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| using namespace httplib; | |
| using json = nlohmann::ordered_json; | |
| enum server_state { | |
| SERVER_STATE_LOADING_MODEL, // Server is starting up, model not fully loaded yet | |
| SERVER_STATE_READY, // Server is ready and model is loaded | |
| }; | |
| namespace { | |
| // output formats | |
| const std::string json_format = "json"; | |
| const std::string text_format = "text"; | |
| const std::string srt_format = "srt"; | |
| const std::string vjson_format = "verbose_json"; | |
| const std::string vtt_format = "vtt"; | |
| std::function<void(int)> shutdown_handler; | |
| std::atomic_flag is_terminating = ATOMIC_FLAG_INIT; | |
| inline void signal_handler(int signal) { | |
| if (is_terminating.test_and_set()) { | |
| // in case it hangs, we can force terminate the server by hitting Ctrl+C twice | |
| // this is for better developer experience, we can remove when the server is stable enough | |
| fprintf(stderr, "Received second interrupt, terminating immediately.\n"); | |
| exit(1); | |
| } | |
| shutdown_handler(signal); | |
| } | |
| struct server_params | |
| { | |
| std::string hostname = "127.0.0.1"; | |
| std::string public_path = "examples/server/public"; | |
| std::string request_path = ""; | |
| std::string inference_path = "/inference"; | |
| int32_t port = 8080; | |
| int32_t read_timeout = 600; | |
| int32_t write_timeout = 600; | |
| bool ffmpeg_converter = false; | |
| }; | |
| struct whisper_params { | |
| int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency()); | |
| int32_t n_processors = 1; | |
| int32_t offset_t_ms = 0; | |
| int32_t offset_n = 0; | |
| int32_t duration_ms = 0; | |
| int32_t progress_step = 5; | |
| int32_t max_context = -1; | |
| int32_t max_len = 0; | |
| int32_t best_of = 2; | |
| int32_t beam_size = -1; | |
| int32_t audio_ctx = 0; | |
| float word_thold = 0.01f; | |
| float entropy_thold = 2.40f; | |
| float logprob_thold = -1.00f; | |
| float temperature = 0.00f; | |
| float temperature_inc = 0.20f; | |
| float no_speech_thold = 0.6f; | |
| bool debug_mode = false; | |
| bool translate = false; | |
| bool detect_language = false; | |
| bool diarize = false; | |
| bool tinydiarize = false; | |
| bool split_on_word = false; | |
| bool no_fallback = false; | |
| bool print_special = false; | |
| bool print_colors = false; | |
| bool print_realtime = false; | |
| bool print_progress = false; | |
| bool no_timestamps = false; | |
| bool use_gpu = true; | |
| bool flash_attn = false; | |
| bool suppress_nst = false; | |
| bool no_context = false; | |
| bool no_language_probabilities = false; | |
| std::string language = "en"; | |
| std::string prompt = ""; | |
| std::string font_path = "/System/Library/Fonts/Supplemental/Courier New Bold.ttf"; | |
| std::string model = "models/ggml-base.en.bin"; | |
| std::string response_format = json_format; | |
| // [TDRZ] speaker turn string | |
| std::string tdrz_speaker_turn = " [SPEAKER_TURN]"; // TODO: set from command line | |
| std::string openvino_encode_device = "CPU"; | |
| std::string dtw = ""; | |
| // Voice Activity Detection (VAD) parameters | |
| bool vad = false; | |
| std::string vad_model = ""; | |
| float vad_threshold = 0.5f; | |
| int vad_min_speech_duration_ms = 250; | |
| int vad_min_silence_duration_ms = 100; | |
| float vad_max_speech_duration_s = FLT_MAX; | |
| int vad_speech_pad_ms = 30; | |
| float vad_samples_overlap = 0.1f; | |
| }; | |
| void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & params, const server_params& sparams) { | |
| 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, " -p N, --processors N [%-7d] number of processors to use during computation\n", params.n_processors); | |
| fprintf(stderr, " -ot N, --offset-t N [%-7d] time offset in milliseconds\n", params.offset_t_ms); | |
| fprintf(stderr, " -on N, --offset-n N [%-7d] segment index offset\n", params.offset_n); | |
| fprintf(stderr, " -d N, --duration N [%-7d] duration of audio to process in milliseconds\n", params.duration_ms); | |
| fprintf(stderr, " -mc N, --max-context N [%-7d] maximum number of text context tokens to store\n", params.max_context); | |
| fprintf(stderr, " -ml N, --max-len N [%-7d] maximum segment length in characters\n", params.max_len); | |
| fprintf(stderr, " -sow, --split-on-word [%-7s] split on word rather than on token\n", params.split_on_word ? "true" : "false"); | |
| fprintf(stderr, " -bo N, --best-of N [%-7d] number of best candidates to keep\n", params.best_of); | |
| fprintf(stderr, " -bs N, --beam-size N [%-7d] beam size for beam search\n", params.beam_size); | |
| fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx); | |
| fprintf(stderr, " -wt N, --word-thold N [%-7.2f] word timestamp probability threshold\n", params.word_thold); | |
| fprintf(stderr, " -et N, --entropy-thold N [%-7.2f] entropy threshold for decoder fail\n", params.entropy_thold); | |
| fprintf(stderr, " -lpt N, --logprob-thold N [%-7.2f] log probability threshold for decoder fail\n", params.logprob_thold); | |
| fprintf(stderr, " -debug, --debug-mode [%-7s] enable debug mode (eg. dump log_mel)\n", params.debug_mode ? "true" : "false"); | |
| fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false"); | |
| fprintf(stderr, " -di, --diarize [%-7s] stereo audio diarization\n", params.diarize ? "true" : "false"); | |
| fprintf(stderr, " -tdrz, --tinydiarize [%-7s] enable tinydiarize (requires a tdrz model)\n", params.tinydiarize ? "true" : "false"); | |
| fprintf(stderr, " -nf, --no-fallback [%-7s] do not use temperature fallback while decoding\n", params.no_fallback ? "true" : "false"); | |
| fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false"); | |
| fprintf(stderr, " -pc, --print-colors [%-7s] print colors\n", params.print_colors ? "true" : "false"); | |
| fprintf(stderr, " -pr, --print-realtime [%-7s] print output in realtime\n", params.print_realtime ? "true" : "false"); | |
| fprintf(stderr, " -pp, --print-progress [%-7s] print progress\n", params.print_progress ? "true" : "false"); | |
| fprintf(stderr, " -nt, --no-timestamps [%-7s] do not print timestamps\n", params.no_timestamps ? "true" : "false"); | |
| fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language ('auto' for auto-detect)\n", params.language.c_str()); | |
| fprintf(stderr, " -dl, --detect-language [%-7s] exit after automatically detecting language\n", params.detect_language ? "true" : "false"); | |
| fprintf(stderr, " --prompt PROMPT [%-7s] initial prompt\n", params.prompt.c_str()); | |
| fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str()); | |
| fprintf(stderr, " -oved D, --ov-e-device DNAME [%-7s] the OpenVINO device used for encode inference\n", params.openvino_encode_device.c_str()); | |
| // server params | |
| fprintf(stderr, " -dtw MODEL --dtw MODEL [%-7s] compute token-level timestamps\n", params.dtw.c_str()); | |
| fprintf(stderr, " --host HOST, [%-7s] Hostname/ip-adress for the server\n", sparams.hostname.c_str()); | |
| fprintf(stderr, " --port PORT, [%-7d] Port number for the server\n", sparams.port); | |
| fprintf(stderr, " --public PATH, [%-7s] Path to the public folder\n", sparams.public_path.c_str()); | |
