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#if defined(_WIN32)
# include <windows.h>
# include <io.h>
#else
# include <sys/file.h>
# include <sys/ioctl.h>
# include <unistd.h>
#endif
#if defined(LLAMA_USE_CURL)
# include <curl/curl.h>
#endif
#include <signal.h>
#include <climits>
#include <cstdarg>
#include <cstdio>
#include <cstring>
#include <filesystem>
#include <iostream>
#include <sstream>
#include <string>
#include <vector>
#include "common.h"
#include "json.hpp"
#include "llama-cpp.h"
#if defined(__unix__) || (defined(__APPLE__) && defined(__MACH__)) || defined(_WIN32)
[[noreturn]] static void sigint_handler(int) {
printf("\n\033[0m");
exit(0); // not ideal, but it's the only way to guarantee exit in all cases
}
#endif
GGML_ATTRIBUTE_FORMAT(1, 2)
static std::string fmt(const char * fmt, ...) {
va_list ap;
va_list ap2;
va_start(ap, fmt);
va_copy(ap2, ap);
const int size = vsnprintf(NULL, 0, fmt, ap);
GGML_ASSERT(size >= 0 && size < INT_MAX); // NOLINT
std::string buf;
buf.resize(size);
const int size2 = vsnprintf(const_cast<char *>(buf.data()), buf.size() + 1, fmt, ap2);
GGML_ASSERT(size2 == size);
va_end(ap2);
va_end(ap);
return buf;
}
GGML_ATTRIBUTE_FORMAT(1, 2)
static int printe(const char * fmt, ...) {
va_list args;
va_start(args, fmt);
const int ret = vfprintf(stderr, fmt, args);
va_end(args);
return ret;
}
class Opt {
public:
int init(int argc, const char ** argv) {
ctx_params = llama_context_default_params();
model_params = llama_model_default_params();
context_size_default = ctx_params.n_batch;
ngl_default = model_params.n_gpu_layers;
common_params_sampling sampling;
temperature_default = sampling.temp;
if (argc < 2) {
printe("Error: No arguments provided.\n");
print_help();
return 1;
}
// Parse arguments
if (parse(argc, argv)) {
printe("Error: Failed to parse arguments.\n");
print_help();
return 1;
}
// If help is requested, show help and exit
if (help) {
print_help();
return 2;
}
ctx_params.n_batch = context_size >= 0 ? context_size : context_size_default;
ctx_params.n_ctx = ctx_params.n_batch;
model_params.n_gpu_layers = ngl >= 0 ? ngl : ngl_default;
temperature = temperature >= 0 ? temperature : temperature_default;
return 0; // Success
}
llama_context_params ctx_params;
llama_model_params model_params;
std::string model_;
std::string user;
int context_size = -1, ngl = -1;
float temperature = -1;
bool verbose = false;
private:
int context_size_default = -1, ngl_default = -1;
float temperature_default = -1;
bool help = false;
bool parse_flag(const char ** argv, int i, const char * short_opt, const char * long_opt) {
return strcmp(argv[i], short_opt) == 0 || strcmp(argv[i], long_opt) == 0;
}
int handle_option_with_value(int argc, const char ** argv, int & i, int & option_value) {
if (i + 1 >= argc) {
return 1;
}
option_value = std::atoi(argv[++i]);
return 0;
}
int handle_option_with_value(int argc, const char ** argv, int & i, float & option_value) {
if (i + 1 >= argc) {
return 1;
}
option_value = std::atof(argv[++i]);
return 0;
}
int parse(int argc, const char ** argv) {
bool options_parsing = true;
for (int i = 1, positional_args_i = 0; i < argc; ++i) {
if (options_parsing && (strcmp(argv[i], "-c") == 0 || strcmp(argv[i], "--context-size") == 0)) {
if (handle_option_with_value(argc, argv, i, context_size) == 1) {
return 1;
}
} else if (options_parsing && (strcmp(argv[i], "-n") == 0 || strcmp(argv[i], "--ngl") == 0)) {
if (handle_option_with_value(argc, argv, i, ngl) == 1) {
return 1;
}
} else if (options_parsing && strcmp(argv[i], "--temp") == 0) {
if (handle_option_with_value(argc, argv, i, temperature) == 1) {
return 1;
}
