Create app.py

app.py

@@ -0,0 +1,155 @@
+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)