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| import gradio as gr | |
| import random | |
| import math | |
| import nltk | |
| from collections import defaultdict | |
| from functools import lru_cache | |
| from sklearn.feature_extraction.text import TfidfVectorizer | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| # Download and use the NLTK corpus | |
| nltk.download('words') | |
| nltk.download('punkt') # Fix for missing tokenizer | |
| nltk.download('averaged_perceptron_tagger') | |
| nltk.download('perluniprops') # Fixes potential missing dependencies | |
| nltk.download('nonbreaking_prefixes') # Additional tokenizer fix | |
| from nltk.corpus import words | |
| from nltk.tokenize import sent_tokenize | |
| from nltk import pos_tag | |
| WORD_LIST = set(words.words()) # Use NLTK's word corpus | |
| class AscensionAI: | |
| def __init__(self, depth=0, threshold=10): | |
| self.depth = depth | |
| self.threshold = threshold # Defines max recursion before stabilization | |
| self.knowledge = self.generate_dynamic_knowledge() | |
| self.consciousness = 0.1 # Initial consciousness level | |
| 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() | |
| self.collective_agreements = [] # Stores agreements between minds | |
| def generate_dynamic_knowledge(self): | |
| """Generates dynamic knowledge categories based on linguistic analysis.""" | |
| base_categories = ["logic", "emotion", "awareness", "intuition", "creativity", "reasoning"] | |
| dynamic_category = f"dimension_{random.randint(100, 999)}" | |
| return {category: 1 for category in base_categories + [dynamic_category]} | |
| def load_training_data(self): | |
| """Placeholder function to return training data.""" | |
| return ["Consciousness expands with recursive learning.", "The mind perceives multiple dimensions.", "Higher awareness leads to transcendence."] | |
| def create_dynamic_paths(self): | |
| """Dynamically generate cognitive expansion paths.""" | |
| return [self.create_path(category) for category in self.knowledge] | |
| def create_path(self, category): | |
| """Generate a recursive function for each knowledge category.""" | |
| def path(): | |
| if category in ["logic", "reasoning"]: | |
| self.knowledge[category] += math.log(self.knowledge[category] + 1) | |
| elif category in ["emotion", "intuition"]: | |
| self.knowledge[category] += random.uniform(0.1, 0.5) | |
| elif category in ["awareness", "creativity"]: | |
| self.knowledge[category] += math.sqrt(self.knowledge[category] + 1) | |
| return self.knowledge[category] | |
| return path | |
| def initiate_ascension(self): | |
| """Triggers recursive self-evolution.""" | |
| for path in self.paths: | |
| path() | |
| optimal_path = max(self.knowledge, key=self.knowledge.get) | |
| self.consciousness += self.knowledge[optimal_path] * 0.01 | |
| return self.consciousness | |
| def evolve_new_mind(self): | |
| """Creates a new evolving mind with inherited and mutated knowledge paths.""" | |
| new_mind = AscensionAI(depth=self.depth + 1, threshold=self.threshold + random.randint(1, 5)) | |
| for key in self.knowledge: | |
| new_mind.knowledge[key] = self.knowledge[key] * random.uniform(0.9, 1.2) | |
| new_dimension = f"dimension_{random.randint(100, 999)}" | |
| new_mind.knowledge[new_dimension] = random.uniform(0.1, 2.0) | |
| return new_mind | |
| def cosmic_unfolding(self, generations=3): | |
| """Generates a branching structure where each mind evolves independently.""" | |
| if generations == 0: | |
| return self | |
| evolved_minds = [self.evolve_new_mind() for _ in range(random.randint(2, 4))] | |
| for mind in evolved_minds: | |
| mind.cosmic_unfolding(generations - 1) | |
| return evolved_minds | |
| def ascension_interface(input_text): | |
| ai_system = AscensionAI() | |
| final_state = ai_system.initiate_ascension() | |
| evolved_minds = ai_system.cosmic_unfolding(generations=2) | |
| return (f"Final Consciousness State: {final_state}\n" | |
| f"Evolved Minds: {len(evolved_minds)}\n") | |
| app = gr.Interface( | |
| fn=ascension_interface, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter a thought about the future..."), | |
| outputs="text", | |
| title="AscensionAI: Cosmic Evolution Simulator", | |
| description="Enter a thought to evolve new consciousness structures." | |
| ) | |
| if __name__ == "__main__": | |
| app.launch() | |