Add greed parameter

modules/chat.py

@@ -84,7 +84,7 @@ def extract_message_from_reply(question, reply, current, other, check, extension
 def stop_everything_event():
     shared.stop_everything = True
 
-def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size):
+def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, greed=1):
     shared.stop_everything = False
     just_started = True
     eos_token = '\n' if check else None
@@ -112,30 +112,33 @@ def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical
         prompt = custom_prompt_generator(text, max_new_tokens, name1, name2, context, chat_prompt_size)
 
     # Generate
-    for reply in generate_reply(prompt, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name1}:"):
-
-        # Extracting the reply
-        reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name2, name1, check, extensions=True)
-        visible_reply = apply_extensions(reply, "output")
-        if shared.args.chat:
-            visible_reply = visible_reply.replace('\n', '<br>')
-
-        # We need this global variable to handle the Stop event,
-        # otherwise gradio gets confused
-        if shared.stop_everything:
-            return shared.history['visible']
-        if just_started:
-            just_started = False
-            shared.history['internal'].append(['', ''])
-            shared.history['visible'].append(['', ''])
-
-        shared.history['internal'][-1] = [text, reply]
-        shared.history['visible'][-1] = [visible_text, visible_reply]
-        if not substring_found:
-            yield shared.history['visible']
-        if next_character_found:
-            break
-    yield shared.history['visible']
+    reply = ''
+    for i in range(greed):
+        for reply in generate_reply(prompt+reply, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name1}:"):
+
+            # Extracting the reply
+            reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name2, name1, check, extensions=True)
+            visible_reply = apply_extensions(reply, "output")
+            if shared.args.chat:
+                visible_reply = visible_reply.replace('\n', '<br>')
+
+            # We need this global variable to handle the Stop event,
+            # otherwise gradio gets confused
+            if shared.stop_everything:
+                return shared.history['visible']
+            if just_started:
+                just_started = False
+                shared.history['internal'].append(['', ''])
+                shared.history['visible'].append(['', ''])
+
+            shared.history['internal'][-1] = [text, reply]
+            shared.history['visible'][-1] = [visible_text, visible_reply]
+            if not substring_found:
+                yield shared.history['visible']
+            if next_character_found:
+                break
+        yield shared.history['visible']
+        print(i, reply)
 
 def impersonate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size):
     eos_token = '\n' if check else None
@@ -153,11 +156,11 @@ def impersonate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typ
             break
     yield reply
 
-def cai_chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size):
-    for _history in chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size):
+def cai_chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, greed=1):
+    for _history in chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, greed):
         yield generate_chat_html(_history, name1, name2, shared.character)
 
-def regenerate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size):
+def regenerate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, greed=1):
     if shared.character != 'None' and len(shared.history['visible']) == 1:
         if shared.args.cai_chat:
             yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)
@@ -167,7 +170,7 @@ def regenerate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typi
         last_visible = shared.history['visible'].pop()
         last_internal = shared.history['internal'].pop()
 
-        for _history in chatbot_wrapper(last_internal[0], max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size):
+        for _history in chatbot_wrapper(last_internal[0], max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, greed):
             if shared.args.cai_chat:
                 shared.history['visible'][-1] = [last_visible[0], _history[-1][1]]
                 yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)

server.py

@@ -241,9 +241,10 @@ if shared.args.chat or shared.args.cai_chat:
                     shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
                 with gr.Column():
                     shared.gradio['chat_prompt_size_slider'] = gr.Slider(minimum=shared.settings['chat_prompt_size_min'], maximum=shared.settings['chat_prompt_size_max'], step=1, label='Maximum prompt size in tokens', value=shared.settings['chat_prompt_size'])
+                shared.gradio['greed'] = gr.Slider(minimum=1, maximum=5, value=1, step=1)
             create_settings_menus()
 
-        shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'name1', 'name2', 'context', 'check', 'chat_prompt_size_slider']]
+        shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'name1', 'name2', 'context', 'check', 'chat_prompt_size_slider', 'greed']]
         if shared.args.extensions is not None:
             with gr.Tab('Extensions'):
                 extensions_module.create_extensions_block()