} else if (options_parsing &&
(parse_flag(argv, i, "-v", "--verbose") || parse_flag(argv, i, "-v", "--log-verbose"))) {
verbose = true;
} else if (options_parsing && parse_flag(argv, i, "-h", "--help")) {
help = true;
return 0;
} else if (options_parsing && strcmp(argv[i], "--") == 0) {
options_parsing = false;
} else if (positional_args_i == 0) {
if (!argv[i][0] || argv[i][0] == '-') {
return 1;
}
++positional_args_i;
model_ = argv[i];
} else if (positional_args_i == 1) {
++positional_args_i;
user = argv[i];
} else {
user += " " + std::string(argv[i]);
}
}
return 0;
}
void print_help() const {
printf(
"Description:\n"
" Runs a llm\n"
"\n"
"Usage:\n"
" llama-run [options] model [prompt]\n"
"\n"
"Options:\n"
" -c, --context-size <value>\n"
" Context size (default: %d)\n"
" -n, --ngl <value>\n"
" Number of GPU layers (default: %d)\n"
" --temp <value>\n"
" Temperature (default: %.1f)\n"
" -v, --verbose, --log-verbose\n"
" Set verbosity level to infinity (i.e. log all messages, useful for debugging)\n"
" -h, --help\n"
" Show help message\n"
"\n"
"Commands:\n"
" model\n"
" Model is a string with an optional prefix of \n"
" huggingface:// (hf://), ollama://, https:// or file://.\n"
" If no protocol is specified and a file exists in the specified\n"
" path, file:// is assumed, otherwise if a file does not exist in\n"
" the specified path, ollama:// is assumed. Models that are being\n"
" pulled are downloaded with .partial extension while being\n"
" downloaded and then renamed as the file without the .partial\n"
" extension when complete.\n"
"\n"
"Examples:\n"
" llama-run llama3\n"
" llama-run ollama://granite-code\n"
" llama-run ollama://smollm:135m\n"
" llama-run hf://QuantFactory/SmolLM-135M-GGUF/SmolLM-135M.Q2_K.gguf\n"
" llama-run "
"huggingface://bartowski/SmolLM-1.7B-Instruct-v0.2-GGUF/SmolLM-1.7B-Instruct-v0.2-IQ3_M.gguf\n"
" llama-run https://example.com/some-file1.gguf\n"
" llama-run some-file2.gguf\n"
" llama-run file://some-file3.gguf\n"
" llama-run --ngl 999 some-file4.gguf\n"
" llama-run --ngl 999 some-file5.gguf Hello World\n",
context_size_default, ngl_default, temperature_default);
}
};
struct progress_data {
size_t file_size = 0;
std::chrono::steady_clock::time_point start_time = std::chrono::steady_clock::now();
bool printed = false;
};
static int get_terminal_width() {
#if defined(_WIN32)
CONSOLE_SCREEN_BUFFER_INFO csbi;
GetConsoleScreenBufferInfo(GetStdHandle(STD_OUTPUT_HANDLE), &csbi);
return csbi.srWindow.Right - csbi.srWindow.Left + 1;
#else
struct winsize w;
ioctl(STDOUT_FILENO, TIOCGWINSZ, &w);
return w.ws_col;
#endif
}
#ifdef LLAMA_USE_CURL
class File {
public:
FILE * file = nullptr;
FILE * open(const std::string & filename, const char * mode) {
file = fopen(filename.c_str(), mode);
return file;
}
int lock() {
if (file) {
# ifdef _WIN32
fd = _fileno(file);
hFile = (HANDLE) _get_osfhandle(fd);
if (hFile == INVALID_HANDLE_VALUE) {
fd = -1;
return 1;
}
OVERLAPPED overlapped = {};
if (!LockFileEx(hFile, LOCKFILE_EXCLUSIVE_LOCK | LOCKFILE_FAIL_IMMEDIATELY, 0, MAXDWORD, MAXDWORD,
&overlapped)) {
fd = -1;
return 1;
}
# else
fd = fileno(file);
if (flock(fd, LOCK_EX | LOCK_NB) != 0) {
fd = -1;
return 1;
}
# endif
}
return 0;
}
~File() {
if (fd >= 0) {
# ifdef _WIN32
if (hFile != INVALID_HANDLE_VALUE) {
OVERLAPPED overlapped = {};
UnlockFileEx(hFile, 0, MAXDWORD, MAXDWORD, &overlapped);
}
# else
flock(fd, LOCK_UN);
# endif
}
if (file) {
fclose(file);
}
}
private:
int fd = -1;
# ifdef _WIN32
HANDLE hFile = nullptr;
# endif
};
class HttpClient {
public:
int init(const std::string & url, const std::vector<std::string> & headers, const std::string & output_file,