| fprintf(stderr, " --request-path PATH, [%-7s] Request path for all requests\n", sparams.request_path.c_str()); | |
| fprintf(stderr, " --inference-path PATH, [%-7s] Inference path for all requests\n", sparams.inference_path.c_str()); | |
| fprintf(stderr, " --convert, [%-7s] Convert audio to WAV, requires ffmpeg on the server\n", sparams.ffmpeg_converter ? "true" : "false"); | |
| fprintf(stderr, " -sns, --suppress-nst [%-7s] suppress non-speech tokens\n", params.suppress_nst ? "true" : "false"); | |
| fprintf(stderr, " -nth N, --no-speech-thold N [%-7.2f] no speech threshold\n", params.no_speech_thold); | |
| fprintf(stderr, " -nc, --no-context [%-7s] do not use previous audio context\n", params.no_context ? "true" : "false"); | |
| fprintf(stderr, " -ng, --no-gpu [%-7s] do not use gpu\n", params.use_gpu ? "false" : "true"); | |
| fprintf(stderr, " -fa, --flash-attn [%-7s] flash attention\n", params.flash_attn ? "true" : "false"); | |
| fprintf(stderr, " -nlp, --no-language-probabilities [%-7s] exclude language probabilities from verbose_json output\n", params.no_language_probabilities ? "true" : "false"); | |
| // Voice Activity Detection (VAD) parameters | |
| fprintf(stderr, "\nVoice Activity Detection (VAD) options:\n"); | |
| fprintf(stderr, " --vad [%-7s] enable Voice Activity Detection (VAD)\n", params.vad ? "true" : "false"); | |
| fprintf(stderr, " -vm FNAME, --vad-model FNAME [%-7s] VAD model path\n", params.vad_model.c_str()); | |
| fprintf(stderr, " -vt N, --vad-threshold N [%-7.2f] VAD threshold for speech recognition\n", params.vad_threshold); | |
| fprintf(stderr, " -vspd N, --vad-min-speech-duration-ms N [%-7d] VAD min speech duration (0.0-1.0)\n", params.vad_min_speech_duration_ms); | |
| fprintf(stderr, " -vsd N, --vad-min-silence-duration-ms N [%-7d] VAD min silence duration (to split segments)\n", params.vad_min_silence_duration_ms); | |
| fprintf(stderr, " -vmsd N, --vad-max-speech-duration-s N [%-7s] VAD max speech duration (auto-split longer)\n", params.vad_max_speech_duration_s == FLT_MAX ? | |
| std::string("FLT_MAX").c_str() : | |
| std::to_string(params.vad_max_speech_duration_s).c_str()); | |
| fprintf(stderr, " -vp N, --vad-speech-pad-ms N [%-7d] VAD speech padding (extend segments)\n", params.vad_speech_pad_ms); | |
| fprintf(stderr, " -vo N, --vad-samples-overlap N [%-7.2f] VAD samples overlap (seconds between segments)\n", params.vad_samples_overlap); | |
| fprintf(stderr, "\n"); | |
| } | |
| bool whisper_params_parse(int argc, char ** argv, whisper_params & params, server_params & sparams) { | |
| for (int i = 1; i < argc; i++) { | |
| std::string arg = argv[i]; | |
| if (arg == "-h" || arg == "--help") { | |
| whisper_print_usage(argc, argv, params, sparams); | |
| exit(0); | |
| } | |
| else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); } | |
| else if (arg == "-p" || arg == "--processors") { params.n_processors = std::stoi(argv[++i]); } | |
| else if (arg == "-ot" || arg == "--offset-t") { params.offset_t_ms = std::stoi(argv[++i]); } | |
| else if (arg == "-on" || arg == "--offset-n") { params.offset_n = std::stoi(argv[++i]); } | |
| else if (arg == "-d" || arg == "--duration") { params.duration_ms = std::stoi(argv[++i]); } | |
| else if (arg == "-mc" || arg == "--max-context") { params.max_context = std::stoi(argv[++i]); } | |
| else if (arg == "-ml" || arg == "--max-len") { params.max_len = std::stoi(argv[++i]); } | |
| else if (arg == "-bo" || arg == "--best-of") { params.best_of = std::stoi(argv[++i]); } | |
| else if (arg == "-bs" || arg == "--beam-size") { params.beam_size = std::stoi(argv[++i]); } | |
| else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); } | |
| else if (arg == "-wt" || arg == "--word-thold") { params.word_thold = std::stof(argv[++i]); } | |
| else if (arg == "-et" || arg == "--entropy-thold") { params.entropy_thold = std::stof(argv[++i]); } | |
| else if (arg == "-lpt" || arg == "--logprob-thold") { params.logprob_thold = std::stof(argv[++i]); } | |
| else if (arg == "-debug"|| arg == "--debug-mode") { params.debug_mode = true; } | |
| else if (arg == "-tr" || arg == "--translate") { params.translate = true; } | |
| else if (arg == "-di" || arg == "--diarize") { params.diarize = true; } | |
| else if (arg == "-tdrz" || arg == "--tinydiarize") { params.tinydiarize = true; } | |
| else if (arg == "-sow" || arg == "--split-on-word") { params.split_on_word = true; } | |
| else if (arg == "-nf" || arg == "--no-fallback") { params.no_fallback = true; } | |
| else if (arg == "-fp" || arg == "--font-path") { params.font_path = argv[++i]; } | |
| else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; } | |
| else if (arg == "-pc" || arg == "--print-colors") { params.print_colors = true; } | |
| else if (arg == "-pr" || arg == "--print-realtime") { params.print_realtime = true; } | |
| else if (arg == "-pp" || arg == "--print-progress") { params.print_progress = true; } | |
| else if (arg == "-nt" || arg == "--no-timestamps") { params.no_timestamps = true; } | |
| else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; } | |
| else if (arg == "-dl" || arg == "--detect-language") { params.detect_language = true; } | |
| else if ( arg == "--prompt") { params.prompt = argv[++i]; } | |
| else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; } | |
| else if (arg == "-oved" || arg == "--ov-e-device") { params.openvino_encode_device = argv[++i]; } | |
| else if (arg == "-dtw" || arg == "--dtw") { params.dtw = argv[++i]; } | |
| 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 == "-sns" || arg == "--suppress-nst") { params.suppress_nst = true; } | |
| else if (arg == "-nth" || arg == "--no-speech-thold") { params.no_speech_thold = std::stof(argv[++i]); } | |
| else if (arg == "-nc" || arg == "--no-context") { params.no_context = true; } | |
| else if (arg == "-nlp" || arg == "--no-language-probabilities") { params.no_language_probabilities = true; } | |
| // server params | |
| else if ( arg == "--port") { sparams.port = std::stoi(argv[++i]); } | |
| else if ( arg == "--host") { sparams.hostname = argv[++i]; } | |
| else if ( arg == "--public") { sparams.public_path = argv[++i]; } | |
| else if ( arg == "--request-path") { sparams.request_path = argv[++i]; } | |
| else if ( arg == "--inference-path") { sparams.inference_path = argv[++i]; } | |
| else if ( arg == "--convert") { sparams.ffmpeg_converter = true; } | |
| // Voice Activity Detection (VAD) | |
| else if ( arg == "--vad") { params.vad = true; } | |
| else if (arg == "-vm" || arg == "--vad-model") { params.vad_model = argv[++i]; } | |
| else if (arg == "-vt" || arg == "--vad-threshold") { params.vad_threshold = std::stof(argv[++i]); } | |
| else if (arg == "-vspd" || arg == "--vad-min-speech-duration-ms") { params.vad_min_speech_duration_ms = std::stoi(argv[++i]); } | |
| else if (arg == "-vsd" || arg == "--vad-min-silence-duration-ms") { params.vad_min_speech_duration_ms = std::stoi(argv[++i]); } | |
| else if (arg == "-vmsd" || arg == "--vad-max-speech-duration-s") { params.vad_max_speech_duration_s = std::stof(argv[++i]); } | |
| else if (arg == "-vp" || arg == "--vad-speech-pad-ms") { params.vad_speech_pad_ms = std::stoi(argv[++i]); } | |
