diff --git a/llama.cpp b/llama.cpp
index bafb4d866..77bfc3e76 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -736,13 +736,16 @@ int llama_main(
     gpt_vocab vocab,
     llama_model model,
     int64_t t_load_us,
-    int64_t t_main_start_us) {
+    int64_t t_main_start_us,
+    std::istream & instream,
+    FILE *outstream,
+    FILE *errstream) {
 
     if (params.seed < 0) {
         params.seed = time(NULL);
     }
 
-    fprintf(stderr, "%s: seed = %d\n", __func__, params.seed);
+    fprintf(errstream, "%s: seed = %d\n", __func__, params.seed);
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {
@@ -788,13 +791,13 @@ int llama_main(
         params.interactive = true;
     }
 
-    fprintf(stderr, "\n");
-    fprintf(stderr, "%s: prompt: '%s'\n", __func__, params.prompt.c_str());
-    fprintf(stderr, "%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
+    fprintf(errstream, "\n");
+    fprintf(errstream, "%s: prompt: '%s'\n", __func__, params.prompt.c_str());
+    fprintf(errstream, "%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
     for (int i = 0; i < (int) embd_inp.size(); i++) {
-        fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], vocab.id_to_token.at(embd_inp[i]).c_str());
+        fprintf(errstream, "%6d -> '%s'\n", embd_inp[i], vocab.id_to_token.at(embd_inp[i]).c_str());
     }
-    fprintf(stderr, "\n");
+    fprintf(errstream, "\n");
     if (params.interactive) {
 #if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
         struct sigaction sigint_action;
@@ -806,22 +809,22 @@ int llama_main(
         signal(SIGINT, sigint_handler);
 #endif
 
-        fprintf(stderr, "%s: interactive mode on.\n", __func__);
+        fprintf(errstream, "%s: interactive mode on.\n", __func__);
 
         if(antipromptv_inp.size()) {
             for (size_t apindex = 0; apindex < antipromptv_inp.size(); ++apindex) {
                 auto antiprompt_inp = antipromptv_inp.at(apindex);
-                fprintf(stderr, "%s: reverse prompt: '%s'\n", __func__, params.antiprompt.at(apindex).c_str());
-                fprintf(stderr, "%s: number of tokens in reverse prompt = %zu\n", __func__, antiprompt_inp.size());
+                fprintf(errstream, "%s: reverse prompt: '%s'\n", __func__, params.antiprompt.at(apindex).c_str());
+                fprintf(errstream, "%s: number of tokens in reverse prompt = %zu\n", __func__, antiprompt_inp.size());
                 for (int i = 0; i < (int) antiprompt_inp.size(); i++) {
-                    fprintf(stderr, "%6d -> '%s'\n", antiprompt_inp[i], vocab.id_to_token.at(antiprompt_inp[i]).c_str());
+                    fprintf(errstream, "%6d -> '%s'\n", antiprompt_inp[i], vocab.id_to_token.at(antiprompt_inp[i]).c_str());
                 }
-                fprintf(stderr, "\n");
+                fprintf(errstream, "\n");
             }
         }
     }
-    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);
-    fprintf(stderr, "\n\n");
+    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);
+    fprintf(errstream, "\n\n");
 
     std::vector<gpt_vocab::id> embd;
 
@@ -834,7 +837,7 @@ int llama_main(
     std::fill(last_n_tokens.begin(), last_n_tokens.end(), 0);
 
     if (params.interactive) {
-        fprintf(stderr, "== Running in interactive mode. ==\n"
+        fprintf(errstream, "== Running in interactive mode. ==\n"
 #if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)
                " - Press Ctrl+C to interject at any time.\n"
 #endif
@@ -850,7 +853,7 @@ int llama_main(
 