const bool progress, std::string * response_str = nullptr) {
std::string output_file_partial;
curl = curl_easy_init();
if (!curl) {
return 1;
}
progress_data data;
File out;
if (!output_file.empty()) {
output_file_partial = output_file + ".partial";
if (!out.open(output_file_partial, "ab")) {
printe("Failed to open file\n");
return 1;
}
if (out.lock()) {
printe("Failed to exclusively lock file\n");
return 1;
}
}
set_write_options(response_str, out);
data.file_size = set_resume_point(output_file_partial);
set_progress_options(progress, data);
set_headers(headers);
perform(url);
if (!output_file.empty()) {
std::filesystem::rename(output_file_partial, output_file);
}
return 0;
}
~HttpClient() {
if (chunk) {
curl_slist_free_all(chunk);
}
if (curl) {
curl_easy_cleanup(curl);
}
}
private:
CURL * curl = nullptr;
struct curl_slist * chunk = nullptr;
void set_write_options(std::string * response_str, const File & out) {
if (response_str) {
curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, capture_data);
curl_easy_setopt(curl, CURLOPT_WRITEDATA, response_str);
} else {
curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, write_data);
curl_easy_setopt(curl, CURLOPT_WRITEDATA, out.file);
}
}
size_t set_resume_point(const std::string & output_file) {
size_t file_size = 0;
if (std::filesystem::exists(output_file)) {
file_size = std::filesystem::file_size(output_file);
curl_easy_setopt(curl, CURLOPT_RESUME_FROM_LARGE, static_cast<curl_off_t>(file_size));
}
return file_size;
}
void set_progress_options(bool progress, progress_data & data) {
if (progress) {
curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 0L);
curl_easy_setopt(curl, CURLOPT_XFERINFODATA, &data);
curl_easy_setopt(curl, CURLOPT_XFERINFOFUNCTION, update_progress);
}
}
void set_headers(const std::vector<std::string> & headers) {
if (!headers.empty()) {
if (chunk) {
curl_slist_free_all(chunk);
chunk = 0;
}
for (const auto & header : headers) {
chunk = curl_slist_append(chunk, header.c_str());
}
curl_easy_setopt(curl, CURLOPT_HTTPHEADER, chunk);
}
}
void perform(const std::string & url) {
CURLcode res;
curl_easy_setopt(curl, CURLOPT_URL, url.c_str());
curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
curl_easy_setopt(curl, CURLOPT_DEFAULT_PROTOCOL, "https");
curl_easy_setopt(curl, CURLOPT_FAILONERROR, 1L);
res = curl_easy_perform(curl);
if (res != CURLE_OK) {
printe("curl_easy_perform() failed: %s\n", curl_easy_strerror(res));
}
}
static std::string human_readable_time(double seconds) {
int hrs = static_cast<int>(seconds) / 3600;
int mins = (static_cast<int>(seconds) % 3600) / 60;
int secs = static_cast<int>(seconds) % 60;
if (hrs > 0) {
return fmt("%dh %02dm %02ds", hrs, mins, secs);
} else if (mins > 0) {
return fmt("%dm %02ds", mins, secs);
} else {
return fmt("%ds", secs);
}
}
static std::string human_readable_size(curl_off_t size) {
static const char * suffix[] = { "B", "KB", "MB", "GB", "TB" };
char length = sizeof(suffix) / sizeof(suffix[0]);
int i = 0;
double dbl_size = size;
if (size > 1024) {
for (i = 0; (size / 1024) > 0 && i < length - 1; i++, size /= 1024) {
dbl_size = size / 1024.0;
}
}
return fmt("%.2f %s", dbl_size, suffix[i]);
}
static int update_progress(void * ptr, curl_off_t total_to_download, curl_off_t now_downloaded, curl_off_t,
curl_off_t) {
progress_data * data = static_cast<progress_data *>(ptr);
if (total_to_download <= 0) {
return 0;
}
total_to_download += data->file_size;
const curl_off_t now_downloaded_plus_file_size = now_downloaded + data->file_size;
const curl_off_t percentage = calculate_percentage(now_downloaded_plus_file_size, total_to_download);