| else if (arg == "-vo" || arg == "--vad-samples-overlap") { params.vad_samples_overlap = std::stof(argv[++i]); } | |
| else { | |
| fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); | |
| whisper_print_usage(argc, argv, params, sparams); | |
| exit(0); | |
| } | |
| } | |
| return true; | |
| } | |
| struct whisper_print_user_data { | |
| const whisper_params * params; | |
| const std::vector<std::vector<float>> * pcmf32s; | |
| int progress_prev; | |
| }; | |
| void check_ffmpeg_availibility() { | |
| int result = system("ffmpeg -version"); | |
| if (result == 0) { | |
| std::cout << "ffmpeg is available." << std::endl; | |
| } else { | |
| // ffmpeg is not available | |
| std::cout << "ffmpeg is not found. Please ensure that ffmpeg is installed "; | |
| std::cout << "and that its executable is included in your system's PATH. "; | |
| exit(0); | |
| } | |
| } | |
| std::string generate_temp_filename(const std::string &prefix, const std::string &extension) { | |
| auto now = std::chrono::system_clock::now(); | |
| auto now_time_t = std::chrono::system_clock::to_time_t(now); | |
| static std::mt19937 rng{std::random_device{}()}; | |
| std::uniform_int_distribution<long long> dist(0, 1e9); | |
| std::stringstream ss; | |
| ss << prefix | |
| << "-" | |
| << std::put_time(std::localtime(&now_time_t), "%Y%m%d-%H%M%S") | |
| << "-" | |
| << dist(rng) | |
| << extension; | |
| return ss.str(); | |
| } | |
| bool convert_to_wav(const std::string & temp_filename, std::string & error_resp) { | |
| std::ostringstream cmd_stream; | |
| std::string converted_filename_temp = temp_filename + "_temp.wav"; | |
| cmd_stream << "ffmpeg -i \"" << temp_filename << "\" -y -ar 16000 -ac 1 -c:a pcm_s16le \"" << converted_filename_temp << "\" 2>&1"; | |
| std::string cmd = cmd_stream.str(); | |
| int status = std::system(cmd.c_str()); | |
| if (status != 0) { | |
| error_resp = "{\"error\":\"FFmpeg conversion failed.\"}"; | |
| return false; | |
| } | |
| // Remove the original file | |
| if (remove(temp_filename.c_str()) != 0) { | |
| error_resp = "{\"error\":\"Failed to remove the original file.\"}"; | |
| return false; | |
| } | |
| // Rename the temporary file to match the original filename | |
| if (rename(converted_filename_temp.c_str(), temp_filename.c_str()) != 0) { | |
| error_resp = "{\"error\":\"Failed to rename the temporary file.\"}"; | |
| return false; | |
| } | |
| return true; | |
| } | |
| std::string estimate_diarization_speaker(std::vector<std::vector<float>> pcmf32s, int64_t t0, int64_t t1, bool id_only = false) { | |
| std::string speaker = ""; | |
| const int64_t n_samples = pcmf32s[0].size(); | |
| const int64_t is0 = timestamp_to_sample(t0, n_samples, WHISPER_SAMPLE_RATE); | |
| const int64_t is1 = timestamp_to_sample(t1, n_samples, WHISPER_SAMPLE_RATE); | |
| double energy0 = 0.0f; | |
| double energy1 = 0.0f; | |
| for (int64_t j = is0; j < is1; j++) { | |
| energy0 += fabs(pcmf32s[0][j]); | |
| energy1 += fabs(pcmf32s[1][j]); | |
| } | |
| if (energy0 > 1.1*energy1) { | |
| speaker = "0"; | |
| } else if (energy1 > 1.1*energy0) { | |
| speaker = "1"; | |
| } else { | |
| speaker = "?"; | |
| } | |
| //printf("is0 = %lld, is1 = %lld, energy0 = %f, energy1 = %f, speaker = %s\n", is0, is1, energy0, energy1, speaker.c_str()); | |
| if (!id_only) { | |
| speaker.insert(0, "(speaker "); | |
| speaker.append(")"); | |
| } | |
| return speaker; | |
| } | |
| void whisper_print_progress_callback(struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, int progress, void * user_data) { | |
| int progress_step = ((whisper_print_user_data *) user_data)->params->progress_step; | |
| int * progress_prev = &(((whisper_print_user_data *) user_data)->progress_prev); | |
| if (progress >= *progress_prev + progress_step) { | |
| *progress_prev += progress_step; | |
| fprintf(stderr, "%s: progress = %3d%%\n", __func__, progress); | |
| } | |
| } | |
| void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper_state * /*state*/, int n_new, void * user_data) { | |
| const auto & params = *((whisper_print_user_data *) user_data)->params; | |
| const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s; | |
| const int n_segments = whisper_full_n_segments(ctx); | |
| std::string speaker = ""; | |
| int64_t t0 = 0; | |
| int64_t t1 = 0; | |
| // print the last n_new segments | |
| const int s0 = n_segments - n_new; | |
| if (s0 == 0) { | |
| printf("\n"); | |
| } | |
| for (int i = s0; i < n_segments; i++) { | |
| if (!params.no_timestamps || params.diarize) { | |
| t0 = whisper_full_get_segment_t0(ctx, i); | |
| t1 = whisper_full_get_segment_t1(ctx, i); | |
| } | |
| if (!params.no_timestamps) { | |
| printf("[%s --> %s] ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str()); | |
| } | |
| if (params.diarize && pcmf32s.size() == 2) { | |
| speaker = estimate_diarization_speaker(pcmf32s, t0, t1); | |
| } | |
| if (params.print_colors) { | |
| for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) { | |
| if (params.print_special == false) { | |
| const whisper_token id = whisper_full_get_token_id(ctx, i, j); | |
| if (id >= whisper_token_eot(ctx)) { | |
| continue; | |
| } | |
| } | |
| const char * text = whisper_full_get_token_text(ctx, i, j); | |
| const float p = whisper_full_get_token_p (ctx, i, j); | |
| const int col = std::max(0, std::min((int) k_colors.size() - 1, (int) (std::pow(p, 3)*float(k_colors.size())))); | |
| printf("%s%s%s%s", speaker.c_str(), k_colors[col].c_str(), text, "\033[0m"); | |
| } | |
| } else { | |
| const char * text = whisper_full_get_segment_text(ctx, i); | |
| printf("%s%s", speaker.c_str(), text); | |
| } | |
| if (params.tinydiarize) { | |
| if (whisper_full_get_segment_speaker_turn_next(ctx, i)) { | |
| printf("%s", params.tdrz_speaker_turn.c_str()); | |
| } | |
| } | |
| // with timestamps or speakers: each segment on new line | |
| if (!params.no_timestamps || params.diarize) { | |
| printf("\n"); | |
| } | |
| fflush(stdout); | |
| } | |
| } | |
| std::string output_str(struct whisper_context * ctx, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) { | |
| std::stringstream result; | |
| const int n_segments = whisper_full_n_segments(ctx); | |
| for (int i = 0; i < n_segments; ++i) { | |
| const char * text = whisper_full_get_segment_text(ctx, i); | |
| std::string speaker = ""; | |
| if (params.diarize && pcmf32s.size() == 2) | |
| { | |
| const int64_t t0 = whisper_full_get_segment_t0(ctx, i); | |
| const int64_t t1 = whisper_full_get_segment_t1(ctx, i); | |
| speaker = estimate_diarization_speaker(pcmf32s, t0, t1); | |
| } | |
| result << speaker << text << "\n"; | |
| } | |
| return result.str(); | |
| } | |
| bool parse_str_to_bool(const std::string & s) { | |
| if (s == "true" || s == "1" || s == "yes" || s == "y") { | |
| return true; | |
| } | |
| return false; | |
| } | |
| void get_req_parameters(const Request & req, whisper_params & params) | |
| { | |
| if (req.has_file("offset_t")) | |
| { | |
| params.offset_t_ms = std::stoi(req.get_file_value("offset_t").content); | |
| } | |
| if (req.has_file("offset_n")) | |
| { | |
| params.offset_n = std::stoi(req.get_file_value("offset_n").content); | |
