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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) |