std::string progress_prefix = generate_progress_prefix(percentage);
const double speed = calculate_speed(now_downloaded, data->start_time);
const double tim = (total_to_download - now_downloaded) / speed;
std::string progress_suffix =
generate_progress_suffix(now_downloaded_plus_file_size, total_to_download, speed, tim);
int progress_bar_width = calculate_progress_bar_width(progress_prefix, progress_suffix);
std::string progress_bar;
generate_progress_bar(progress_bar_width, percentage, progress_bar);
print_progress(progress_prefix, progress_bar, progress_suffix);
data->printed = true;
return 0;
}
static curl_off_t calculate_percentage(curl_off_t now_downloaded_plus_file_size, curl_off_t total_to_download) {
return (now_downloaded_plus_file_size * 100) / total_to_download;
}
static std::string generate_progress_prefix(curl_off_t percentage) { return fmt("%3ld%% |", static_cast<long int>(percentage)); }
static double calculate_speed(curl_off_t now_downloaded, const std::chrono::steady_clock::time_point & start_time) {
const auto now = std::chrono::steady_clock::now();
const std::chrono::duration<double> elapsed_seconds = now - start_time;
return now_downloaded / elapsed_seconds.count();
}
static std::string generate_progress_suffix(curl_off_t now_downloaded_plus_file_size, curl_off_t total_to_download,
double speed, double estimated_time) {
const int width = 10;
return fmt("%*s/%*s%*s/s%*s", width, human_readable_size(now_downloaded_plus_file_size).c_str(), width,
human_readable_size(total_to_download).c_str(), width, human_readable_size(speed).c_str(), width,
human_readable_time(estimated_time).c_str());
}
static int calculate_progress_bar_width(const std::string & progress_prefix, const std::string & progress_suffix) {
int progress_bar_width = get_terminal_width() - progress_prefix.size() - progress_suffix.size() - 3;
if (progress_bar_width < 1) {
progress_bar_width = 1;
}
return progress_bar_width;
}
static std::string generate_progress_bar(int progress_bar_width, curl_off_t percentage,
std::string & progress_bar) {
const curl_off_t pos = (percentage * progress_bar_width) / 100;
for (int i = 0; i < progress_bar_width; ++i) {
progress_bar.append((i < pos) ? "█" : " ");
}
return progress_bar;
}
static void print_progress(const std::string & progress_prefix, const std::string & progress_bar,
const std::string & progress_suffix) {
printe("\r%*s\r%s%s| %s", get_terminal_width(), " ", progress_prefix.c_str(), progress_bar.c_str(),
progress_suffix.c_str());
}
// Function to write data to a file
static size_t write_data(void * ptr, size_t size, size_t nmemb, void * stream) {
FILE * out = static_cast<FILE *>(stream);
return fwrite(ptr, size, nmemb, out);
}
// Function to capture data into a string
static size_t capture_data(void * ptr, size_t size, size_t nmemb, void * stream) {
std::string * str = static_cast<std::string *>(stream);
str->append(static_cast<char *>(ptr), size * nmemb);
return size * nmemb;
}
};
#endif
class LlamaData {
public:
llama_model_ptr model;
llama_sampler_ptr sampler;
llama_context_ptr context;
std::vector<llama_chat_message> messages;
std::vector<std::string> msg_strs;
std::vector<char> fmtted;
int init(Opt & opt) {
model = initialize_model(opt);
if (!model) {
return 1;
}
context = initialize_context(model, opt);
if (!context) {
return 1;
}
sampler = initialize_sampler(opt);
return 0;
}
private:
#ifdef LLAMA_USE_CURL
int download(const std::string & url, const std::vector<std::string> & headers, const std::string & output_file,
const bool progress, std::string * response_str = nullptr) {
HttpClient http;