| } | |
| if (req.has_file("duration")) | |
| { | |
| params.duration_ms = std::stoi(req.get_file_value("duration").content); | |
| } | |
| if (req.has_file("max_context")) | |
| { | |
| params.max_context = std::stoi(req.get_file_value("max_context").content); | |
| } | |
| if (req.has_file("max_len")) | |
| { | |
| params.max_len = std::stoi(req.get_file_value("max_len").content); | |
| } | |
| if (req.has_file("best_of")) | |
| { | |
| params.best_of = std::stoi(req.get_file_value("best_of").content); | |
| } | |
| if (req.has_file("beam_size")) | |
| { | |
| params.beam_size = std::stoi(req.get_file_value("beam_size").content); | |
| } | |
| if (req.has_file("audio_ctx")) | |
| { | |
| params.audio_ctx = std::stof(req.get_file_value("audio_ctx").content); | |
| } | |
| if (req.has_file("word_thold")) | |
| { | |
| params.word_thold = std::stof(req.get_file_value("word_thold").content); | |
| } | |
| if (req.has_file("entropy_thold")) | |
| { | |
| params.entropy_thold = std::stof(req.get_file_value("entropy_thold").content); | |
| } | |
| if (req.has_file("logprob_thold")) | |
| { | |
| params.logprob_thold = std::stof(req.get_file_value("logprob_thold").content); | |
| } | |
| if (req.has_file("debug_mode")) | |
| { | |
| params.debug_mode = parse_str_to_bool(req.get_file_value("debug_mode").content); | |
| } | |
| if (req.has_file("translate")) | |
| { | |
| params.translate = parse_str_to_bool(req.get_file_value("translate").content); | |
| } | |
| if (req.has_file("diarize")) | |
| { | |
| params.diarize = parse_str_to_bool(req.get_file_value("diarize").content); | |
| } | |
| if (req.has_file("tinydiarize")) | |
| { | |
| params.tinydiarize = parse_str_to_bool(req.get_file_value("tinydiarize").content); | |
| } | |
| if (req.has_file("split_on_word")) | |
| { | |
| params.split_on_word = parse_str_to_bool(req.get_file_value("split_on_word").content); | |
| } | |
| if (req.has_file("no_timestamps")) | |
| { | |
| params.no_timestamps = parse_str_to_bool(req.get_file_value("no_timestamps").content); | |
| } | |
| if (req.has_file("language")) | |
| { | |
| params.language = req.get_file_value("language").content; | |
| } | |
| if (req.has_file("detect_language")) | |
| { | |
| params.detect_language = parse_str_to_bool(req.get_file_value("detect_language").content); | |
| } | |
| if (req.has_file("prompt")) | |
| { | |
| params.prompt = req.get_file_value("prompt").content; | |
| } | |
| if (req.has_file("response_format")) | |
| { | |
| params.response_format = req.get_file_value("response_format").content; | |
| } | |
| if (req.has_file("temperature")) | |
| { | |
| params.temperature = std::stof(req.get_file_value("temperature").content); | |
| } | |
| if (req.has_file("temperature_inc")) | |
| { | |
| params.temperature_inc = std::stof(req.get_file_value("temperature_inc").content); | |
| } | |
| if (req.has_file("suppress_non_speech")) | |
| { | |
| params.suppress_nst = parse_str_to_bool(req.get_file_value("suppress_non_speech").content); | |
| } | |
| if (req.has_file("suppress_nst")) | |
| { | |
| params.suppress_nst = parse_str_to_bool(req.get_file_value("suppress_nst").content); | |
| } | |
| if (req.has_file("no_context")) | |
| { | |
| params.no_context = parse_str_to_bool(req.get_file_value("no_context").content); | |
| } | |
| if (req.has_file("vad")) | |
| { | |
| params.vad = parse_str_to_bool(req.get_file_value("vad").content); | |
| } | |
| if (req.has_file("vad_threshold")) | |
| { | |
| params.vad_threshold = std::stof(req.get_file_value("vad_threshold").content); | |
| } | |
| if (req.has_file("vad_min_speech_duration_ms")) | |
| { | |
| params.vad_min_speech_duration_ms = std::stof(req.get_file_value("vad_min_speech_duration_ms").content); | |
| } | |
| if (req.has_file("vad_min_silence_duration_ms")) | |
| { | |
| params.vad_min_silence_duration_ms = std::stof(req.get_file_value("vad_min_silence_duration_ms").content); | |
| } | |
| if (req.has_file("vad_max_speech_duration_s")) | |
| { | |
| params.vad_max_speech_duration_s = std::stof(req.get_file_value("vad_max_speech_duration_s").content); | |
| } | |
| if (req.has_file("vad_speech_pad_ms")) | |
| { | |
| params.vad_speech_pad_ms = std::stoi(req.get_file_value("vad_speech_pad_ms").content); | |
| } | |
| if (req.has_file("vad_samples_overlap")) | |
| { | |
| params.vad_samples_overlap = std::stof(req.get_file_value("vad_samples_overlap").content); | |
| } | |
| if (req.has_file("no_language_probabilities")) | |
| { | |
| params.no_language_probabilities = parse_str_to_bool(req.get_file_value("no_language_probabilities").content); | |
| } | |
| } | |
| } // namespace | |
| // Async task management | |
| namespace { | |
| enum class async_status { PENDING, RUNNING, FINISHED, FAILED }; | |
| struct async_task_t { | |
| async_status status = async_status::PENDING; | |
| std::string result; // final response body | |
| std::string content_type = "application/json"; | |
| std::string error; // error message if failed | |
| whisper_params params; // copy of the params used for this task | |
| }; | |
| static std::unordered_map<std::string, async_task_t> tasks; | |
| static std::mutex tasks_mutex; | |
| static std::atomic<uint64_t> task_counter{0}; | |
| std::string generate_task_id() { | |
| const uint64_t id = ++task_counter; | |
| auto now = std::chrono::system_clock::now(); | |
| auto now_ms = std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()).count(); | |
| std::stringstream ss; | |
| ss << id << "-" << now_ms; | |
| return ss.str(); | |
| } | |
| } | |
| int main(int argc, char ** argv) { | |
| ggml_backend_load_all(); | |
| whisper_params params; | |
| server_params sparams; | |
| std::mutex whisper_mutex; | |
| if (whisper_params_parse(argc, argv, params, sparams) == false) { | |
| whisper_print_usage(argc, argv, params, sparams); | |
| return 1; | |
| } | |
| if (params.language != "auto" && 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, sparams); | |
| exit(0); | |
| } | |
| if (params.diarize && params.tinydiarize) { | |
| fprintf(stderr, "error: cannot use both --diarize and --tinydiarize\n"); | |
| whisper_print_usage(argc, argv, params, sparams); | |
| exit(0); | |
| } | |
| if (sparams.ffmpeg_converter) { | |
| check_ffmpeg_availibility(); | |
| } | |
| // whisper init | |
| struct whisper_context_params cparams = whisper_context_default_params(); | |
| cparams.use_gpu = params.use_gpu; | |
| cparams.flash_attn = params.flash_attn; | |
| if (!params.dtw.empty()) { | |
| cparams.dtw_token_timestamps = true; | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_NONE; | |
| if (params.dtw == "tiny") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_TINY; | |
| } | |
| if (params.dtw == "tiny.en") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_TINY_EN; | |
| } | |
| if (params.dtw == "base") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_BASE; | |
| } | |
| if (params.dtw == "base.en") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_BASE_EN; | |
| } | |
| if (params.dtw == "small") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_SMALL; | |
| } | |
| if (params.dtw == "small.en") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_SMALL_EN; | |
