Merge branch 'pytorch_clear_actions' & 'suggestion loop' into pytorch

config.ini

@@ -97,4 +97,5 @@ query = 7;42
 ai-text = 37
 main-prompt = 34
 user-text = 36
+transformed-user-text = 36
 print-story = 37

play.py

@@ -25,16 +25,27 @@ with open(Path('interface', 'clover'), 'r', encoding='utf-8') as file:
 
 
 #ECMA-48 set graphics codes for the curious. Check out "man console_codes"
-def colPrint(str, col='0', wrap=True):
+def colPrint(str, col='0', wrap=True, end=None):
         if wrap and settings.getint('text-wrap-width') > 1:
             str = textwrap.fill(str, settings.getint('text-wrap-width'), replace_whitespace=False)
-        print("\x1B[{}m{}\x1B[{}m".format(col, str, colors["default"]))
+        print("\x1B[{}m{}\x1B[{}m".format(col, str, colors["default"]), end=end)
 
 def colInput(str, col1=colors["default"], col2=colors["default"]):
     val=input("\x1B[{}m{}\x1B[0m\x1B[{}m".format(col1,str,col1))
     print('\x1B[0m', end='')
     return val
 
+def clear_lines(n):
+    """Clear the last line in the terminal."""
+    screen_code = "\033[1A[\033[2K"  # up one line, and clear line
+    for _ in range(n):
+        print(screen_code, end="")
+
+def count_printed_lines(text):
+    """For a prompt, work out how many console lines it took up with wrapping."""
+    width = settings.getint("text-wrap-width")
+    return sum([(len(ss) // width) + 1 for ss in text.split("\n")])
+
 def getNumberInput(n):
     val=colInput("Enter a number from above (default 0):", colors["selection-prompt"], colors["selection-value"])
     if val=='':
@@ -93,21 +104,6 @@ class AIPlayer:
                 prompt, generate_num=settings.getint('action-generate-num'), temperature=settings.getint('action-temp'))
         return clean_suggested_action(result_raw, min_length=settings.getint('action-min-length'))
 
-    def get_actions(self, prompt):
-        suggested_actions = [
-                self.get_action(prompt)
-                for _ in range(settings.getint('action-alternatives')) 
-            ]
-        logger.debug("Suggested actions before filter and dedup %s", suggested_actions)
-        #remove short ones
-        suggested_actions = [
-                s
-                for s in suggested_actions
-                if len(s) > settings.getint('action-min-length')
-            ]
-        #remove dups
-        suggested_actions = list(set(suggested_actions))
-        return suggested_actions
 
 def play():
     generator = getGenerator()
@@ -171,17 +167,26 @@ def play():
                     ) + "\n>"
                 suggested_actions = []
                 colPrint('Suggested actions:', colors['selection-value'])
+                action_suggestion_lines = 1
                 for i in range(settings.getint('action-alternatives')):
                     suggested_action = ai_player.get_action(action_prompt)
                     suggested_actions.append(suggested_action)
-                    colPrint('{}> {}'.format(i, suggested_action), colors['selection-value'])
+                    suggestion = '{}> {}'.format(i, suggested_action)
+                    colPrint(suggestion, colors['selection-value'])
+                    action_suggestion_lines += count_printed_lines(suggestion)
                 print()
 
             if settings.getboolean('console-bell'):
                 print('\x07', end='')
             action = colInput("> ", colors["main-prompt"], colors["user-text"])
             
-            #TODO:Clear suggestions and user input
+            # Clear suggestions and user input
+            if settings.getint('action-alternatives') > 0:
+                action_suggestion_lines += count_printed_lines('> '+action) + 1
+                clear_lines(action_suggestion_lines)
+
+                # Show user input again
+                colPrint("\n> " + action.rstrip(), colors["user-text"], end="")
 
             setRegex = re.search('^set ([^ ]+) ([^ ]+)$', action)
             if setRegex:
@@ -247,6 +252,7 @@ def play():
 
                     action = "\n> " + action + "\n"
 
+                colPrint("\n>> " + action.lstrip(), colors["transformed-user-text"])
                 result = "\n" + story_manager.act(action)
                 if len(story_manager.story.results) >= 2:
                     similarity = get_similarity(