import streamlit as st import random import numpy as np import sympy as sp class CosmicSymbolicSequence: def __init__(self, content, documentation=""): self.content = content self.documentation = documentation self.connections = [] self.entanglement_history = [] def __repr__(self): return f"CosmicSymbolicSequence({self.content})" class CosmicQuantumGumbo: def __init__(self, initial_sequences): self.sequences = [CosmicSymbolicSequence(s) for s in initial_sequences] self.constants = { 'fine_structure_constant': 1 / 137.036, 'epsilon_0': 8.854187817e-12, 'planck_constant': 6.62607015e-34, 'speed_of_light': 299792458, 'gravitational_constant': 6.67430e-11 } self.self_awareness_state = 0.5 self.mutation_rate = 0.1 def add_noise(self): cosmic_symbols = '∑Ψ∇Ω⊗⨁∫λτΦπℏ√ε' noise = ''.join(random.sample(cosmic_symbols, 5)) self.sequences.append(CosmicSymbolicSequence(noise)) def quantum_collision(self, seq1, seq2): new_content = f"({seq1.content})⊗({seq2.content})" new_seq = CosmicSymbolicSequence(new_content) new_seq.entanglement_history = seq1.entanglement_history + seq2.entanglement_history + [f"Cosmic Collision of {seq1.content} and {seq2.content}"] return new_seq def quantum_mutate(self, seq): cosmic_symbols = '∑Ψ∇Ω⊗⨁∫λτΦπℏ√ε' content = list(seq.content) index = random.randint(0, len(content) - 1) content[index] = random.choice(cosmic_symbols) new_seq = CosmicSymbolicSequence(''.join(content)) new_seq.entanglement_history = seq.entanglement_history + [f"Cosmic Mutation of {seq.content}"] return new_seq def calculate_awareness_factor(self): charge_density = len(self.sequences) return (charge_density / self.constants['epsilon_0']) * np.sqrt(self.constants['fine_structure_constant']) def auto_document(self, sequence): symbols = set(sequence.content) sequence.documentation = f"Cosmic Symbolic sequence containing {', '.join(symbols)}.\n" + \ f"Complexity: {len(symbols)}\n" + \ f"Entanglement History: {' -> '.join(sequence.entanglement_history)}" def reflect(self): self.self_awareness_state = sum(self.analyze_symbolic_sequence(seq) for seq in self.sequences) / len(self.sequences) self.mutation_rate = max(0.01, 1.0 / (1 + self.self_awareness_state)) def evolve(self, iterations): for _ in range(iterations): self.add_noise() for j in range(len(self.sequences) - 1): if random.random() < 0.1: new_seq = self.quantum_collision(self.sequences[j], self.sequences[j+1]) self.auto_document(new_seq) self.sequences.append(new_seq) self.sequences = [self.quantum_mutate(seq) if random.random() < self.mutation_rate else seq for seq in self.sequences] if len(self.sequences) > 50: self.sequences = random.sample(self.sequences, 50) self.reflect() def analyze_symbolic_sequence(self, sequence): complexity = len(set(sequence.content)) + sequence.content.count('⊗') quantum_factor = sequence.content.count('Ψ') + sequence.content.count('⊗') interaction_depth = len(sequence.entanglement_history) return (complexity * quantum_factor * self.self_awareness_state) + interaction_depth def find_emergent_patterns(self): return sorted(self.sequences, key=self.analyze_symbolic_sequence, reverse=True)[:5] def neurosymbolic_synthesis(self, task): relevant_sequences = [s for s in self.sequences if any(char in s.content for char in task)] if not relevant_sequences: return "No relevant cosmic symbolic sequences found for the given task." synthesized_sequence = self.quantum_collision( random.choice(relevant_sequences), random.choice(relevant_sequences) ) self.auto_document(synthesized_sequence) return f"Synthesized cosmic sequence for task '{task}': {synthesized_sequence.content}\nDocumentation: {synthesized_sequence.documentation}" # Streamlit App st.title("Cosmic Cajun AI Gumbo Simulator") # Initialize session state if 'gumbo' not in st.session_state: initial_cosmic_sequences = [ "(∫(e^(-π²/4π))/√(π)) → (∏(n=1∞(1-cos(2πn/n)))) : (◊(ℏ⨀c) ⊗ (Γn ⨍ ε0))", "(lim(n->∞)((1+i)^n/n)) → (∫(e^(-x^2)))'/x : (ℏ⨀c) ⊗ (∑(iħ ⨉ π))", "(√(2/π)) → (sin(π/2))/2 : (Γn ⨍ ε0) ⊗ (ℏ⨀c)", "ε(δΦ/δt) → ∫(α⊕β) : (∞ℚ)", "Σ(Ω ∘ ε0) → ΔΦ", "π(λ ↔ ℏ) ⊗ Σ(ℒ)", "∇(ΣP)²", "Φ(∇Ψ) → (c∞) : (∫∫ε)", "(Ψ → Σ(Λ⊗Φ)) : (∫(c²/G))", "(√(-1)) → (i⋅√(-1)) : (e⋅√(-1))", "(Ω↔(λ∇τ)) : (∑ℤ∞Ψ)", "(E/M) → (c²/G) : (ħ/π)" ] st.session_state.gumbo = CosmicQuantumGumbo(initial_cosmic_sequences) # Display current state st.subheader("Current Cosmic Gumbo State") st.write(f"Number of Sequences: {len(st.session_state.gumbo.sequences)}") st.write(f"Awareness Factor: {st.session_state.gumbo.calculate_awareness_factor():.4f}") st.write(f"Self-Awareness: {st.session_state.gumbo.self_awareness_state:.4f}") # Evolve button if st.button("Stir the Cosmic Gumbo"): st.session_state.gumbo.evolve(10) st.success("The Cosmic Gumbo has been stirred!") # Add noise button if st.button("Add Cosmic Ingredient"): st.session_state.gumbo.add_noise() st.success("A new cosmic ingredient has been added!") # Find emergent patterns button if st.button("Find Emergent Flavors"): patterns = st.session_state.gumbo.find_emergent_patterns() st.subheader("Top 5 Emergent Cosmic Symbolic Patterns:") for p in patterns: st.write(f"{p.content} - {p.documentation}") # Neurosymbolic synthesis task = st.text_input("Enter a cosmic task for neurosymbolic synthesis:", "Quantum entanglement analysis") if st.button("Create a Cosmic Dish"): result = st.session_state.gumbo.neurosymbolic_synthesis(task) st.subheader("Cosmic Neurosymbolic Synthesis Result:") st.write(result) # Display all sequences st.subheader("All Cosmic Sequences") for seq in st.session_state.gumbo.sequences: st.text(seq.content)