#include "common.h" #include "common-sdl.h" #include "whisper.h" #include "json.hpp" #include #include #include #include #include #include #include #include using json = nlohmann::json; // command-line parameters struct whisper_params { int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency()); int32_t prompt_ms = 5000; int32_t command_ms = 8000; int32_t capture_id = -1; int32_t max_tokens = 32; int32_t audio_ctx = 0; float vad_thold = 0.6f; float freq_thold = 100.0f; bool translate = false; bool print_special = false; bool print_energy = false; bool use_gpu = true; bool flash_attn = false; std::string language = "en"; std::string model = "models/ggml-base.en.bin"; }; struct command { std::vector tokens; std::string plaintext; }; struct commandset { std::vector commands; std::vector prompt_tokens; // TODO: Store longest command? // Multi-token commands should have probabilities of subsequent logits // given that the prior logit is correct. // In this case, all commands must be iterated. // This however, is likely highly involved as different tokens // almost certainly have different spoken lengths // It would also have performance implications equivalent to a beam search }; void whisper_print_usage(int argc, char ** argv, const whisper_params & params); static bool whisper_params_parse(int argc, char ** argv, whisper_params & params) { for (int i = 1; i < argc; i++) { std::string arg = argv[i]; if (arg == "-h" || arg == "--help") { whisper_print_usage(argc, argv, params); exit(0); } else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); } else if (arg == "-pms" || arg == "--prompt-ms") { params.prompt_ms = std::stoi(argv[++i]); } else if (arg == "-cms" || arg == "--command-ms") { params.command_ms = std::stoi(argv[++i]); } else if (arg == "-c" || arg == "--capture") { params.capture_id = std::stoi(argv[++i]); } else if (arg == "-mt" || arg == "--max-tokens") { params.max_tokens = std::stoi(argv[++i]); } else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); } else if (arg == "-vth" || arg == "--vad-thold") { params.vad_thold = std::stof(argv[++i]); } else if (arg == "-fth" || arg == "--freq-thold") { params.freq_thold = std::stof(argv[++i]); } else if (arg == "-tr" || arg == "--translate") { params.translate = true; } else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; } else if (arg == "-pe" || arg == "--print-energy") { params.print_energy = true; } else if (arg == "-ng" || arg == "--no-gpu") { params.use_gpu = false; } else if (arg == "-fa" || arg == "--flash-attn") { params.flash_attn = true; } else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; } else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; } else { fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); whisper_print_usage(argc, argv, params); exit(0); } } return true; } void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & params) { fprintf(stderr, "\n"); fprintf(stderr, "usage: %s [options]\n", argv[0]); fprintf(stderr, "\n"); fprintf(stderr, "options:\n"); fprintf(stderr, " -h, --help [default] show this help message and exit\n"); fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads); fprintf(stderr, " -pms N, --prompt-ms N [%-7d] prompt duration in milliseconds\n", params.prompt_ms); fprintf(stderr, " -cms N, --command-ms N [%-7d] command duration in milliseconds\n", params.command_ms); fprintf(stderr, " -c ID, --capture ID [%-7d] capture device ID\n", params.capture_id); fprintf(stderr, " -mt N, --max-tokens N [%-7d] maximum number of tokens per audio chunk\n", params.max_tokens); fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx); fprintf(stderr, " -vth N, --vad-thold N [%-7.2f] voice activity detection threshold\n", params.vad_thold); fprintf(stderr, " -fth N, --freq-thold N [%-7.2f] high-pass frequency cutoff\n", params.freq_thold); fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false"); fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false"); fprintf(stderr, " -pe, --print-energy [%-7s] print sound energy (for debugging)\n", params.print_energy ? "true" : "false"); fprintf(stderr, " -ng, --no-gpu [%-7s] disable GPU\n", params.use_gpu ? "false" : "true"); fprintf(stderr, " -fa, --flash-attn [%-7s] flash attention\n", params.flash_attn ? "true" : "false"); fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str()); fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str()); fprintf(stderr, "\n"); } static uint64_t wait_for_vad(audio_async & audio, json jparams, const whisper_params & params, uint64_t maxlength_ms, std::vector & pcmf32) { using namespace std::chrono; uint64_t time_now = time_point_cast(system_clock::now()).time_since_epoch().count(); uint64_t start_time = time_now; if (jparams.contains("timestamp")) { start_time = jparams.at("timestamp"); } if(time_now - start_time < 500) { //wait for a backlog of audio std::this_thread::sleep_for(milliseconds(500 - (time_now - start_time))); time_now = time_point_cast(system_clock::now()).time_since_epoch().count(); } else if (time_now - start_time > 1000) { audio.get(time_now-start_time, pcmf32); size_t max_offset = pcmf32.size() - WHISPER_SAMPLE_RATE; for(size_t offset=0;offset < max_offset;offset+=WHISPER_SAMPLE_RATE/10) { std::vector audio_chunk(&pcmf32[offset], &pcmf32[offset+WHISPER_SAMPLE_RATE]); if(::vad_simple(audio_chunk, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) { pcmf32.resize(offset+WHISPER_SAMPLE_RATE); if (offset*1000/WHISPER_SAMPLE_RATE+1000 > maxlength_ms) { //remove samples from the beginning pcmf32.erase(pcmf32.begin(),pcmf32.end()-(maxlength_ms*WHISPER_SAMPLE_RATE/1000)); fprintf(stderr, "Shortened samples"); } return start_time + offset*1000/WHISPER_SAMPLE_RATE+1000; } } } size_t window_duration = std::max((uint64_t)1000, time_now-start_time); audio.get(window_duration, pcmf32); while (!::vad_simple(pcmf32, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) { std::this_thread::sleep_for(milliseconds(100)); time_now = time_point_cast(system_clock::now()).time_since_epoch().count(); window_duration = std::max((uint64_t)1000,time_now-start_time); audio.get(window_duration, pcmf32); } if (time_now - start_time > maxlength_ms) { audio.get(maxlength_ms, pcmf32); } else { audio.get(time_now - start_time, pcmf32); } return time_now; } static json unguided_transcription(struct whisper_context * ctx, audio_async &audio, json jparams, const whisper_params ¶ms) { std::vector prompt_tokens; std::vector pcmf32; uint64_t unprocessed_audio_timestamp = wait_for_vad(audio, jparams, params, 10000U, pcmf32); whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY); if (jparams.contains("prompt")) { // unlikely to see much use. Under normal circumstances, no_context would be set to false std::string prompt = jparams.at("prompt"); prompt_tokens.resize(1024); int n = whisper_tokenize(ctx, prompt.c_str(), prompt_tokens.data(), 1024); prompt_tokens.resize(n); wparams.prompt_tokens = prompt_tokens.data(); wparams.prompt_n_tokens = prompt_tokens.size(); } wparams.print_progress = false; wparams.print_special = params.print_special; wparams.print_realtime = false; wparams.print_timestamps = false; wparams.translate = params.translate; wparams.no_context = jparams.value("no_context", true); wparams.single_segment = true; wparams.max_tokens = params.max_tokens; wparams.language = params.language.c_str(); wparams.n_threads = params.n_threads; wparams.audio_ctx = params.audio_ctx; wparams.suppress_non_speech_tokens = true; // run the transformer and a single decoding pass if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) { fprintf(stderr, "%s: ERROR: whisper_full() failed\n", __func__); throw json{ {"code", -32803}, {"message", "ERROR: whisper_full() failed"} }; } std::string result = whisper_full_get_segment_text(ctx,0); return json { {"transcription", result}, {"timestamp", unprocessed_audio_timestamp} }; } // command-list mode // guide the transcription to match the most likely command from a provided list static json guided_transcription(struct whisper_context * ctx, audio_async &audio, const whisper_params ¶ms, json jparams, std::vector commandset_list) { struct commandset cs = commandset_list[jparams.value("commandset_index", commandset_list.size()-1)]; std::vector pcmf32; uint64_t unprocessed_audio_timestamp = wait_for_vad(audio, jparams, params, 2000U, pcmf32); fprintf(stderr, "%s: Speech detected! Processing ...