| } | |
| if (params.dtw == "medium") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_MEDIUM; | |
| } | |
| if (params.dtw == "medium.en") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_MEDIUM_EN; | |
| } | |
| if (params.dtw == "large.v1") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V1; | |
| } | |
| if (params.dtw == "large.v2") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V2; | |
| } | |
| if (params.dtw == "large.v3") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V3; | |
| } | |
| if (params.dtw == "large.v3.turbo") { | |
| cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V3_TURBO; | |
| } | |
| if (cparams.dtw_aheads_preset == WHISPER_AHEADS_NONE) { | |
| fprintf(stderr, "error: unknown DTW preset '%s'\n", params.dtw.c_str()); | |
| return 3; | |
| } | |
| } | |
| std::unique_ptr<httplib::Server> svr = std::make_unique<httplib::Server>(); | |
| std::atomic<server_state> state{SERVER_STATE_LOADING_MODEL}; | |
| struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams); | |
| if (ctx == nullptr) { | |
| fprintf(stderr, "error: failed to initialize whisper context\n"); | |
| return 3; | |
| } | |
| // initialize openvino encoder. this has no effect on whisper.cpp builds that don't have OpenVINO configured | |
| whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr); | |
| state.store(SERVER_STATE_READY); | |
| svr->set_default_headers({{"Server", "whisper.cpp"}, | |
| {"Access-Control-Allow-Origin", "*"}, | |
| {"Access-Control-Allow-Headers", "content-type, authorization"}}); | |
| std::string const default_content = R"( | |
| <html> | |
| <head> | |
| <title>Whisper.cpp Server</title> | |
| <meta charset="utf-8"> | |
| <meta name="viewport" content="width=device-width"> | |
| <style> | |
| body { | |
| font-family: sans-serif; | |
| max-width: 900px; | |
| margin: 1rem auto; | |
| padding: 0 1rem; | |
| } | |
| form { | |
| display: flex; | |
| flex-direction: column; | |
| align-items: flex-start; | |
| margin-bottom: 1.5rem; | |
| } | |
| label { | |
| margin-bottom: 0.5rem; | |
| } | |
| input, select, button, textarea { | |
| margin-bottom: 1rem; | |
| } | |
| .box { border: 1px solid #ddd; padding: 1rem; border-radius: 6px; } | |
| </style> | |
| </head> | |
| <body> | |
| <h1>Whisper.cpp Server</h1> | |
| <h2>/inference (同步示例)</h2> | |
| <pre> | |
| curl 127.0.0.1:)" + std::to_string(sparams.port) + R"(/inference \ | |
| -H "Content-Type: multipart/form-data" \ | |
| -F file="@<file-path>" \ | |
| -F temperature="0.0" \ | |
| -F temperature_inc="0.2" \ | |
| -F response_format="json" | |
| </pre> | |
| <h2>/load</h2> | |
| <pre> | |
| curl 127.0.0.1:)" + std::to_string(sparams.port) + R"(/load \ | |
| -H "Content-Type: multipart/form-data" \ | |
| -F model="<path-to-model-file>" | |
| </pre> | |
| <div class="box"> | |
| <h2>同步 Try it out</h2> | |
| <form action="/inference" method="POST" enctype="multipart/form-data"> | |
| <label for="file">Choose an audio file:</label> | |
| <input type="file" id="file" name="file" accept="audio/*" required> | |
| <label for="response_format">Response Format:</label> | |
| <select id="response_format" name="response_format"> | |
| <option value="verbose_json">Verbose JSON</option> | |
| <option value="json">JSON</option> | |
| <option value="text">Text</option> | |
| <option value="srt">SRT</option> | |
| <option value="vtt">VTT</option> | |
| </select> | |
| <button type="submit">Run synchronous inference</button> | |
| </form> | |
| </div> | |
| <div class="box"> | |
| <h2>异步示例(可运行)</h2> | |
| <form id="async-form" enctype="multipart/form-data"> | |
| <label for="afile">Choose an audio file:</label> | |
| <input type="file" id="afile" name="file" accept="audio/*" required> | |
| <label for="a_response_format">Response Format:</label> | |
| <select id="a_response_format" name="response_format"> | |
| <option value="json">JSON</option> | |
| <option value="text">Text</option> | |
| <option value="srt">SRT</option> | |
| <option value="vtt">VTT</option> | |
| <option value="verbose_json">Verbose JSON</option> | |
| </select> | |
| <button id="async-submit" type="button">Submit async job</button> | |
| </form> | |
| <div> | |
| <h3>Task</h3> | |
| <div id="task-id">(no task)</div> | |
| <h3>Result / Status</h3> | |
| <pre id="task-result" style="white-space:pre-wrap; background:#f7f7f7; padding:0.5rem; border-radius:4px;"></pre> | |
| </div> | |
| </div> | |
| <script> | |
| (function(){ | |
| const submitBtn = document.getElementById('async-submit'); | |
| const form = document.getElementById('async-form'); | |
| const taskIdEl = document.getElementById('task-id'); | |
| const resultEl = document.getElementById('task-result'); | |
| let currentTask = null; | |
| function sleep(ms){ return new Promise(r=>setTimeout(r, ms)); } | |
| async function pollTask(id){ | |
| taskIdEl.textContent = id; | |
| resultEl.textContent = 'processing...'; | |
| while (true) { | |
| try { | |
| const resp = await fetch('/inference_result?id=' + encodeURIComponent(id)); | |
| if (resp.status === 404) { | |
| resultEl.textContent = 'task not found'; | |
| return; | |
| } | |
| const ctype = resp.headers.get('content-type') || ''; | |
| if (ctype.indexOf('application/json') !== -1) { | |
| const j = await resp.json(); | |
| // if processing status, continue polling | |
| if (j && j.status && (j.status === 'processing')) { | |
| await sleep(1000); | |
| continue; | |
| } | |
| resultEl.textContent = JSON.stringify(j, null, 2); | |
| return; | |
| } else { | |
| // non-json (final text or srt/vtt) | |
| const txt = await resp.text(); | |
| // if it's the processing JSON returned with application/json, handle above | |
| if (txt && txt.indexOf('{"status":"processing"') !== -1) { | |
| await sleep(1000); | |
| continue; | |
| } | |
| resultEl.textContent = txt; | |
| return; | |
| } | |
| } catch (err) { | |
| resultEl.textContent = 'error: ' + err.message; | |
| return; | |
| } | |
| } | |
| } | |
| submitBtn.addEventListener('click', async function(){ | |
| resultEl.textContent = ''; | |
| const fileInput = document.getElementById('afile'); | |
| if (!fileInput.files || fileInput.files.length === 0) { | |
| alert('Please choose a file'); | |
| return; | |
| } | |
| const fd = new FormData(); | |
| fd.append('file', fileInput.files[0]); | |
| fd.append('response_format', document.getElementById('a_response_format').value); | |
| submitBtn.disabled = true; | |
| submitBtn.textContent = 'Submitting...'; | |
| try { | |
| const resp = await fetch('/inference_async', { method: 'POST', body: fd }); | |
| const j = await resp.json(); | |
| if (j && j.task_id) { | |
| currentTask = j.task_id; | |
| pollTask(currentTask); | |
| } else { | |
| resultEl.textContent = 'invalid response: ' + JSON.stringify(j); | |
| } | |
| } catch (err) { | |
| resultEl.textContent = 'submit error: ' + err.message; | |
| } finally { | |
| submitBtn.disabled = false; | |
| submitBtn.textContent = 'Submit async job'; | |
| } | |
| }); | |
| })(); | |
| </script> | |
| </body> | |
| </html> | |
| )"; | |
| // store default params so we can reset after each inference request | |
| whisper_params default_params = params; | |
