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Remove direct access to std streams from llama_main
The goal is to allow running llama_main while connected to other streams, such as TCP sockets. Signed-off-by: Thiago Padilha <[email protected]>
1 parent 50228d5 commit 934840d

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3 files changed

+41
-35
lines changed

3 files changed

+41
-35
lines changed

llama.cpp

Lines changed: 36 additions & 33 deletions
Original file line numberDiff line numberDiff line change
@@ -718,13 +718,16 @@ int llama_main(
718718
gpt_vocab vocab,
719719
llama_model model,
720720
int64_t t_load_us,
721-
int64_t t_main_start_us) {
721+
int64_t t_main_start_us,
722+
FILE *instream,
723+
FILE *outstream,
724+
FILE *errstream) {
722725

723726
if (params.seed < 0) {
724727
params.seed = time(NULL);
725728
}
726729

727-
fprintf(stderr, "%s: seed = %d\n", __func__, params.seed);
730+
fprintf(errstream, "%s: seed = %d\n", __func__, params.seed);
728731

729732
std::mt19937 rng(params.seed);
730733
if (params.prompt.empty()) {
@@ -751,13 +754,13 @@ int llama_main(
751754
// tokenize the reverse prompt
752755
std::vector<gpt_vocab::id> antiprompt_inp = ::llama_tokenize(vocab, params.antiprompt, false);
753756

754-
fprintf(stderr, "\n");
755-
fprintf(stderr, "%s: prompt: '%s'\n", __func__, params.prompt.c_str());
756-
fprintf(stderr, "%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
757+
fprintf(errstream, "\n");
758+
fprintf(errstream, "%s: prompt: '%s'\n", __func__, params.prompt.c_str());
759+
fprintf(errstream, "%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
757760
for (int i = 0; i < (int) embd_inp.size(); i++) {
758-
fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], vocab.id_to_token.at(embd_inp[i]).c_str());
761+
fprintf(errstream, "%6d -> '%s'\n", embd_inp[i], vocab.id_to_token.at(embd_inp[i]).c_str());
759762
}
760-
fprintf(stderr, "\n");
763+
fprintf(errstream, "\n");
761764
if (params.interactive) {
762765
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
763766
struct sigaction sigint_action;
@@ -769,19 +772,19 @@ int llama_main(
769772
signal(SIGINT, sigint_handler);
770773
#endif
771774

772-
fprintf(stderr, "%s: interactive mode on.\n", __func__);
775+
fprintf(errstream, "%s: interactive mode on.\n", __func__);
773776

774777
if(antiprompt_inp.size()) {
775-
fprintf(stderr, "%s: reverse prompt: '%s'\n", __func__, params.antiprompt.c_str());
776-
fprintf(stderr, "%s: number of tokens in reverse prompt = %zu\n", __func__, antiprompt_inp.size());
778+
fprintf(errstream, "%s: reverse prompt: '%s'\n", __func__, params.antiprompt.c_str());
779+
fprintf(errstream, "%s: number of tokens in reverse prompt = %zu\n", __func__, antiprompt_inp.size());
777780
for (int i = 0; i < (int) antiprompt_inp.size(); i++) {
778-
fprintf(stderr, "%6d -> '%s'\n", antiprompt_inp[i], vocab.id_to_token.at(antiprompt_inp[i]).c_str());
781+
fprintf(errstream, "%6d -> '%s'\n", antiprompt_inp[i], vocab.id_to_token.at(antiprompt_inp[i]).c_str());
779782
}
780-
fprintf(stderr, "\n");
783+
fprintf(errstream, "\n");
781784
}
782785
}
783-
fprintf(stderr, "sampling parameters: temp = %f, top_k = %d, top_p = %f, repeat_last_n = %i, repeat_penalty = %f\n", params.temp, params.top_k, params.top_p, params.repeat_last_n, params.repeat_penalty);
784-
fprintf(stderr, "\n\n");
786+
fprintf(errstream, "sampling parameters: temp = %f, top_k = %d, top_p = %f, repeat_last_n = %i, repeat_penalty = %f\n", params.temp, params.top_k, params.top_p, params.repeat_last_n, params.repeat_penalty);
787+
fprintf(errstream, "\n\n");
785788

786789
std::vector<gpt_vocab::id> embd;
787790

@@ -795,7 +798,7 @@ int llama_main(
795798

796799

797800
if (params.interactive) {
798-
fprintf(stderr, "== Running in interactive mode. ==\n"
801+
fprintf(errstream, "== Running in interactive mode. ==\n"
799802
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)
800803
" - Press Ctrl+C to interject at any time.\n"
801804
#endif
@@ -814,7 +817,7 @@ int llama_main(
814817

815818
// set the color for the prompt which will be output initially
816819
if (params.use_color) {
817-
printf(ANSI_COLOR_YELLOW);
820+
fprintf(outstream, ANSI_COLOR_YELLOW);
818821
}
819822

820823
while (remaining_tokens > 0) {
@@ -823,7 +826,7 @@ int llama_main(
823826
const int64_t t_start_us = ggml_time_us();
824827

