mirror of
https://github.com/ggerganov/whisper.cpp.git
synced 2024-12-28 00:08:50 +00:00
1512545149
* whisper : add loader to allow loading from other than file * whisper : rename whisper_init to whisper_init_from_file * whisper : add whisper_init_from_buffer * android : Delete local.properties * android : load models directly from assets * whisper : adding <stddef.h> needed for size_t + code style Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
381 lines
12 KiB
C++
381 lines
12 KiB
C++
#include "ggml.h"
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#include "gpt-2.h"
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#include "whisper.h"
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#include <emscripten.h>
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#include <emscripten/bind.h>
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#include <atomic>
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#include <cmath>
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#include <mutex>
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#include <string>
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#include <thread>
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#include <vector>
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#include <regex>
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constexpr int N_THREAD = 8;
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struct gpt2_context * g_gpt2;
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std::vector<struct whisper_context *> g_contexts(4, nullptr);
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std::mutex g_mutex;
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std::thread g_worker;
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std::atomic<bool> g_running(false);
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bool g_force_speak = false;
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std::string g_text_to_speak = "";
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std::string g_status = "";
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std::string g_status_forced = "";
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std::vector<float> g_pcmf32;
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std::string to_timestamp(int64_t t) {
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int64_t sec = t/100;
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int64_t msec = t - sec*100;
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int64_t min = sec/60;
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sec = sec - min*60;
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char buf[32];
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snprintf(buf, sizeof(buf), "%02d:%02d.%03d", (int) min, (int) sec, (int) msec);
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return std::string(buf);
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}
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void talk_set_status(const std::string & status) {
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std::lock_guard<std::mutex> lock(g_mutex);
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g_status = status;
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}
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void talk_main(size_t index) {
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talk_set_status("loading data ...");
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struct whisper_full_params wparams = whisper_full_default_params(whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY);
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wparams.n_threads = std::min(N_THREAD, (int) std::thread::hardware_concurrency());
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wparams.offset_ms = 0;
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wparams.translate = false;
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wparams.no_context = true;
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wparams.single_segment = true;
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wparams.print_realtime = false;
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wparams.print_progress = false;
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wparams.print_timestamps = true;
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wparams.print_special = false;
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wparams.max_tokens = 32;
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wparams.audio_ctx = 768; // partial encoder context for better performance
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wparams.language = "en";
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g_gpt2 = gpt2_init("gpt-2.bin");
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printf("talk: using %d threads\n", wparams.n_threads);
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std::vector<float> pcmf32;
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// whisper context
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auto & ctx = g_contexts[index];
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const int64_t step_samples = 2*WHISPER_SAMPLE_RATE;
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const int64_t window_samples = 9*WHISPER_SAMPLE_RATE;
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const int64_t step_ms = (step_samples*1000)/WHISPER_SAMPLE_RATE;
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auto t_last = std::chrono::high_resolution_clock::now();
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talk_set_status("listening ...");
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while (g_running) {
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const auto t_now = std::chrono::high_resolution_clock::now();
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if (std::chrono::duration_cast<std::chrono::milliseconds>(t_now - t_last).count() < step_ms) {
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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g_pcmf32.clear();
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}
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std::this_thread::sleep_for(std::chrono::milliseconds(10));
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continue;
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}
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talk_set_status("listening ...");
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{
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std::unique_lock<std::mutex> lock(g_mutex);
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if (g_pcmf32.size() < step_samples) {
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lock.unlock();
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std::this_thread::sleep_for(std::chrono::milliseconds(10));
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continue;
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}
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pcmf32 = std::vector<float>(g_pcmf32.end() - std::min((int64_t) g_pcmf32.size(), window_samples), g_pcmf32.end());
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}
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// VAD: if energy in during last second is above threshold, then skip
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{
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float energy_all = 0.0f;
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float energy_1s = 0.0f;
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for (size_t i = 0; i < pcmf32.size(); i++) {
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energy_all += fabsf(pcmf32[i]);
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if (i >= pcmf32.size() - WHISPER_SAMPLE_RATE) {
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energy_1s += fabsf(pcmf32[i]);
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}
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}
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energy_all /= pcmf32.size();
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energy_1s /= WHISPER_SAMPLE_RATE;
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if (energy_1s > 0.1f*energy_all && !g_force_speak) {
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std::this_thread::sleep_for(std::chrono::milliseconds(10));
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continue;
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}
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}
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talk_set_status("processing audio (whisper)...");
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t_last = t_now;
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if (!g_force_speak) {
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const auto t_start = std::chrono::high_resolution_clock::now();
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int ret = whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size());
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if (ret != 0) {
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printf("whisper_full() failed: %d\n", ret);
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break;
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}
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const auto t_end = std::chrono::high_resolution_clock::now();
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printf("whisper_full() returned %d in %f seconds\n", ret, std::chrono::duration<double>(t_end - t_start).count());
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}
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{
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std::string text_heard;
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if (!g_force_speak) {
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const int n_segments = whisper_full_n_segments(ctx);
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for (int i = n_segments - 1; i < n_segments; ++i) {
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const char * text = whisper_full_get_segment_text(ctx, i);
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const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
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const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
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printf ("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text);
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text_heard += text;
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}
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}
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g_force_speak = false;
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// remove text between brackets using regex
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{
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std::regex re("\\[.*?\\]");
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text_heard = std::regex_replace(text_heard, re, "");
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}
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// remove text between brackets using regex
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{
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std::regex re("\\(.*?\\)");
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text_heard = std::regex_replace(text_heard, re, "");
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}
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// remove all characters, except for letters, numbers, punctuation and ':', '\'', '-', ' '
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text_heard = std::regex_replace(text_heard, std::regex("[^a-zA-Z0-9\\.,\\?!\\s\\:\\'\\-]"), "");