| // this is only called if no index.html is found in the public --path | |
| svr->Get(sparams.request_path + "/", [&](const Request &, Response &res){ | |
| res.set_content(default_content, "text/html"); | |
| return false; | |
| }); | |
| svr->Options(sparams.request_path + sparams.inference_path, [&](const Request &, Response &){ | |
| }); | |
| // Helper: run inference for a prepared audio buffer and params, store response in task | |
| auto run_inference_task = [&](const std::string & task_id, | |
| whisper_params task_params, | |
| std::vector<float> pcmf32, | |
| std::vector<std::vector<float>> pcmf32s, | |
| const Request * orig_req) { | |
| { | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| tasks[task_id].status = async_status::RUNNING; | |
| } | |
| try { | |
| // set up whisper params | |
| whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY); | |
| wparams.strategy = task_params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY; | |
| wparams.print_realtime = false; | |
| wparams.print_progress = task_params.print_progress; | |
| wparams.print_timestamps = !task_params.no_timestamps; | |
| wparams.print_special = task_params.print_special; | |
| wparams.translate = task_params.translate; | |
| wparams.language = task_params.language.c_str(); | |
| wparams.detect_language = task_params.detect_language; | |
| wparams.n_threads = task_params.n_threads; | |
| wparams.n_max_text_ctx = task_params.max_context >= 0 ? task_params.max_context : wparams.n_max_text_ctx; | |
| wparams.offset_ms = task_params.offset_t_ms; | |
| wparams.duration_ms = task_params.duration_ms; | |
| wparams.thold_pt = task_params.word_thold; | |
| wparams.max_len = task_params.max_len == 0 ? 60 : task_params.max_len; | |
| wparams.split_on_word = task_params.split_on_word; | |
| wparams.audio_ctx = task_params.audio_ctx; | |
| wparams.debug_mode = task_params.debug_mode; | |
| wparams.tdrz_enable = task_params.tinydiarize; // [TDRZ] | |
| wparams.initial_prompt = task_params.prompt.c_str(); | |
| wparams.greedy.best_of = task_params.best_of; | |
| wparams.beam_search.beam_size = task_params.beam_size; | |
| wparams.temperature = task_params.temperature; | |
| wparams.no_speech_thold = task_params.no_speech_thold; | |
| wparams.temperature_inc = task_params.temperature_inc; | |
| wparams.entropy_thold = task_params.entropy_thold; | |
| wparams.logprob_thold = task_params.logprob_thold; | |
| wparams.no_timestamps = task_params.no_timestamps; | |
| wparams.token_timestamps = !task_params.no_timestamps && task_params.response_format == vjson_format; | |
| wparams.no_context = task_params.no_context; | |
| wparams.suppress_nst = task_params.suppress_nst; | |
| wparams.vad = task_params.vad; | |
| wparams.vad_model_path = task_params.vad_model.c_str(); | |
| wparams.vad_params.threshold = task_params.vad_threshold; | |
| wparams.vad_params.min_speech_duration_ms = task_params.vad_min_speech_duration_ms; | |
| wparams.vad_params.min_silence_duration_ms = task_params.vad_min_silence_duration_ms; | |
| wparams.vad_params.max_speech_duration_s = task_params.vad_max_speech_duration_s; | |
| wparams.vad_params.speech_pad_ms = task_params.vad_speech_pad_ms; | |
| wparams.vad_params.samples_overlap = task_params.vad_samples_overlap; | |
| whisper_print_user_data user_data = { &task_params, &pcmf32s, 0 }; | |
| if (task_params.print_realtime) { | |
| wparams.new_segment_callback = whisper_print_segment_callback; | |
| wparams.new_segment_callback_user_data = &user_data; | |
| } | |
| if (wparams.print_progress) { | |
| wparams.progress_callback = whisper_print_progress_callback; | |
| wparams.progress_callback_user_data = &user_data; | |
| } | |
| // abort callback uses original request pointer if provided | |
| // ggml_abort_callback expects a function returning bool | |
| wparams.abort_callback = [](void *user_data)->bool { | |
| if (!user_data) return false; | |
| auto req_ptr = static_cast<const httplib::Request*>(user_data); | |
| return req_ptr->is_connection_closed(); | |
| }; | |
| wparams.abort_callback_user_data = (void*)orig_req; | |
| if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), task_params.n_processors) != 0) { | |
| // failure | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| tasks[task_id].status = async_status::FAILED; | |
| tasks[task_id].error = "failed to process audio"; | |
| tasks[task_id].result = ""; | |
| return; | |
| } | |
| // prepare response according to format | |
| std::string content; | |
| std::string ctype = "application/json"; | |
| if (task_params.response_format == text_format) { | |
| content = output_str(ctx, task_params, pcmf32s); | |
| ctype = "text/plain; charset=utf-8"; | |
| } else if (task_params.response_format == srt_format) { | |
| std::stringstream ss; | |
| const int n_segments = whisper_full_n_segments(ctx); | |
| for (int i = 0; i < n_segments; ++i) { | |
| const char * text = whisper_full_get_segment_text(ctx, i); | |
| const int64_t t0 = whisper_full_get_segment_t0(ctx, i); | |
| const int64_t t1 = whisper_full_get_segment_t1(ctx, i); | |
| std::string speaker = ""; | |
| if (task_params.diarize && pcmf32s.size() == 2) { | |
| speaker = estimate_diarization_speaker(pcmf32s, t0, t1); | |
| } | |
| ss << i + 1 + task_params.offset_n << "\n"; | |
| ss << to_timestamp(t0, true) << " --> " << to_timestamp(t1, true) << "\n"; | |
| ss << speaker << text << "\n\n"; | |
| } | |
| content = ss.str(); | |
| ctype = "application/x-subrip"; | |
| } else if (task_params.response_format == vtt_format) { | |
| std::stringstream ss; | |
| ss << "WEBVTT\n\n"; | |
| const int n_segments = whisper_full_n_segments(ctx); | |
| for (int i = 0; i < n_segments; ++i) { | |
| const char * text = whisper_full_get_segment_text(ctx, i); | |
| const int64_t t0 = whisper_full_get_segment_t0(ctx, i); | |
| const int64_t t1 = whisper_full_get_segment_t1(ctx, i); | |
| std::string speaker = ""; | |
| if (task_params.diarize && pcmf32s.size() == 2) { | |
| speaker = estimate_diarization_speaker(pcmf32s, t0, t1, true); | |
| speaker.insert(0, "<v Speaker"); | |
| speaker.append(">"); | |
| } | |
| ss << to_timestamp(t0) << " --> " << to_timestamp(t1) << "\n"; | |
| ss << speaker << text << "\n\n"; | |
| } | |
| content = ss.str(); | |
| ctype = "text/vtt"; | |
| } else if (task_params.response_format == vjson_format) { | |
| std::string results = output_str(ctx, task_params, pcmf32s); | |
| json jres = json{ | |
| {"task", task_params.translate ? "translate" : "transcribe"}, | |
| {"language", whisper_lang_str_full(whisper_full_lang_id(ctx))}, | |
| {"duration", float(pcmf32.size())/WHISPER_SAMPLE_RATE}, | |
| {"text", results}, | |
| {"segments", json::array()} | |
| }; | |
| if (!task_params.no_language_probabilities) { | |
| std::vector<float> lang_probs(whisper_lang_max_id() + 1, 0.0f); | |
| const auto detected_lang_id = whisper_lang_auto_detect(ctx, 0, task_params.n_threads, lang_probs.data()); | |
| jres["detected_language"] = whisper_lang_str_full(detected_lang_id); | |
| jres["detected_language_probability"] = lang_probs[detected_lang_id]; | |
| jres["language_probabilities"] = json::object(); | |