\n", __func__); whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY); wparams.print_progress = false; wparams.print_special = params.print_special; wparams.print_realtime = false; wparams.print_timestamps = false; wparams.translate = params.translate; wparams.no_context = true; wparams.single_segment = true; wparams.max_tokens = 1; wparams.language = params.language.c_str(); wparams.n_threads = params.n_threads; wparams.audio_ctx = params.audio_ctx; // TODO: Do some time testing. Does an overly long prompt slow down processing? // Set up command sets/precompute prompts wparams.prompt_tokens = cs.prompt_tokens.data(); wparams.prompt_n_tokens = cs.prompt_tokens.size(); // TODO: properly expose as option wparams.suppress_non_speech_tokens = true; // run the transformer and a single decoding pass if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) { fprintf(stderr, "%s: ERROR: whisper_full() failed\n", __func__); throw json{ {"code", -32803}, {"message", "ERROR: whisper_full() failed"}//TODO: format string (sprintf?) }; } // estimate command probability // NOTE: not optimal { const auto * logits = whisper_get_logits(ctx); std::vector probs(whisper_n_vocab(ctx), 0.0f); // compute probs from logits via softmax { float max = -1e9; for (int i = 0; i < (int) probs.size(); ++i) { max = std::max(max, logits[i]); } float sum = 0.0f; for (int i = 0; i < (int) probs.size(); ++i) { probs[i] = expf(logits[i] - max); sum += probs[i]; } for (int i = 0; i < (int) probs.size(); ++i) { probs[i] /= sum; } } std::vector> probs_id; // In my testing, the most verbose token is always the desired. // TODO: Trim commandset struct once efficacy has been verified for (int i = 0; i < (int) cs.commands.size(); ++i) { probs_id.emplace_back(probs[cs.commands[i].tokens[0]], i); } // sort descending { using pair_type = decltype(probs_id)::value_type; std::sort(probs_id.begin(), probs_id.end(), [](const pair_type & a, const pair_type & b) { return a.first > b.first; }); } int id = probs_id[0].second; return json{ {"command_index", id}, {"command_text", cs.commands[id].plaintext}, {"timestamp", unprocessed_audio_timestamp}, }; } } static json register_commandset(struct whisper_context * ctx, json jparams, std::vector &commandset_list) { // TODO: check for token collision struct commandset cs; std::string k_prompt = " select one from the available words: "; std::set token_set; whisper_token tokens[32]; for (std::string s : jparams) { std::vector token_vec; // The existing command implementation uses a nested for loop to tokenize single characters // I fail to see the purpose of this when ' a' has a wholly different pronunciation than the start of ' apple' const int n = whisper_tokenize(ctx, (" " + s).c_str(), tokens, 32); if (n < 0) { fprintf(stderr, "%s: error: failed to tokenize command '%s'\n", __func__, s.c_str()); return 3; } token_vec.push_back(tokens[0]); if (!token_set.insert(tokens[0]).second) { fprintf(stderr, "%s: warning: %s is a duplicate of an existing token\n", __func__, s.c_str()); throw json{ {"code",-31000}, {"message", "Duplicate token in token set: " + s} }; } if (n > 1) {// empty string if n=0? Should never occur fprintf(stderr, "%s: error: command is more than a single token: %s\n", __func__, s.c_str()); } struct command command = {token_vec, s}; cs.commands.push_back(command); k_prompt += s; } k_prompt = k_prompt.substr(0,k_prompt.length()-2) + ". Selected word:"; cs.prompt_tokens.resize(1024); int n = whisper_tokenize(ctx, k_prompt.c_str(), cs.prompt_tokens.data(), 1024); cs.prompt_tokens.resize(n); // prepare response int index = commandset_list.size(); commandset_list.push_back(cs); return json{{"index",index}}; } static json seek(struct whisper_context * /*ctx*/, audio_async & /*audio*/, json /*params*/) { // whisper_state has the pertinent offsets, but there also seem to be a large // number of scratch buffers that would prevent rewinding context in a manner similar to llama // I'll give this a another pass once everything else is implemented, // but for now, it's unsupported throw json { {"code", -32601}, {"message", "Seeking is not yet supported."