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| 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 speed_up = false; | |
| bool translate = false; | |
| bool print_special = false; | |
| bool print_energy = false; | |
| bool use_gpu = true; | |
| std::string language = "en"; | |
| std::string model = "models/ggml-base.en.bin"; | |
| }; | |
| struct command { | |
| std::vector<whisper_token> tokens; | |
| std::string plaintext; | |
| }; | |
| struct commandset { | |
| std::vector<struct command> commands; | |
| std::vector<whisper_token> 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); | |
| 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 == "-su" || arg == "--speed-up") { params.speed_up = true; } | |
| 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 == "-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, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false"); | |
| 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, " -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"); | |
| } | |
| uint64_t wait_for_vad(audio_async & audio, json jparams, const whisper_params & params, uint64_t maxlength_ms, std::vector<float> & pcmf32) { | |
| using namespace std::chrono; | |
| uint64_t time_now = time_point_cast<milliseconds>(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<milliseconds>(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<float> 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<milliseconds>(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; | |
| } | |
| json unguided_transcription(struct whisper_context * ctx, audio_async &audio, json jparams, const whisper_params ¶ms) { | |
| std::vector<whisper_token> prompt_tokens; | |
| std::vector<float> 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.speed_up = params.speed_up; | |
| 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 | |
| json guided_transcription(struct whisper_context * ctx, audio_async &audio, const whisper_params ¶ms, json jparams, std::vector<struct commandset> commandset_list) { | |
| struct commandset cs = commandset_list[jparams.value("commandset_index", commandset_list.size()-1)]; | |
| std::vector<float> 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; | |
| wparams.speed_up = params.speed_up; | |
| // 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<float> 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<std::pair<float, int>> 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}, | |
| }; | |
| } | |
| } | |
| json register_commandset(struct whisper_context * ctx, json jparams, std::vector<struct commandset> &commandset_list) { | |
| // TODO: check for token collision | |
| struct commandset cs; | |
| std::string k_prompt = " select one from the available words: "; | |
| std::set<whisper_token> token_set; | |
| whisper_token tokens[32]; | |
| for (std::string s : jparams) { | |
| std::vector<whisper_token> 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}}; | |
| } | |
| 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."} | |
| }; | |
| } | |
| json parse_job(const json &body, struct whisper_context * ctx, audio_async &audio, const whisper_params ¶ms, std::vector<struct commandset> &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} | |
| }; | |
| } | |
| } | |
| void process_loop(struct whisper_context * ctx, audio_async &audio, const whisper_params ¶ms) { | |
| std::deque<json> jobqueue; | |
| std::vector<struct commandset> 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; | |
| 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; | |
| } | |