| for (int i = 0; i <= whisper_lang_max_id(); ++i) { | |
| if (lang_probs[i] > 0.001f) { | |
| jres["language_probabilities"][whisper_lang_str(i)] = lang_probs[i]; | |
| } | |
| } | |
| } | |
| const int n_segments = whisper_full_n_segments(ctx); | |
| for (int i = 0; i < n_segments; ++i) { | |
| json segment = json{{"id", i}, {"text", whisper_full_get_segment_text(ctx, i)}}; | |
| if (!task_params.no_timestamps) { | |
| segment["start"] = whisper_full_get_segment_t0(ctx, i) * 0.01; | |
| segment["end"] = whisper_full_get_segment_t1(ctx, i) * 0.01; | |
| } | |
| float total_logprob = 0; | |
| const int n_tokens = whisper_full_n_tokens(ctx, i); | |
| for (int j = 0; j < n_tokens; ++j) { | |
| whisper_token_data token = whisper_full_get_token_data(ctx, i, j); | |
| if (token.id >= whisper_token_eot(ctx)) continue; | |
| segment["tokens"].push_back(token.id); | |
| json word = json{{"word", whisper_full_get_token_text(ctx, i, j)}}; | |
| if (!task_params.no_timestamps) { | |
| word["start"] = token.t0 * 0.01; | |
| word["end"] = token.t1 * 0.01; | |
| word["t_dtw"] = token.t_dtw; | |
| } | |
| word["probability"] = token.p; | |
| total_logprob += token.plog; | |
| segment["words"].push_back(word); | |
| } | |
| segment["temperature"] = task_params.temperature; | |
| segment["avg_logprob"] = total_logprob / n_tokens; | |
| segment["no_speech_prob"] = whisper_full_get_segment_no_speech_prob(ctx, i); | |
| jres["segments"].push_back(segment); | |
| } | |
| content = jres.dump(-1, ' ', false, json::error_handler_t::replace); | |
| ctype = "application/json"; | |
| } else { | |
| std::string results = output_str(ctx, task_params, pcmf32s); | |
| json jres = json{{"text", results}}; | |
| content = jres.dump(-1, ' ', false, json::error_handler_t::replace); | |
| ctype = "application/json"; | |
| } | |
| // store result | |
| { | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| tasks[task_id].status = async_status::FINISHED; | |
| tasks[task_id].result = content; | |
| tasks[task_id].content_type = ctype; | |
| } | |
| } catch (const std::exception &e) { | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| tasks[task_id].status = async_status::FAILED; | |
| tasks[task_id].error = e.what(); | |
| tasks[task_id].result.clear(); | |
| } | |
| }; | |
| // Synchronous inference kept for compatibility at original path | |
| svr->Post(sparams.request_path + sparams.inference_path, [&](const Request &req, Response &res){ | |
| // existing synchronous behavior: simply call async helper synchronously while holding mutex | |
| std::lock_guard<std::mutex> lock(whisper_mutex); | |
| if (!req.has_file("file")) { | |
| const std::string error_resp = "{\"error\":\"no 'file' field in the request\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| auto audio_file = req.get_file_value("file"); | |
| // gather parameters | |
| get_req_parameters(req, params); | |
| std::vector<float> pcmf32; | |
| std::vector<std::vector<float>> pcmf32s; | |
| if (sparams.ffmpeg_converter) { | |
| const std::string temp_filename = generate_temp_filename("whisper-server", ".wav"); | |
| std::ofstream temp_file{temp_filename, std::ios::binary}; | |
| temp_file << audio_file.content; | |
| temp_file.close(); | |
| std::string error_resp; | |
| if (!convert_to_wav(temp_filename, error_resp)) { | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| if (!::read_audio_data(temp_filename, pcmf32, pcmf32s, params.diarize)) { | |
| const std::string error_resp = "{\"error\":\"failed to read WAV file\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| std::remove(temp_filename.c_str()); | |
| return; | |
| } | |
| std::remove(temp_filename.c_str()); | |
| } else { | |
| if (!::read_audio_data(audio_file.content, pcmf32, pcmf32s, params.diarize)) { | |
| const std::string error_resp = "{\"error\":\"failed to read audio data\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| } | |
| // create a temporary task id to run synchronously | |
| const std::string tmp_task_id = generate_task_id(); | |
| { | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| tasks[tmp_task_id] = async_task_t(); | |
| tasks[tmp_task_id].status = async_status::PENDING; | |
| tasks[tmp_task_id].params = params; // store params used for this sync run | |
| } | |
| // run in same thread | |
| run_inference_task(tmp_task_id, params, std::move(pcmf32), std::move(pcmf32s), &req); | |
| // return the stored result | |
| { | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| if (tasks[tmp_task_id].status == async_status::FINISHED) { | |
| res.set_content(tasks[tmp_task_id].result, tasks[tmp_task_id].content_type); | |
| } else if (tasks[tmp_task_id].status == async_status::FAILED) { | |
| const std::string err = tasks[tmp_task_id].error.empty() ? "{\"error\":\"failed\"}" : tasks[tmp_task_id].error; | |
| res.set_content(err, "application/json"); | |
| } else { | |
| res.set_content("{\"status\":\"processing\"}", "application/json"); | |
| } | |
| tasks.erase(tmp_task_id); | |
| } | |
| }); | |
| // POST /inference_async -> enqueue background task and return task id | |
| svr->Post(sparams.request_path + "/inference_async", [&](const Request &req, Response &res){ | |
| if (!req.has_file("file")) { | |
| const std::string error_resp = "{\"error\":\"no 'file' field in the request\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| // prepare params and audio buffers without holding model mutex for long | |
| whisper_params task_params = params; // copy default base | |
| get_req_parameters(req, task_params); | |
| auto audio_file = req.get_file_value("file"); | |
| std::vector<float> pcmf32; | |
| std::vector<std::vector<float>> pcmf32s; | |
| if (sparams.ffmpeg_converter) { | |
| const std::string temp_filename = generate_temp_filename("whisper-server", ".wav"); | |
| std::ofstream temp_file{temp_filename, std::ios::binary}; | |
| temp_file << audio_file.content; | |
| temp_file.close(); | |
| std::string error_resp; | |
| if (!convert_to_wav(temp_filename, error_resp)) { | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| if (!::read_audio_data(temp_filename, pcmf32, pcmf32s, task_params.diarize)) { | |
| const std::string error_resp = "{\"error\":\"failed to read WAV file\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| std::remove(temp_filename.c_str()); | |
| return; | |
| } | |
| std::remove(temp_filename.c_str()); | |
| } else { | |
| if (!::read_audio_data(audio_file.content, pcmf32, pcmf32s, task_params.diarize)) { | |
| const std::string error_resp = "{\"error\":\"failed to read audio data\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| } | |
| // create task id and store placeholder | |
| const std::string task_id = generate_task_id(); | |
| { | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| tasks[task_id] = async_task_t(); | |
| tasks[task_id].status = async_status::PENDING; | |
| tasks[task_id].params = task_params; // store params for async task | |
| } | |
| // spawn background worker thread | |
| std::thread worker([&, task_id, task_params, pcmf32 = std::move(pcmf32), pcmf32s = std::move(pcmf32s)]() mutable { | |
| // ensure only one inference runs at a time | |
| std::lock_guard<std::mutex> lock(whisper_mutex); | |