} }; } static json parse_job(const json &body, struct whisper_context * ctx, audio_async &audio, const whisper_params ¶ms, std::vector &commandset_list) { // See: https://www.jsonrpc.org/specification json id = body.at("id"); try { std::string version = body.at("jsonrpc"); if (version != "2.0") { // unsupported version throw json{ {"code", -3260}, {"message", "invalid jsonrpc version"} }; } std::string method = body.at("method"); json jparams = json{{"dummy", "dummy"}}; if (body.contains("params")) jparams = body.at("params"); json res; // TODO: be consistent about argument order fprintf(stderr, "Dispatching a job\n"); if (method == "unguided") { res = unguided_transcription(ctx, audio, jparams, params); } else if (method == "guided") { res = guided_transcription(ctx, audio, params, jparams, commandset_list); } else if (method == "seek") { res = seek(ctx, audio, jparams); } else if (method == "registerCommandset") { res = register_commandset(ctx, jparams, commandset_list); } else if (method == "echo") { res = jparams; } return json{ {"jsonrpc", "2.0"}, {"result", res}, {"id", id} }; } catch(json ex) { return json { {"jsonrpc", "2.0"}, {"error", ex}, {"id", id} }; } } static void process_loop(struct whisper_context * ctx, audio_async &audio, const whisper_params ¶ms) { std::deque jobqueue; std::vector commandset_list; while (true) { // For eventual cancellation support, shouldn't block if job exists if (std::cin.rdbuf()->in_avail() > 22 || jobqueue.size() == 0) { int content_length; if (scanf("Content-Length: %d", &content_length) != 1) { fprintf(stderr, "Could not read input: %d", std::cin.peek()); return; } // scanf leaves the new lines intact std::cin.ignore(2); if (std::cin.peek() != 13) { // Content-Type. jsonrpc necessitates utf8. std::cin.ignore(200,10); } std::cin.ignore(2); // A message is being sent and blocking is acceptable std::string content(content_length,'\0'); std::cin.read(&content[0], content_length); json job = json::parse(content); // TODO: Some messages(cancellation) should skip queue here if (job.is_array()) { // response must also be batched. Will implement later // for (subjob : job.begin()) // TODO: At the very least respond with an unsupported error. } else { jobqueue.push_back(job); } } assert(jobqueue.size() > 0); json job = jobqueue.front(); json resp = parse_job(job, ctx, audio, params, commandset_list); if (resp != "unfinished") { jobqueue.pop_front(); // send response std::string data = resp.dump(-1, ' ', false, json::error_handler_t::replace); fprintf(stdout, "Content-Length: %d\r\n\r\n%s\n", (int)data.length()+1, data.c_str()); std::cout.flush(); } } } int main(int argc, char ** argv) { whisper_params params; if (whisper_params_parse(argc, argv, params) == false) { return 1; } if (whisper_lang_id(params.language.c_str()) == -1) { fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str()); whisper_print_usage(argc, argv, params); exit(0); } // whisper init struct whisper_context_params cparams = whisper_context_default_params(); cparams.use_gpu = params.use_gpu; cparams.flash_attn = params.flash_attn; struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams); // init audio audio_async audio(30*1000); if (!audio.init(params.capture_id, WHISPER_SAMPLE_RATE)) { fprintf(stderr, "%s: audio.init() failed!\n", __func__); return 1; } audio.resume(); // TODO: Investigate why this is required. An extra second of startup latency is not great // wait for 1 second to avoid any buffered noise std::this_thread::sleep_for(std::chrono::milliseconds(1000)); audio.clear(); // TODO: consider some sort of indicator to designate loading has finished? // Potentially better for the client to just start with a non-blocking message (register commands) process_loop(ctx, audio, params); audio.pause(); whisper_print_timings(ctx); whisper_free(ctx); return 0; }