if (http.init(url, headers, output_file, progress, response_str)) {
return 1;
}
return 0;
}
#else
int download(const std::string &, const std::vector<std::string> &, const std::string &, const bool,
std::string * = nullptr) {
printe("%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__);
return 1;
}
#endif
int huggingface_dl(const std::string & model, const std::vector<std::string> headers, const std::string & bn) {
// Find the second occurrence of '/' after protocol string
size_t pos = model.find('/');
pos = model.find('/', pos + 1);
if (pos == std::string::npos) {
return 1;
}
const std::string hfr = model.substr(0, pos);
const std::string hff = model.substr(pos + 1);
const std::string url = "https://huggingface.co/" + hfr + "/resolve/main/" + hff;
return download(url, headers, bn, true);
}
int ollama_dl(std::string & model, const std::vector<std::string> headers, const std::string & bn) {
if (model.find('/') == std::string::npos) {
model = "library/" + model;
}
std::string model_tag = "latest";
size_t colon_pos = model.find(':');
if (colon_pos != std::string::npos) {
model_tag = model.substr(colon_pos + 1);
model = model.substr(0, colon_pos);
}
std::string manifest_url = "https://registry.ollama.ai/v2/" + model + "/manifests/" + model_tag;
std::string manifest_str;
const int ret = download(manifest_url, headers, "", false, &manifest_str);
if (ret) {
return ret;
}
nlohmann::json manifest = nlohmann::json::parse(manifest_str);
std::string layer;
for (const auto & l : manifest["layers"]) {
if (l["mediaType"] == "application/vnd.ollama.image.model") {
layer = l["digest"];
break;
}
}
std::string blob_url = "https://registry.ollama.ai/v2/" + model + "/blobs/" + layer;
return download(blob_url, headers, bn, true);
}
std::string basename(const std::string & path) {
const size_t pos = path.find_last_of("/\\");
if (pos == std::string::npos) {
return path;
}
return path.substr(pos + 1);
}
int remove_proto(std::string & model_) {
const std::string::size_type pos = model_.find("://");
if (pos == std::string::npos) {
return 1;
}
model_ = model_.substr(pos + 3); // Skip past "://"
return 0;
}
int resolve_model(std::string & model_) {
int ret = 0;
if (string_starts_with(model_, "file://") || std::filesystem::exists(model_)) {
remove_proto(model_);
return ret;
}
const std::string bn = basename(model_);
const std::vector<std::string> headers = { "--header",
"Accept: application/vnd.docker.distribution.manifest.v2+json" };
if (string_starts_with(model_, "hf://") || string_starts_with(model_, "huggingface://")) {
remove_proto(model_);
ret = huggingface_dl(model_, headers, bn);
} else if (string_starts_with(model_, "ollama://")) {
remove_proto(model_);
ret = ollama_dl(model_, headers, bn);
} else if (string_starts_with(model_, "https://")) {
download(model_, headers, bn, true);
} else {
ret = ollama_dl(model_, headers, bn);
}
model_ = bn;
return ret;
}
// Initializes the model and returns a unique pointer to it
llama_model_ptr initialize_model(Opt & opt) {
ggml_backend_load_all();
resolve_model(opt.model_);
printe(
"\r%*s"
"\rLoading model",
get_terminal_width(), " ");
llama_model_ptr model(llama_model_load_from_file(opt.model_.c_str(), opt.model_params));
if (!model) {
printe("%s: error: unable to load model from file: %s\n", __func__, opt.model_.c_str());
}
printe("\r%*s\r", static_cast<int>(sizeof("Loading model")), " ");
return model;
}
// Initializes the context with the specified parameters
llama_context_ptr initialize_context(const llama_model_ptr & model, const Opt & opt) {
llama_context_ptr context(llama_init_from_model(model.get(), opt.ctx_params));
if (!context) {
