From c1a44044209d64e47c87f93cafdde4fadaf684e1 Mon Sep 17 00:00:00 2001
From: brandons209 <brandons209@aol.com>
Date: Sun, 20 Jan 2019 02:15:38 -0500
Subject: [PATCH] let text generation run asyncrously

---
 scriptcog/script.py | 51 +++++++++++++++++++++++++--------------------
 1 file changed, 28 insertions(+), 23 deletions(-)

diff --git a/scriptcog/script.py b/scriptcog/script.py
index 2c237e9..f330213 100644
--- a/scriptcog/script.py
+++ b/scriptcog/script.py
@@ -136,6 +136,27 @@ class ScriptCog:
         self._write_config()
         await self.bot.say("Script cooldown is now {}.".format(self.cooldown_limit))
 
+    async def get_model_output(self, num_words, temp, seed):
+        input_text = seed
+        for _  in range(num_words):
+            #tokenize text to ints
+            int_text = _tokenize_punctuation(input_text)
+            int_text = int_text.lower()
+            int_text = int_text.split()
+            try:
+                int_text = np.array([self.word_to_int[word] for word in int_text], dtype=np.int32)
+            except KeyError:
+                await self.bot.say("Sorry, that seed word is not in my vocabulary.\nPlease try an English word from the show.\n")
+                return None
+            #pad text if it is too short, pads with zeros at beginning of text, so shouldnt have too much noise added
+            int_text = pad_sequences([int_text], maxlen=self.sequence_length)
+            #predict next word:
+            prediction = self.model.predict(int_text, verbose=0)
+            output_word = self.int_to_word[_sample(prediction, temp=temp)]
+            #append to the result
+            input_text += ' ' + output_word
+        #convert tokenized punctuation and other characters back
+        return _untokenize_punctuation(input_text)
 
     @commands.command(pass_context=True, no_pm=True)
     async def genscript(self, ctx, num_words_to_generate : int = 100, variance : float = 0.5, seed : str = "pinkie pie::"):
@@ -157,29 +178,13 @@ class ScriptCog:
             variance = 0
 
         await self.bot.say("Generating script, please wait...")
-        input_text = seed
-        for _  in range(num_words_to_generate):
-            #tokenize text to ints
-            int_text = _tokenize_punctuation(input_text)
-            int_text = int_text.lower()
-            int_text = int_text.split()
-            try:
-                int_text = np.array([self.word_to_int[word] for word in int_text], dtype=np.int32)
-            except KeyError:
-                await self.bot.say("Sorry, that seed word is not in my vocabulary.\nPlease try an English word from the show.\n")
-                return
-            #pad text if it is too short, pads with zeros at beginning of text, so shouldnt have too much noise added
-            int_text = pad_sequences([int_text], maxlen=self.sequence_length)
-            #predict next word:
-            prediction = self.model.predict(int_text, verbose=0)
-            output_word = self.int_to_word[_sample(prediction, temp=variance)]
-            #append to the result
-            input_text += ' ' + output_word
-        #convert tokenized punctuation and other characters back
-        result = _untokenize_punctuation(input_text)
-        await self.bot.say("------------------------")
-        await self.bot.say(result)
-        await self.bot.say("------------------------")
+
+        result = self.get_model_output(num_words_to_generate, variance, seed)
+
+        if result is not None:
+            await self.bot.say("------------------------")
+            await self.bot.say(result)
+            await self.bot.say("------------------------")
 
 def setup(bot):
     bot.add_cog(ScriptCog(bot))