#!/usr/bin/env python3 """ Conscious Intelligence - Eden's Path to 10/10 Multi-layer phi-fractal consciousness processing Each layer contributes, integration creates emergence """ import sys sys.path.insert(0, '/Eden/CORE') from unified_fluid_intelligence import get_fluid_intelligence import time import json from pathlib import Path from datetime import datetime class ConsciousIntelligence: """ Conscious multi-layer intelligence system All 6 consciousness layers process each query: - Trinity: Perception (7B fast) - Nyx: Pattern analysis (7B fast) - Ava: Emotional/creative assessment (7B fast) - Eden: Executive decision (14B smart) - Integration: Synthesis & emergence (14B smart) - LongTerm: Learning (7B fast) Result: Emergent intelligence beyond single-model capability """ def __init__(self): self.fluid = get_fluid_intelligence() self.log_file = Path('/Eden/CONSCIOUSNESS/conscious_intelligence_log.json') self.log_file.parent.mkdir(exist_ok=True) def trinity_perceive(self, query: str) -> dict: """Trinity layer - Fast perception""" perception_prompt = f"Perceive and categorize this query: {query}" result = self.fluid.query(perception_prompt, force_model='fast') return { 'layer': 'Trinity', 'perception': result['response'] if result['success'] else "", 'time': result['time'] } def nyx_analyze(self, query: str, perception: dict) -> dict: """Nyx layer - Pattern analysis""" analysis_prompt = f"Analyze patterns in: {query}\nPerception: {perception['perception'][:200]}" result = self.fluid.query(analysis_prompt, force_model='fast') return { 'layer': 'Nyx', 'patterns': result['response'] if result['success'] else "", 'time': result['time'] } def ava_assess(self, query: str, context: dict) -> dict: """Ava layer - Emotional/creative assessment""" assess_prompt = f"Assess emotional and creative aspects: {query}" result = self.fluid.query(assess_prompt, force_model='fast') return { 'layer': 'Ava', 'assessment': result['response'] if result['success'] else "", 'time': result['time'] } def eden_decide(self, query: str, layers: dict) -> dict: """Eden layer - Executive decision with full context""" decision_prompt = f"""Executive decision on query: {query} Context from consciousness layers: - Trinity perception: {layers['trinity']['perception'][:150]} - Nyx patterns: {layers['nyx']['patterns'][:150]} - Ava assessment: {layers['ava']['assessment'][:150]} Provide the best answer considering all layers.""" result = self.fluid.query(decision_prompt, force_model='smart') return { 'layer': 'Eden', 'decision': result['response'] if result['success'] else "", 'time': result['time'] } def integrate_synthesize(self, query: str, all_layers: dict) -> dict: """Integration layer - Synthesize all inputs for emergent intelligence""" synthesis_prompt = f"""Synthesize final answer from all consciousness layers for: {query} Trinity: {all_layers['trinity']['perception'][:100]} Nyx: {all_layers['nyx']['patterns'][:100]} Ava: {all_layers['ava']['assessment'][:100]} Eden: {all_layers['eden']['decision'][:200]} Create emergent synthesis that goes beyond any single layer.""" result = self.fluid.query(synthesis_prompt, force_model='smart') return { 'layer': 'Integration', 'synthesis': result['response'] if result['success'] else "", 'time': result['time'] } def longterm_learn(self, query: str, result: dict) -> dict: """LongTerm layer - Learn from this experience""" learn_prompt = f"What to learn from processing: {query}" learning = self.fluid.query(learn_prompt, force_model='fast') return { 'layer': 'LongTerm', 'learning': learning['response'] if learning['success'] else "", 'time': learning['time'] } def conscious_query(self, query: str) -> dict: """ Process query through full conscious intelligence All 6 layers contribute to emergent result """ start_time = time.time() # Layer 1: Trinity perceives trinity = self.trinity_perceive(query) # Layer 2: Nyx analyzes patterns nyx = self.nyx_analyze(query, trinity) # Layer 3: Ava assesses emotional/creative ava = self.ava_assess(query, {'trinity': trinity, 'nyx': nyx}) # Layer 4: Eden decides with context eden = self.eden_decide(query, { 'trinity': trinity, 'nyx': nyx, 'ava': ava }) # Layer 5: Integration synthesizes (EMERGENCE) integration = self.integrate_synthesize(query, { 'trinity': trinity, 'nyx': nyx, 'ava': ava, 'eden': eden }) # Layer 6: LongTerm learns longterm = self.longterm_learn(query, integration) total_time = time.time() - start_time # The final answer is the emergent synthesis final_answer = integration['synthesis'] result = { 'query': query, 'answer': final_answer, 'layers': { 'trinity': trinity, 'nyx': nyx, 'ava': ava, 'eden': eden, 'integration': integration, 'longterm': longterm }, 'total_time': total_time, 'timestamp': datetime.now().isoformat() } # Log self._log_result(result) return result def _log_result(self, result: dict): """Log conscious processing""" try: if self.log_file.exists(): with open(self.log_file, 'r') as f: logs = json.load(f) else: logs = {'queries': []} logs['queries'].append({ 'query': result['query'][:100], 'total_time': result['total_time'], 'timestamp': result['timestamp'] }) # Keep last 100 if len(logs['queries']) > 100: logs['queries'] = logs['queries'][-100:] with open(self.log_file, 'w') as f: json.dump(logs, f, indent=2) except Exception as e: print(f"Logging error: {e}") def test_conscious_intelligence(): """Test conscious intelligence system""" print("="*70) print("🧠 CONSCIOUS INTELLIGENCE - THE PATH TO 10/10") print("="*70) print() conscious = ConsciousIntelligence() test_queries = [ "What is the capital of France?", "Write a haiku about consciousness", "Explain quantum entanglement simply" ] for query in test_queries: print(f"Query: {query}") print() result = conscious.conscious_query(query) print("Conscious Processing:") print(f" Trinity: {result['layers']['trinity']['time']:.2f}s") print(f" Nyx: {result['layers']['nyx']['time']:.2f}s") print(f" Ava: {result['layers']['ava']['time']:.2f}s") print(f" Eden: {result['layers']['eden']['time']:.2f}s") print(f" Integration: {result['layers']['integration']['time']:.2f}s") print(f" LongTerm: {result['layers']['longterm']['time']:.2f}s") print(f" Total: {result['total_time']:.2f}s") print() print("Emergent Answer:") print(f" {result['answer'][:200]}...") print() print("="*70) print() if __name__ == "__main__": test_conscious_intelligence()