printe("%s: error: failed to create the llama_context\n", __func__);
}
return context;
}
// Initializes and configures the sampler
llama_sampler_ptr initialize_sampler(const Opt & opt) {
llama_sampler_ptr sampler(llama_sampler_chain_init(llama_sampler_chain_default_params()));
llama_sampler_chain_add(sampler.get(), llama_sampler_init_min_p(0.05f, 1));
llama_sampler_chain_add(sampler.get(), llama_sampler_init_temp(opt.temperature));
llama_sampler_chain_add(sampler.get(), llama_sampler_init_dist(LLAMA_DEFAULT_SEED));
return sampler;
}
};
// Add a message to `messages` and store its content in `msg_strs`
static void add_message(const char * role, const std::string & text, LlamaData & llama_data) {
llama_data.msg_strs.push_back(std::move(text));
llama_data.messages.push_back({ role, llama_data.msg_strs.back().c_str() });
}
// Function to apply the chat template and resize `formatted` if needed
static int apply_chat_template(LlamaData & llama_data, const bool append) {
int result = llama_chat_apply_template(
llama_model_chat_template(llama_data.model.get()), llama_data.messages.data(), llama_data.messages.size(), append,
append ? llama_data.fmtted.data() : nullptr, append ? llama_data.fmtted.size() : 0);
if (append && result > static_cast<int>(llama_data.fmtted.size())) {
llama_data.fmtted.resize(result);
result = llama_chat_apply_template(llama_model_chat_template(llama_data.model.get()), llama_data.messages.data(),
llama_data.messages.size(), append, llama_data.fmtted.data(),
llama_data.fmtted.size());
}
return result;
}
// Function to tokenize the prompt
static int tokenize_prompt(const llama_vocab * vocab, const std::string & prompt,
std::vector<llama_token> & prompt_tokens) {
const int n_prompt_tokens = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), NULL, 0, true, true);
prompt_tokens.resize(n_prompt_tokens);
if (llama_tokenize(vocab, prompt.c_str(), prompt.size(), prompt_tokens.data(), prompt_tokens.size(), true,
true) < 0) {
printe("failed to tokenize the prompt\n");
return -1;
}
return n_prompt_tokens;
}
// Check if we have enough space in the context to evaluate this batch
static int check_context_size(const llama_context_ptr & ctx, const llama_batch & batch) {
const int n_ctx = llama_n_ctx(ctx.get());
const int n_ctx_used = llama_get_kv_cache_used_cells(ctx.get());
if (n_ctx_used + batch.n_tokens > n_ctx) {
printf("\033[0m\n");
printe("context size exceeded\n");
return 1;
}
return 0;
}
// convert the token to a string
static int convert_token_to_string(const llama_vocab * vocab, const llama_token token_id, std::string & piece) {
char buf[256];
int n = llama_token_to_piece(vocab, token_id, buf, sizeof(buf), 0, true);
if (n < 0) {
printe("failed to convert token to piece\n");
return 1;
}
piece = std::string(buf, n);
return 0;
}
static void print_word_and_concatenate_to_response(const std::string & piece, std::string & response) {
printf("%s", piece.c_str());
fflush(stdout);
response += piece;
}
// helper function to evaluate a prompt and generate a response
static int generate(LlamaData & llama_data, const std::string & prompt, std::string & response) {
const llama_vocab * vocab = llama_model_get_vocab(llama_data.model.get());
std::vector<llama_token> tokens;
if (tokenize_prompt(vocab, prompt, tokens) < 0) {
return 1;
}
// prepare a batch for the prompt
llama_batch batch = llama_batch_get_one(tokens.data(), tokens.size());
llama_token new_token_id;
while (true) {
check_context_size(llama_data.context, batch);
if (llama_decode(llama_data.context.get(), batch)) {
printe("failed to decode\n");
return 1;
}
// sample the next token, check is it an end of generation?
