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gemma3-cli.cpp
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#include "arg.h"
#include "log.h"
#include "common.h"
#include "sampling.h"
#include "llama.h"
#include "ggml.h"
#include "console.h"
#include "chat.h"
#include "mtmd.h"
#include <vector>
#include <limits.h>
#include <cinttypes>
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
#include <signal.h>
#include <unistd.h>
#elif defined (_WIN32)
#define WIN32_LEAN_AND_MEAN
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include <windows.h>
#include <signal.h>
#endif
static bool g_is_generating = false;
/**
* Please note that this is NOT a production-ready stuff.
* It is a playground for trying Gemma 3 vision capabilities.
* For contributors: please keep this code simple and easy to understand.
*/
static void show_additional_info(int /*argc*/, char ** argv) {
LOG(
"Experimental CLI for using Gemma 3 vision model\n\n"
"Usage: %s [options] -m <model> --mmproj <mmproj> --image <image> -p <prompt>\n\n"
" -m and --mmproj are required\n"
" --image and -p are optional, if NOT provided, the CLI will run in chat mode\n",
argv[0]
);
}
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)
static void sigint_handler(int signo) {
if (signo == SIGINT) {
if (g_is_generating) {
g_is_generating = false;
} else {
console::cleanup();
LOG("\nInterrupted by user\n");
_exit(130);
}
}
}
#endif
struct gemma3_context {
mtmd_context_ptr ctx_vision;
common_init_result llama_init;
llama_model * model;
llama_context * lctx;
const llama_vocab * vocab;
llama_batch batch;
int n_batch;
// note: we know that gemma3 template is "linear", meaning each turn is completely separated to another
// so here we don't need to keep track of chat history
common_chat_templates_ptr tmpls;
int n_threads = 1;
llama_pos n_past = 0;
gemma3_context(common_params & params) : llama_init(common_init_from_params(params)) {
model = llama_init.model.get();
lctx = llama_init.context.get();
vocab = llama_model_get_vocab(model);
n_threads = params.cpuparams.n_threads;
batch = llama_batch_init(params.n_batch, 0, 1);
n_batch = params.n_batch;
tmpls = common_chat_templates_init(model, params.chat_template);
init_vision_context(params);
}
void init_vision_context(common_params & params) {
const char * clip_path = params.mmproj.path.c_str();
ctx_vision.reset(mtmd_init_from_file(clip_path, model, mtmd_context_params{
/* use_gpu */ true,
/* timings */ true,
/* n_threads */ params.cpuparams.n_threads,
/* verbosity */ GGML_LOG_LEVEL_INFO,
}));
if (!ctx_vision.get()) {
LOG_ERR("Failed to load vision model from %s\n", clip_path);
exit(1);
}
}
};
struct decode_embd_batch {
std::vector<llama_pos> pos;
std::vector<int32_t> n_seq_id;
std::vector<llama_seq_id> seq_id_0;
std::vector<llama_seq_id *> seq_ids;
std::vector<int8_t> logits;
llama_batch batch;
decode_embd_batch(float * embd, int32_t n_tokens, llama_pos pos_0, llama_seq_id seq_id) {
pos .resize(n_tokens);
n_seq_id.resize(n_tokens);
seq_ids .resize(n_tokens + 1);
logits .resize(n_tokens);
seq_id_0.resize(1);
seq_id_0[0] = seq_id;
seq_ids [n_tokens] = nullptr;
batch = {
/*n_tokens =*/ n_tokens,
/*tokens =*/ nullptr,
/*embd =*/ embd,
/*pos =*/ pos.data(),
/*n_seq_id =*/ n_seq_id.data(),
/*seq_id =*/ seq_ids.data(),
/*logits =*/ logits.data(),
};
for (int i = 0; i < n_tokens; i++) {
batch.pos [i] = pos_0 + i;
batch.n_seq_id[i] = 1;
batch.seq_id [i] = seq_id_0.data();
batch.logits [i] = false;
}
}
};
static int generate_response(gemma3_context & ctx, common_sampler * smpl, int n_predict) {
for (int i = 0; i < n_predict; i++) {
if (i > n_predict || !g_is_generating) {
printf("\n");
break;
}
llama_token token_id = common_sampler_sample(smpl, ctx.lctx, -1);
common_sampler_accept(smpl, token_id, true);
if (llama_vocab_is_eog(ctx.vocab, token_id)) {
printf("\n");
break; // end of generation
}
