_view_cell * c_curr = view.cells; llama_seq_id * cs_curr = view.cells_sequences; for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) { for (int j = 0; j < view.n_seq_max; j++) { if (cs_curr[j] < 0) { continue; } if (seqs.find(cs_curr[j]) == seqs.end()) { if (seqs.size() + 1 >= sizeof(slot_chars)) { break; } const size_t sz = seqs.size(); seqs[cs_curr[j]] = sz; } } if (seqs.size() + 1 >= sizeof(slot_chars)) { break; } } printf("=== Sequence legend: "); for (const auto & it : seqs) { printf("%zu=%d, ", it.second, it.first); } printf("'+'=other sequence ids"); c_curr = view.cells; cs_curr = view.cells_sequences; for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) { if (i % row_size == 0) { printf("\n%5d: ", i); } for (int j = 0; j < view.n_seq_max; j++) { if (cs_curr[j] >= 0) { const auto & it = seqs.find(cs_curr[j]); putchar(it != seqs.end() ? int(slot_chars[it->second]) : '+'); } else { putchar('.'); } } putchar(' '); } printf("\n=== Done dumping\n"); } // // Embedding utils // void common_embd_normalize(const float * inp, float * out, int n, int embd_norm) { double sum = 0.0; switch (embd_norm) { case -1: // no normalisation sum = 1.0; break; case 0: // max absolute for (int i = 0; i < n; i++) { if (sum < std::abs(inp[i])) sum = std::abs(inp[i]); } sum /= 32760.0; // make an int16 range break; case 2: // euclidean for (int i = 0; i < n; i++) { sum += inp[i] * inp[i]; } sum = std::sqrt(sum); break; default: // p-norm (euclidean is p-norm p=2) for (int i = 0; i < n; i++) { sum += std::pow(std::abs(inp[i]), embd_norm); } sum = std::pow(sum, 1.0 / embd_norm); break; } const float norm = sum > 0.0 ? 1.0 / sum : 0.0f; for (int i = 0; i < n; i++) { out[i] = inp[i] * norm; } } float common_embd_similarity_cos(const float * embd1, const float * embd2, int n){ double sum = 0.0; double sum1 = 0.0; double sum2 = 0.0; for (int i = 0; i < n; i++) { sum += embd1[i] * embd2[i]; sum1 += embd1[i] * embd1[i]; sum2 += embd2[i] * embd2[i]; } // Handle the case where one or both vectors are zero vectors if (sum1 == 0.0 || sum2 == 0.0) { if (sum1 == 0.0 && sum2 == 0.0) { return 1.0f; // two zero vectors are similar } return 0.0f; } return sum / (sqrt(sum1) * sqrt(sum2)); } // // Control vector utils // static common_control_vector_data common_control_vector_load_one(const common_control_vector_load_info & load_info) { common_control_vector_data result = { -1, {} }; ggml_context * ctx = nullptr; struct gguf_init_params meta_gguf_params = { /* .no_alloc = */ false, /* .ctx = */ &ctx, }; struct gguf_context * ctx_gguf = gguf_init_from_file(load_info.fname.c_str(), meta_gguf_params); if (!ctx_gguf) { LOG_ERR("%s: failed to load control vector file from %s\n", __func__, load_info.fname.c_str()); return result; } int32_t n_tensors = gguf_get_n_tensors(ctx_gguf); if (n_tensors == 0) { LOG_WRN("%s: no direction tensors found in %s\n", __func__, load_info.fname.c_str()); } for (int i = 0; i < n_tensors; i++) { std::string name = gguf_get_tensor_name(ctx_gguf, i); int layer_idx = -1; // split on '.' size_t dotpos = name.find('.'); if (dotpos != std::string::npos && name.substr(0, dotpos) == "direction") { try { layer_idx = std::stoi(name.substr(dotpos + 1)); } catch (...) { layer_idx = -1; } } if (layer_idx < 0) { LOG_ERR("%s: invalid/unparsable direction tensor layer index in %s\n", __func__, load_info.fname.c_str()); result.n_embd = -1; break; } else if (layer_idx == 0) { LOG_ERR("%s: invalid (zero) direction tensor layer index in %s\n", __func__, load_info.fname.c_str()); result.n_embd = -1; break; } struct ggml_tensor * tensor = ggml_get_tensor(ctx, name.c_str()); if (tensor->type != GGML_TYPE_F32) { LOG_ERR("%s: invalid (non-F32) direction tensor type in %s\n", __func__, load_info.fname.c_str()); result.n_embd = -1; break; } if (ggml_n_dims(tensor) != 1) { LOG_ERR("%s: invalid (non-1D) direction tensor shape in %s\n", __func__, load_info.fname.c_str()); result.n_embd = -1; break; } if (result.n_embd == -1) { result.n_embd = ggml_nelements(tensor); } else if (ggml_nelements(tensor) != result.n_embd) { LOG_ERR("%s: direction tensor in %s does not match previous dimensions\n", __func__, load_info.fname.c_str()); result.n_embd = -1; break; } // extend if necessary - do not store data for layer 0 (it's not used) result.data.resize(std::max(result.data.size(), static_cast(result.n_embd * layer_idx)), 0.0f); const float * src = (const float *) tensor->data; float * dst = result.data.data() + result.n_embd * (layer_idx - 1); // layer 1 at [0] for (int j = 0; j < result.n_embd; j++) { dst[j] += src[j] * load_info.strength; // allows multiple directions for same layer in same file } } if (result.n_embd == -1) { LOG_WRN("%s: skipping %s due to invalid direction tensors\n", __func__, load_info.fname.c_str()); result.data.clear(); } gguf_free(ctx_gguf); ggml_free(ctx); return result; } common_control_vector_data common_control_vector_load(const std::vector & load_infos) { common_control_vector_data result = { -1, {} }; for (const auto & info : load_infos) { auto cur = common_control_vector_load_one(info); if (cur.n_embd == -1) { result.n_embd = -1; break; } if (result.n_embd != -1 && result.n_embd != cur.n_embd) { LOG_ERR("%s: control vectors in %s does not match previous dimensions\n", __func__, info.fname.c_str()); result.n_embd = -1; break; } if (result.n_embd == -1) { result = std::move(cur); } else { result.data.resize(std::max(result.data.size(), cur.data.size()), 0.0f); // extend if necessary for (size_t i = 0; i < cur.data.size(); i++) { result.data[i] += cur.data[i]; } } } if (result.n_embd == -1) { LOG_ERR("%s: no valid control vector files passed\n", __func__); result.data.clear(); } return result; }