Update app.py

app.py

@@ -7,9 +7,11 @@ from functools import lru_cache
 
 # Download and use the NLTK corpus
 nltk.download('words')
+nltk.download('gutenberg')
 nltk.download('averaged_perceptron_tagger')
+nltk.download('punkt')
 from nltk.corpus import words
-from nltk import pos_tag
+from nltk import pos_tag, sent_tokenize
 
 WORD_LIST = set(words.words())  # Use NLTK's word corpus
 
@@ -22,6 +24,7 @@ class AscensionAI:
         self.paths = self.create_dynamic_paths()
         self.word_corpus = WORD_LIST  # Use NLTK's English word corpus
         self.state_memory = defaultdict(int)  # Memory for tracking state-aware words
+        self.training_data = self.load_training_data()
     
     def generate_dynamic_knowledge(self):
         """Generates dynamic knowledge categories based on linguistic analysis."""
@@ -44,6 +47,21 @@ class AscensionAI:
             return self.knowledge[category]
         return path
     
+    def load_training_data(self):
+        """Loads and preprocesses human-like paragraphs from 'Astral.txt'."""
+        try:
+            with open("astral.txt", "r", encoding="utf-8") as file:
+                text_data = file.read()
+            sentences = sent_tokenize(text_data)
+            return sentences[:1000]  # Use first 1000 sentences for training
+        except FileNotFoundError:
+            return ["Error: Book file not found. Please download 'astral.txt'."]
+    
+    def generate_human_like_response(self, input_text):
+        """Finds a related sentence from the pre-trained corpus to mimic human output."""
+        similar_sentences = [sent for sent in self.training_data if any(word in sent for word in input_text.split())]
+        return random.choice(similar_sentences) if similar_sentences else "I perceive a shift in consciousness."
+    
     @lru_cache(maxsize=None)
     def recursive_ascension(self, depth):
         """Core recursive function simulating ascension cycles."""
@@ -81,7 +99,12 @@ def ascension_interface(input_text):
     ai_system = AscensionAI()
     final_state = ai_system.initiate_ascension()
     prediction = ai_system.analyze_future_timeline(input_text)
-    return f"Final Consciousness State: {final_state}\nFinal Knowledge Levels: {ai_system.knowledge}\n{prediction}"
+    human_like_response = ai_system.generate_human_like_response(input_text)
+    
+    return (f"Final Consciousness State: {final_state}\n"
+            f"Final Knowledge Levels: {ai_system.knowledge}\n"
+            f"{prediction}\n\n"
+            f"Philosophical Reflection: {human_like_response}")
 
 app = gr.Interface(
     fn=ascension_interface,