printf("%s", common_token_to_piece(ctx.lctx, token_id).c_str());
fflush(stdout);
// eval the token
common_batch_clear(ctx.batch);
common_batch_add(ctx.batch, token_id, ctx.n_past++, {0}, true);
if (llama_decode(ctx.lctx, ctx.batch)) {
LOG_ERR("failed to decode token\n");
return 1;
}
}
return 0;
}
static int eval_message(gemma3_context & ctx, common_chat_msg & msg, std::vector<std::string> & images_fname, bool add_bos = false) {
std::vector<mtmd_bitmap> bitmaps;
common_chat_templates_inputs tmpl_inputs;
tmpl_inputs.messages = {msg};
tmpl_inputs.add_generation_prompt = true;
tmpl_inputs.use_jinja = false; // jinja is buggy here
auto formatted_chat = common_chat_templates_apply(ctx.tmpls.get(), tmpl_inputs);
LOG_DBG("formatted_chat.prompt: %s\n", formatted_chat.prompt.c_str());
for (auto & fname : images_fname) {
mtmd_bitmap bitmap;
if (mtmd_helper_bitmap_init_from_file(fname.c_str(), bitmap)) {
LOG_ERR("Unable to load image %s\n", fname.c_str());
return 2; // image not found
}
bitmaps.push_back(std::move(bitmap));
}
mtmd_input_text text;
text.text = formatted_chat.prompt;
text.add_special = add_bos;
text.parse_special = true;
mtmd_input_chunks_ptr chunks(mtmd_tokenize(ctx.ctx_vision.get(), text, bitmaps));
if (chunks == nullptr) {
LOG_ERR("Unable to tokenize prompt\n");
return 1;
}
if (mtmd_helper_eval(ctx.ctx_vision.get(), ctx.lctx, chunks.get(), ctx.n_past, 0, ctx.n_batch)) {
LOG_ERR("Unable to eval prompt\n");
return 1;
}
ctx.n_past += mtmd_helper_get_n_tokens(chunks.get());
return 0;
}
int main(int argc, char ** argv) {
ggml_time_init();
common_params params;
params.sampling.temp = 0.2; // lower temp by default for better quality
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_LLAVA, show_additional_info)) {
return 1;
}
common_init();
if (params.mmproj.path.empty()) {
show_additional_info(argc, argv);
return 1;
}
gemma3_context ctx(params);
printf("%s: %s\n", __func__, params.model.path.c_str());
bool is_single_turn = !params.prompt.empty() && !params.image.empty();
struct common_sampler * smpl = common_sampler_init(ctx.model, params.sampling);
int n_predict = params.n_predict < 0 ? INT_MAX : params.n_predict;
// 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
}
if (is_single_turn) {
g_is_generating = true;
if (params.prompt.find("<__image__>") == std::string::npos) {
params.prompt += " <__image__>";
}
common_chat_msg msg;
msg.role = "user";
msg.content = params.prompt;
if (eval_message(ctx, msg, params.image, true)) {
return 1;
}
if (generate_response(ctx, smpl, n_predict)) {
return 1;
}
} else {
LOG("\n Running in chat mode, available commands:");
LOG("\n /image <path> load an image");
LOG("\n /clear clear the chat history");
LOG("\n /quit or /exit exit the program");
LOG("\n");
bool is_first_msg = true;
std::vector<std::string> images_fname;
std::string content;
while (true) {
g_is_generating = false;
LOG("\n> ");
console::set_display(console::user_input);
std::string line;
console::readline(line, false);
console::set_display(console::reset);
line = string_strip(line);
if (line.empty()) {
continue;
}
if (line == "/quit" || line == "/exit") {
break;
}
if (line == "/clear") {
ctx.n_past = 0;
llama_kv_self_seq_rm(ctx.lctx, 0, 1, -1); // keep BOS
LOG("Chat history cleared\n\n");
continue;
}
g_is_generating = true;
if (line.find("/image") == 0) {
std::string image = line.substr(7);
images_fname.push_back(string_strip(image));
content += "<__image__>";
continue;
} else {
content += line;
}
common_chat_msg msg;
msg.role = "user";
msg.content = content;
int ret = eval_message(ctx, msg, images_fname, is_first_msg);
if (ret == 2) {
// non-fatal error
images_fname.clear();
content.clear();
continue;
}
if (ret) {
return 1;
}
if (generate_response(ctx, smpl, n_predict)) {
return 1;
}
images_fname.clear();
content.clear();
is_first_msg = false;
}
}
llama_perf_context_print(ctx.lctx);
return 0;
}