Merge pull request #85 from AIDungeon/develop

Develop -> master

data/build_training_data.py

@@ -1,5 +1,6 @@
 import csv
 import json
+
 from story.utils import *
 
 

data/make_reddit_data.py

@@ -1,7 +1,8 @@
 import json
-from story.utils import *
 import os
 
+from story.utils import *
+
 
 def load_stories(file):
 

data/scraper.py

@@ -1,7 +1,9 @@
+import json
+import time
+
 from selenium import webdriver
 from selenium.webdriver.chrome.options import Options
-import time
-import json
+
 
 """
 format of tree is

generator/gpt2/download_model.py

@@ -1,5 +1,6 @@
 import os
 import sys
+
 import requests
 from tqdm import tqdm
 

generator/gpt2/gpt2_generator.py

@@ -1,14 +1,15 @@
-from story.utils import *
+import json
+import os
 import warnings
 
-warnings.filterwarnings("ignore")
-import os
+import numpy as np
 import tensorflow as tf
+from generator.gpt2.src import encoder, model, sample
+from story.utils import *
+
+warnings.filterwarnings("ignore")
 
 tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
-from generator.gpt2.src import sample, encoder, model
-import json
-import numpy as np
 
 
 class GPT2Generator:

generator/gpt2/src/encoder.py

@@ -1,10 +1,11 @@
 """Byte pair encoding utilities"""
 
-import os
 import json
-import regex as re
+import os
 from functools import lru_cache
 
+import regex as re
+
 
 @lru_cache()
 def bytes_to_unicode():

generator/gpt2/src/sample.py

@@ -1,5 +1,4 @@
 import tensorflow as tf
-
 from generator.gpt2.src import model
 
 

generator/simple/finetune.py

@@ -1,7 +1,7 @@
-import tarfile
 import os
-import gpt_2_simple as gpt2
+import tarfile
 
+import gpt_2_simple as gpt2
 
 model_name = "1558M"
 if not os.path.isdir(os.path.join("models", model_name)):

other/cacher.py

@@ -1,6 +1,7 @@
-from google.cloud import storage
 import os
 
+from google.cloud import storage
+
 
 class Cacher:
     def __init__(self, credentials_file, bucket_name="dungeon-cache"):

play.py

@@ -1,7 +1,10 @@
-from story.story_manager import *
+import os
+import sys
+import time
+
 from generator.gpt2.gpt2_generator import *
+from story.story_manager import *
 from story.utils import *
-import time, sys, os
 
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
 

play_dm.py

@@ -1,9 +1,12 @@
-from story.story_manager import *
-from generator.human_dm import *
+import os
+import sys
+import time
+
 from generator.gpt2.gpt2_generator import *
-from story.utils import *
+from generator.human_dm import *
 from play import *
-import time, sys, os
+from story.story_manager import *
+from story.utils import *
 
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
 

story/story_manager.py

@@ -1,9 +1,10 @@
-from story.utils import *
 import json
+import os
+import subprocess
 import uuid
 from subprocess import Popen
-import subprocess
-import os
+
+from story.utils import *
 
 
 class Story:

story/utils.py

@@ -1,11 +1,12 @@
 # coding: utf-8
 import re
-import yaml
 from difflib import SequenceMatcher
 
+import yaml
+from profanityfilter import ProfanityFilter
+
 YAML_FILE = "story/story_data.yaml"
 
-from profanityfilter import ProfanityFilter
 
 with open("story/extra_censored_words.txt", "r") as f:
     more_words = [l.replace("\n", "") for l in f.readlines()]
@@ -47,41 +48,31 @@ def get_num_options(num):
 
 
 def player_died(text):
-
-    # reg_phrases = ["You[a-zA-Z ]* die.", "you[a-zA-Z ]* die.", "You[a-zA-Z ]* die ", "you[a-zA-Z ]* die ",]
-    #
-    # for phrase in reg_phrases:
-    #     reg_expr = re.compile(phrase)
-    #     matches = re.findall(reg_expr, text)
-    #     if len(matches) > 0:
-    #         return True
-
-    dead_phrases = [
-        "you die",
-        "You die",
-        "you died",
-        "you are dead",
-        "You died",
-        "You are dead",
-        "You're dead",
-        "you're dead",
-        "you have died",
-        "You have died",
-        "you bleed out",
+    """
+    TODO: Add in more sophisticated NLP, maybe a custom classifier
+    trained on hand-labelled data that classifies second-person
+    statements as resulting in death or not.
+    """
+    lower_text = text.lower()
+    you_dead_regexps = [
+        "you('re| are) (dead|killed|slain|no more|nonexistent)",
+        "you (die|pass away|perish|suffocate|drown|bleed out)",
+        "you('ve| have) (died|perished|suffocated|drowned|been (killed|slain))",
+        "you \w* to death",
+        "you \w+ yourself to death",
     ]
-    for phrase in dead_phrases:
-        if phrase in text:
-            return True
-    return False
+    return any(re.search(regexp, lower_text) for regexp in you_dead_regexps)
 
 
 def player_won(text):
-
-    won_phrases = ["live happily ever after", "you live forever"]
-    for phrase in won_phrases:
-        if phrase in text:
-            return True
-    return False
+    lower_text = text.lower()
+    won_phrases = [
+        "live happily ever after",
+        "(you)? live (forever|eternally|for eternity)",
+        "you (are|become|turn into) (a)? (deity|god)",
+        "you ((go|get) (in)?to|arrive (at|in)) (heaven|paradise)",
+    ]
+    return any(re.search(regexp, lower_text) for regexp in won_phrases)
 
 
 def remove_profanity(text):