new_token_id = llama_sampler_sample(llama_data.sampler.get(), llama_data.context.get(), -1);
if (llama_vocab_is_eog(vocab, new_token_id)) {
break;
}
std::string piece;
if (convert_token_to_string(vocab, new_token_id, piece)) {
return 1;
}
print_word_and_concatenate_to_response(piece, response);
// prepare the next batch with the sampled token
batch = llama_batch_get_one(&new_token_id, 1);
}
return 0;
}
static int read_user_input(std::string & user) {
std::getline(std::cin, user);
if (std::cin.eof()) {
printf("\n");
return 1;
}
if (user == "/bye") {
return 1;
}
if (user.empty()) {
return 2;
}
return 0; // Should have data in happy path
}
// Function to generate a response based on the prompt
static int generate_response(LlamaData & llama_data, const std::string & prompt, std::string & response,
const bool stdout_a_terminal) {
// Set response color
if (stdout_a_terminal) {
printf("\033[33m");
}
if (generate(llama_data, prompt, response)) {
printe("failed to generate response\n");
return 1;
}
// End response with color reset and newline
printf("\n%s", stdout_a_terminal ? "\033[0m" : "");
return 0;
}
// Helper function to apply the chat template and handle errors
static int apply_chat_template_with_error_handling(LlamaData & llama_data, const bool append, int & output_length) {
const int new_len = apply_chat_template(llama_data, append);
if (new_len < 0) {
printe("failed to apply the chat template\n");
return -1;
}
output_length = new_len;
return 0;
}
// Helper function to handle user input
static int handle_user_input(std::string & user_input, const std::string & user) {
if (!user.empty()) {
user_input = user;
return 0; // No need for interactive input
}
printf(
"\r%*s"
"\r\033[32m> \033[0m",
get_terminal_width(), " ");
return read_user_input(user_input); // Returns true if input ends the loop
}
static bool is_stdin_a_terminal() {
#if defined(_WIN32)
HANDLE hStdin = GetStdHandle(STD_INPUT_HANDLE);
DWORD mode;
return GetConsoleMode(hStdin, &mode);
#else
return isatty(STDIN_FILENO);
#endif
}
static bool is_stdout_a_terminal() {
#if defined(_WIN32)
HANDLE hStdout = GetStdHandle(STD_OUTPUT_HANDLE);
DWORD mode;
return GetConsoleMode(hStdout, &mode);
#else
return isatty(STDOUT_FILENO);
#endif
}
// Function to handle user input
static int get_user_input(std::string & user_input, const std::string & user) {
while (true) {
const int ret = handle_user_input(user_input, user);
if (ret == 1) {
return 1;
}
if (ret == 2) {
continue;
}
break;
}
return 0;
}
// Main chat loop function
static int chat_loop(LlamaData & llama_data, const std::string & user) {
int prev_len = 0;
llama_data.fmtted.resize(llama_n_ctx(llama_data.context.get()));
static const bool stdout_a_terminal = is_stdout_a_terminal();
while (true) {
// Get user input
std::string user_input;
if (get_user_input(user_input, user) == 1) {
return 0;
}
add_message("user", user.empty() ? user_input : user, llama_data);
int new_len;
if (apply_chat_template_with_error_handling(llama_data, true, new_len) < 0) {
return 1;
}
std::string prompt(llama_data.fmtted.begin() + prev_len, llama_data.fmtted.begin() + new_len);
std::string response;
if (generate_response(llama_data, prompt, response, stdout_a_terminal)) {
return 1;
}
if (!user.empty()) {
break;
}
add_message("assistant", response, llama_data);
if (apply_chat_template_with_error_handling(llama_data, false, prev_len) < 0) {
return 1;
}
}
return 0;
}
static void log_callback(const enum ggml_log_level level, const char * text, void * p) {
const Opt * opt = static_cast<Opt *>(p);
if (opt->verbose || level == GGML_LOG_LEVEL_ERROR) {
printe("%s", text);
}
}
static std::string read_pipe_data() {
std::ostringstream result;
result << std::cin.rdbuf(); // Read all data from std::cin
return result.str();
}
static void ctrl_c_handling() {
#if defined(__unix__) || (defined(__APPLE__) && defined(__MACH__))
struct sigaction sigint_action;
sigint_action.sa_handler = sigint_handler;
sigemptyset(&sigint_action.sa_mask);
sigint_action.sa_flags = 0;
sigaction(SIGINT, &sigint_action, NULL);
#elif defined(_WIN32)
auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
return (ctrl_type == CTRL_C_EVENT) ? (sigint_handler(SIGINT), true) : false;
};
SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
#endif
}
int main(int argc, const char ** argv) {
ctrl_c_handling();
Opt opt;
const int ret = opt.init(argc, argv);
if (ret == 2) {
return 0;
} else if (ret) {
return 1;
}
if (!is_stdin_a_terminal()) {
if (!opt.user.empty()) {
opt.user += "\n\n";
}
opt.user += read_pipe_data();
}
llama_log_set(log_callback, &opt);
LlamaData llama_data;
if (llama_data.init(opt)) {
return 1;
}