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, " --prompt PROMPT [%-7s] initial prompt (max n_text_ctx/2 tokens)\n", params.prompt.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] input WAV file path\n", "");
fprintf(stderr, " -oved D, --ov-e-device DNAME [%-7s] the OpenVINO device used for encode inference\n", params.openvino_encode_device.c_str());
if (n_max_tokens < (int) res.size()) {
WHISPER_LOG_ERROR("%s: too many resulting tokens: %d (max %d)\n", __func__, (int) res.size(), n_max_tokens);
- return -1;
+ return -(int) res.size();
}
for (int i = 0; i < (int) res.size(); i++) {
return res.size();
}
+int whisper_token_count(struct whisper_context * ctx, const char * text) {
+ return -whisper_tokenize(ctx, text, NULL, 0);
+}
+
int whisper_lang_max_id() {
auto max_id = 0;
for (const auto & kv : g_lang) {
// initial prompt
if (!params.prompt_tokens && params.initial_prompt) {
prompt_tokens.resize(1024);
- prompt_tokens.resize(whisper_tokenize(ctx, params.initial_prompt, prompt_tokens.data(), prompt_tokens.size()));
+ int n_needed = whisper_tokenize(ctx, params.initial_prompt, prompt_tokens.data(), prompt_tokens.size());
+ if (n_needed < 0) {
+ prompt_tokens.resize(-n_needed);
+ n_needed = whisper_tokenize(ctx, params.initial_prompt, prompt_tokens.data(), prompt_tokens.size());
+ }
+ prompt_tokens.resize(n_needed);
params.prompt_tokens = prompt_tokens.data();
params.prompt_n_tokens = prompt_tokens.size();
}
// Convert the provided text into tokens.
// The tokens pointer must be large enough to hold the resulting tokens.
// Returns the number of tokens on success, no more than n_max_tokens
- // Returns -1 on failure
+ // Returns a negative number on failure - the number of tokens that would have been returned
// TODO: not sure if correct
WHISPER_API int whisper_tokenize(
struct whisper_context * ctx,
whisper_token * tokens,
int n_max_tokens);
+ // Return the number of tokens in the provided text
+ // Equivalent to: -whisper_tokenize(ctx, text, NULL, 0)
+ int whisper_token_count(struct whisper_context * ctx, const char * text);
+
// Largest language id (i.e. number of available languages - 1)
WHISPER_API int whisper_lang_max_id();
// tokens to provide to the whisper decoder as initial prompt
// these are prepended to any existing text context from a previous call
+ // use whisper_tokenize() to convert text to tokens
+ // maximum of whisper_n_text_ctx()/2 tokens are used (typically 224)
const char * initial_prompt;
const whisper_token * prompt_tokens;
int prompt_n_tokens;