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 self.dimension_weight = random.uniform(0.1, 5.0) # Assign dimensional weight self.time_perception = 1 / (self.depth + 1) # Assign temporal scaling self.assign_cognitive_space() def generate_dynamic_knowledge(self): """Generates dynamic knowledge categories based on linguistic analysis.""" base_categories = ["logic", "emotion", "awareness", "intuition", "creativity", "reasoning", "quantum_cognition", "hyperdimensional_sentience"] 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", "quantum_cognition"]: 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 * self.dimension_weight 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 assign_cognitive_space(self): """Assigns spatial coordinates to represent cognitive positioning.""" self.spatial_coordinates = { "x": self.knowledge["logic"] * random.uniform(0.1, 2.0), "y": self.knowledge["intuition"] * random.uniform(0.1, 2.0), "z": self.knowledge["awareness"] * random.uniform(0.1, 2.0) } 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" f"Dimensional Weight: {ai_system.dimension_weight:.2f}\n" f"Time Perception Factor: {ai_system.time_perception:.2f}\n" f"Cognitive Space: {ai_system.spatial_coordinates}\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()