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whisper.cpp
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whisper.cpp/examples/lsp/lsp.cpp

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#include "common.h"
#include "common-sdl.h"
#include "whisper.h"
#include "json.hpp"
#include <iostream>
#include <cassert>
#include <cstdio>
#include <string>
#include <thread>
#include <vector>
#include <deque>
#include <set>
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 &params) {
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 &params, 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 &params, 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 &params) {
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;
}
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