825828
if (!llama_eval(model, params.n_threads, n_past, embd, logits, mem_per_token)) {
826-
fprintf(stderr, "Failed to predict\n");
829+
fprintf(errstream, "Failed to predict\n");
827830
return 1;
828831
}
829832

@@ -877,16 +880,16 @@ int llama_main(
877880

878881
// reset color to default if we there is no pending user input
879882
if (!input_noecho && params.use_color && embd_inp.size() == input_consumed) {
880-
printf(ANSI_COLOR_RESET);
883+
fprintf(outstream, ANSI_COLOR_RESET);
881884
}
882885
}
883886

884887
// display text
885888
if (!input_noecho) {
886889
for (auto id : embd) {
887-
printf("%s", vocab.id_to_token[id].c_str());
890+
fprintf(outstream, "%s", vocab.id_to_token[id].c_str());
888891
}
889-
fflush(stdout);
892+
fflush(outstream);
890893
}
891894

892895
// in interactive mode, and not currently processing queued inputs;
@@ -901,16 +904,16 @@ int llama_main(
901904
// currently being interactive
902905
bool another_line=true;
903906
while (another_line) {
904-
fflush(stdout);
907+
fflush(outstream);
905908
char buf[256] = {0};
906909
int n_read;
907-
if(params.use_color) printf(ANSI_BOLD ANSI_COLOR_GREEN);
908-
if (scanf("%255[^\n]%n%*c", buf, &n_read) <= 0) {
910+
if(params.use_color) fprintf(outstream, ANSI_BOLD ANSI_COLOR_GREEN);
911+
if (fscanf(instream, "%255[^\n]%n%*c", buf, &n_read) <= 0) {
909912
// presumable empty line, consume the newline
910-
std::ignore = scanf("%*c");
913+
std::ignore = fscanf(instream, "%*c");
911914
n_read=0;
912915
}
913-
if(params.use_color) printf(ANSI_COLOR_RESET);
916+
if(params.use_color) fprintf(outstream, ANSI_COLOR_RESET);
914917

915918
if (n_read > 0 && buf[n_read-1]=='\\') {
916919
another_line = true;
@@ -936,7 +939,7 @@ int llama_main(
936939

937940
// end of text token
938941
if (embd.back() == 2) {
939-
fprintf(stderr, " [end of text]\n");
942+
fprintf(errstream, " [end of text]\n");
940943
break;
941944
}
942945
}
@@ -949,18 +952,18 @@ int llama_main(
949952
{
950953
const int64_t t_main_end_us = ggml_time_us();
951954

952-
fprintf(stderr, "\n\n");
953-
fprintf(stderr, "%s: mem per token = %8zu bytes\n", __func__, mem_per_token);
954-
fprintf(stderr, "%s: load time = %8.2f ms\n", __func__, t_load_us/1000.0f);
955-
fprintf(stderr, "%s: sample time = %8.2f ms\n", __func__, t_sample_us/1000.0f);
956-
fprintf(stderr, "%s: predict time = %8.2f ms / %.2f ms per token\n", __func__, t_predict_us/1000.0f, t_predict_us/1000.0f/n_past);
957-
fprintf(stderr, "%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0f);
955+
fprintf(errstream, "\n\n");
956+
fprintf(errstream, "%s: mem per token = %8zu bytes\n", __func__, mem_per_token);
957+
fprintf(errstream, "%s: load time = %8.2f ms\n", __func__, t_load_us/1000.0f);
958+
fprintf(errstream, "%s: sample time = %8.2f ms\n", __func__, t_sample_us/1000.0f);
959+
fprintf(errstream, "%s: predict time = %8.2f ms / %.2f ms per token\n", __func__, t_predict_us/1000.0f, t_predict_us/1000.0f/n_past);
960+
fprintf(errstream, "%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0f);
958961
}
959962

960963
ggml_free(model.ctx);
961964

962965
if (params.use_color) {
963-
printf(ANSI_COLOR_RESET);
966+
fprintf(outstream, ANSI_COLOR_RESET);
964967
}
965968

966969
return 0;

llama.h

Lines changed: 4 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -64,5 +64,8 @@ int llama_main(
6464
gpt_vocab vocab,
6565
llama_model model,
6666
int64_t t_load_us,
67-
int64_t t_main_start_us);
67+
int64_t t_main_start_us,
68+
FILE *instream,
69+
FILE *outstream,
70+
FILE *errstream);
6871
bool llama_model_load(const std::string & fname, llama_model & model, gpt_vocab & vocab, int n_ctx);

main.cpp

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -56,5 +56,5 @@ int main(int argc, char ** argv) {
5656
params.n_threads, std::thread::hardware_concurrency(), llama_print_system_info());
5757
}
5858

59-
return llama_main(params, vocab, model, t_main_start_us, t_load_us);
59+
return llama_main(params, vocab, model, t_main_start_us, t_load_us, stdin, stdout, stderr);
6060
}

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