| // Do not pass pointer to the Request object into background thread - it will be out of scope | |
| run_inference_task(task_id, task_params, std::move(pcmf32), std::move(pcmf32s), nullptr); | |
| }); | |
| worker.detach(); | |
| json j = json{{"task_id", task_id}}; | |
| res.set_content(j.dump(), "application/json"); | |
| }); | |
| // GET /inference_result?id=<task_id> -> return status/result | |
| svr->Get(sparams.request_path + "/inference_result", [&](const Request &req, Response &res){ | |
| if (!req.has_param("id")) { | |
| res.set_content("{\"error\":\"missing id parameter\"}", "application/json"); | |
| return; | |
| } | |
| const std::string id = req.get_param_value("id"); | |
| json response_json; | |
| response_json["status"] = "unknown"; | |
| response_json["data"] = nullptr; | |
| response_json["params"] = json::object(); | |
| { | |
| std::lock_guard<std::mutex> tlock(tasks_mutex); | |
| auto it = tasks.find(id); | |
| if (it == tasks.end()) { | |
| res.set_content("{\"error\":\"task not found\"}", "application/json"); | |
| res.status = 404; | |
| return; | |
| } | |
| auto t = it->second; // copy so we can erase while unlocked | |
| // populate params subset for client inspection | |
| json p = json::object(); | |
| p["temperature"] = t.params.temperature; | |
| p["temperature_inc"] = t.params.temperature_inc; | |
| p["response_format"] = t.params.response_format; | |
| p["n_threads"] = t.params.n_threads; | |
| response_json["params"] = p; | |
| if (t.status == async_status::PENDING || t.status == async_status::RUNNING) { | |
| response_json["status"] = "processing"; | |
| response_json["data"] = nullptr; | |
| res.set_content(response_json.dump(), "application/json"); | |
| return; | |
| } | |
| if (t.status == async_status::FAILED) { | |
| response_json["status"] = "failed"; | |
| response_json["data"] = json{{"error", t.error}}; | |
| // remove failed task from map to avoid accumulation | |
| tasks.erase(it); | |
| res.set_content(response_json.dump(), "application/json"); | |
| return; | |
| } | |
| // FINISHED | |
| response_json["status"] = "finished"; | |
| // If original requested JSON format, try to parse stored result JSON and return as data | |
| if (t.params.response_format == json_format || t.content_type.find("application/json") != std::string::npos) { | |
| try { | |
| json parsed = json::parse(t.result); | |
| response_json["data"] = parsed; | |
| } catch (...) { | |
| response_json["data"] = t.result; | |
| } | |
| } else { | |
| // non-json content -> return as string under data.content | |
| response_json["data"] = json{{"content", t.result}, {"content_type", t.content_type}}; | |
| } | |
| // remove the task after building the response | |
| tasks.erase(it); | |
| } | |
| res.set_content(response_json.dump(), "application/json"); | |
| }); | |
| svr->Post(sparams.request_path + "/load", [&](const Request &req, Response &res){ | |
| std::lock_guard<std::mutex> lock(whisper_mutex); | |
| state.store(SERVER_STATE_LOADING_MODEL); | |
| if (!req.has_file("model")) | |
| { | |
| fprintf(stderr, "error: no 'model' field in the request\n"); | |
| const std::string error_resp = "{\"error\":\"no 'model' field in the request\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| std::string model = req.get_file_value("model").content; | |
| if (!is_file_exist(model.c_str())) | |
| { | |
| fprintf(stderr, "error: 'model': %s not found!\n", model.c_str()); | |
| const std::string error_resp = "{\"error\":\"model not found!\"}"; | |
| res.set_content(error_resp, "application/json"); | |
| return; | |
| } | |
| // clean up | |
| whisper_free(ctx); | |
| // whisper init | |
| ctx = whisper_init_from_file_with_params(model.c_str(), cparams); | |
| // TODO perhaps load prior model here instead of exit | |
| if (ctx == nullptr) { | |
| fprintf(stderr, "error: model init failed, no model loaded must exit\n"); | |
| exit(1); | |
| } | |
| // initialize openvino encoder. this has no effect on whisper.cpp builds that don't have OpenVINO configured | |
| whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr); | |
| state.store(SERVER_STATE_READY); | |
| const std::string success = "Load was successful!"; | |
| res.set_content(success, "application/text"); | |
| // check if the model is in the file system | |
| }); | |
| svr->Get(sparams.request_path + "/health", [&](const Request &, Response &res){ | |
| server_state current_state = state.load(); | |
| if (current_state == SERVER_STATE_READY) { | |
| const std::string health_response = "{\"status\":\"ok\"}"; | |
| res.set_content(health_response, "application/json"); | |
| } else { | |
| res.set_content("{\"status\":\"loading model\"}", "application/json"); | |
| res.status = 503; | |
| } | |
| }); | |
| svr->set_exception_handler([](const Request &, Response &res, std::exception_ptr ep) { | |
| const char fmt[] = "500 Internal Server Error\n%s"; | |
| char buf[BUFSIZ]; | |
| try { | |
| std::rethrow_exception(std::move(ep)); | |
| } catch (std::exception &e) { | |
| snprintf(buf, sizeof(buf), fmt, e.what()); | |
| } catch (...) { | |
| snprintf(buf, sizeof(buf), fmt, "Unknown Exception"); | |
| } | |
| res.set_content(buf, "text/plain"); | |
| res.status = 500; | |
| }); | |
| svr->set_error_handler([](const Request &req, Response &res) { | |
| if (res.status == 400) { | |
| res.set_content("Invalid request", "text/plain"); | |
| } else if (res.status != 500) { | |
| res.set_content("File Not Found (" + req.path + ")", "text/plain"); | |
| res.status = 404; | |
| } | |
| }); | |
| // set timeouts and change hostname and port | |
| svr->set_read_timeout(sparams.read_timeout); | |
| svr->set_write_timeout(sparams.write_timeout); | |
| if (!svr->bind_to_port(sparams.hostname, sparams.port)) | |
| { | |
| fprintf(stderr, "\ncouldn't bind to server socket: hostname=%s port=%d\n\n", | |
| sparams.hostname.c_str(), sparams.port); | |
| return 1; | |
| } | |
| // Set the base directory for serving static files | |
| svr->set_base_dir(sparams.public_path); | |
| // to make it ctrl+clickable: | |
| printf("\nwhisper server listening at http://%s:%d\n\n", sparams.hostname.c_str(), sparams.port); | |
| shutdown_handler = [&](int signal) { | |
| printf("\nCaught signal %d, shutting down gracefully...\n", signal); | |
| if (svr) { | |
| svr->stop(); | |
| } | |
| }; | |
| struct sigaction sigint_action; | |
| sigint_action.sa_handler = signal_handler; | |
| sigemptyset (&sigint_action.sa_mask); | |
| sigint_action.sa_flags = 0; | |
| sigaction(SIGINT, &sigint_action, NULL); | |
| sigaction(SIGTERM, &sigint_action, NULL); | |
| auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL { | |
| return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false; | |
| }; | |
| SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true); | |
| // clean up function, to be called before exit | |
| auto clean_up = [&]() { | |
| whisper_print_timings(ctx); | |
| whisper_free(ctx); | |
| }; | |
| std::thread t([&] { | |
| if (!svr->listen_after_bind()) { | |
| fprintf(stderr, "error: server listen failed\n"); | |
| } | |
| }); | |
| svr->wait_until_ready(); | |
| t.join(); | |
| clean_up(); | |
| return 0; | |
| } | |