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// take first line
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text_heard = text_heard.substr(0, text_heard.find_first_of("\n"));
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// remove leading and trailing whitespace
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text_heard = std::regex_replace(text_heard, std::regex("^\\s+"), "");
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text_heard = std::regex_replace(text_heard, std::regex("\\s+$"), "");
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talk_set_status("'" + text_heard + "' - thinking how to respond (gpt-2) ...");
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const std::vector<gpt_vocab::id> tokens = gpt2_tokenize(g_gpt2, text_heard.c_str());
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printf("whisper: number of tokens: %d, '%s'\n", (int) tokens.size(), text_heard.c_str());
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std::string text_to_speak;
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std::string prompt_base;
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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prompt_base = gpt2_get_prompt(g_gpt2);
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}
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if (tokens.size() > 0) {
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text_to_speak = gpt2_gen_text(g_gpt2, (prompt_base + text_heard + "\n").c_str(), 32);
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text_to_speak = std::regex_replace(text_to_speak, std::regex("[^a-zA-Z0-9\\.,\\?!\\s\\:\\'\\-]"), "");
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text_to_speak = text_to_speak.substr(0, text_to_speak.find_first_of("\n"));
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std::lock_guard<std::mutex> lock(g_mutex);
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// remove first 2 lines of base prompt
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{
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const size_t pos = prompt_base.find_first_of("\n");
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if (pos != std::string::npos) {
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prompt_base = prompt_base.substr(pos + 1);
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}
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}
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{
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const size_t pos = prompt_base.find_first_of("\n");
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if (pos != std::string::npos) {
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prompt_base = prompt_base.substr(pos + 1);
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}
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}
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prompt_base += text_heard + "\n" + text_to_speak + "\n";
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} else {
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text_to_speak = gpt2_gen_text(g_gpt2, prompt_base.c_str(), 32);
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text_to_speak = std::regex_replace(text_to_speak, std::regex("[^a-zA-Z0-9\\.,\\?!\\s\\:\\'\\-]"), "");
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text_to_speak = text_to_speak.substr(0, text_to_speak.find_first_of("\n"));
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std::lock_guard<std::mutex> lock(g_mutex);
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const size_t pos = prompt_base.find_first_of("\n");
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if (pos != std::string::npos) {
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prompt_base = prompt_base.substr(pos + 1);
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}
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prompt_base += text_to_speak + "\n";
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}
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printf("gpt-2: %s\n", text_to_speak.c_str());
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//printf("========================\n");
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//printf("gpt-2: prompt_base:\n'%s'\n", prompt_base.c_str());
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//printf("========================\n");
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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t_last = std::chrono::high_resolution_clock::now();
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g_text_to_speak = text_to_speak;
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g_pcmf32.clear();
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gpt2_set_prompt(g_gpt2, prompt_base.c_str());
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}
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talk_set_status("speaking ...");
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}
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}
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gpt2_free(g_gpt2);
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if (index < g_contexts.size()) {
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whisper_free(g_contexts[index]);
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g_contexts[index] = nullptr;
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}
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}
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EMSCRIPTEN_BINDINGS(talk) {
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emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
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for (size_t i = 0; i < g_contexts.size(); ++i) {
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if (g_contexts[i] == nullptr) {
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g_contexts[i] = whisper_init_from_file(path_model.c_str());
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if (g_contexts[i] != nullptr) {
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g_running = true;
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if (g_worker.joinable()) {
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g_worker.join();
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}
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g_worker = std::thread([i]() {
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talk_main(i);
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});
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return i + 1;
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} else {
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return (size_t) 0;
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}
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}
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}
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return (size_t) 0;
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}));
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emscripten::function("free", emscripten::optional_override([](size_t index) {
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if (g_running) {
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g_running = false;
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}
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}));
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emscripten::function("set_audio", emscripten::optional_override([](size_t index, const emscripten::val & audio) {
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--index;
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if (index >= g_contexts.size()) {
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return -1;
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}
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if (g_contexts[index] == nullptr) {
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return -2;
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}
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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const int n = audio["length"].as<int>();
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emscripten::val heap = emscripten::val::module_property("HEAPU8");
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emscripten::val memory = heap["buffer"];
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g_pcmf32.resize(n);
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emscripten::val memoryView = audio["constructor"].new_(memory, reinterpret_cast<uintptr_t>(g_pcmf32.data()), n);
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memoryView.call<void>("set", audio);
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}
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return 0;
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}));
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emscripten::function("force_speak", emscripten::optional_override([](size_t index) {
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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g_force_speak = true;
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}
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}));
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emscripten::function("get_text_context", emscripten::optional_override([]() {
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std::string text_context;
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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text_context = gpt2_get_prompt(g_gpt2);
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}
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return text_context;
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}));
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emscripten::function("get_text_to_speak", emscripten::optional_override([]() {
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std::string text_to_speak;
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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text_to_speak = std::move(g_text_to_speak);
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}
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return text_to_speak;
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}));
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emscripten::function("get_status", emscripten::optional_override([]() {
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std::string status;
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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status = g_status_forced.empty() ? g_status : g_status_forced;
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}
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return status;
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}));
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emscripten::function("set_status", emscripten::optional_override([](const std::string & status) {
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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g_status_forced = status;
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}
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}));
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emscripten::function("set_prompt", emscripten::optional_override([](const std::string & prompt) {
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{
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std::lock_guard<std::mutex> lock(g_mutex);
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gpt2_set_prompt(g_gpt2, prompt.c_str());
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}
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}));
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}
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