     // set the color for the prompt which will be output initially
     if (params.use_color) {
-        printf(ANSI_COLOR_YELLOW);
+        fprintf(outstream, ANSI_COLOR_YELLOW);
     }
 
     while (remaining_tokens > 0 || params.interactive) {
@@ -859,7 +862,7 @@ int llama_main(
             const int64_t t_start_us = ggml_time_us();
 
             if (!llama_eval(model, params.n_threads, n_past, embd, logits, mem_per_token)) {
-                fprintf(stderr, "Failed to predict\n");
+                fprintf(errstream, "Failed to predict\n");
                 return 1;
             }
 
@@ -920,9 +923,9 @@ int llama_main(
         // display text
         if (!input_noecho) {
             for (auto id : embd) {
-                printf("%s", vocab.id_to_token[id].c_str());
+                fprintf(outstream, "%s", vocab.id_to_token[id].c_str());
             }
-            fflush(stdout);
+            fflush(outstream);
         }
         // reset color to default if we there is no pending user input
         if (!input_noecho && params.use_color && (int)embd_inp.size() == input_consumed) {
@@ -954,7 +957,7 @@ int llama_main(
                 std::string line;
                 bool another_line = true;
                 do {
-                    std::getline(std::cin, line);
+                    std::getline(instream, line);
                     if (line.empty() || line.back() != '\\') {
                         another_line = false;
                     } else {
@@ -983,7 +986,7 @@ int llama_main(
             if (params.interactive) {
                 is_interacting = true;
             } else {
-                fprintf(stderr, " [end of text]\n");
+                fprintf(errstream, " [end of text]\n");
                 break;
             }
         }
@@ -1003,18 +1006,18 @@ int llama_main(
     {
         const int64_t t_main_end_us = ggml_time_us();
 
-        fprintf(stderr, "\n\n");
-        fprintf(stderr, "%s: mem per token = %8zu bytes\n", __func__, mem_per_token);
-        fprintf(stderr, "%s:     load time = %8.2f ms\n", __func__, t_load_us/1000.0f);
-        fprintf(stderr, "%s:   sample time = %8.2f ms\n", __func__, t_sample_us/1000.0f);
-        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);
-        fprintf(stderr, "%s:    total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0f);
+        fprintf(errstream, "\n\n");
+        fprintf(errstream, "%s: mem per token = %8zu bytes\n", __func__, mem_per_token);
+        fprintf(errstream, "%s:     load time = %8.2f ms\n", __func__, t_load_us/1000.0f);
+        fprintf(errstream, "%s:   sample time = %8.2f ms\n", __func__, t_sample_us/1000.0f);
+        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);
+        fprintf(errstream, "%s:    total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0f);
     }
 
     ggml_free(model.ctx);
 
     if (params.use_color) {
-        printf(ANSI_COLOR_RESET);
+        fprintf(outstream, ANSI_COLOR_RESET);
     }
 
     return 0;
diff --git a/llama.h b/llama.h
index cf777c6b6..e8d1d43a5 100644
--- a/llama.h
+++ b/llama.h
@@ -64,5 +64,8 @@ int llama_main(
     gpt_vocab vocab,
     llama_model model,
     int64_t t_load_us,
-    int64_t t_main_start_us);
+    int64_t t_main_start_us,
+    std::istream & instream,
+    FILE *outstream,
+    FILE *errstream);
 bool llama_model_load(const std::string & fname, llama_model & model, gpt_vocab & vocab, int n_ctx, ggml_type memory_type);
diff --git a/main.cpp b/main.cpp
index 5d3cddeaa..0079c3975 100644
--- a/main.cpp
+++ b/main.cpp
@@ -2,6 +2,8 @@
 #include "utils.h"
 #include "llama.h"
 
+#include <iostream>
+
 const char * llama_print_system_info(void) {
     static std::string s;
 
@@ -63,5 +65,5 @@ int main(int argc, char ** argv) {
                 params.n_threads, std::thread::hardware_concurrency(), llama_print_system_info());
     }
 
-    return llama_main(params, vocab, model, t_main_start_us, t_load_us);
+    return llama_main(params, vocab, model, t_main_start_us, t_load_us, std::cin, stdout, stderr);
 }