"""Quantum-inspired reasoning implementations.""" import logging from typing import Dict, Any, List import json from .base import ReasoningStrategy class QuantumReasoning(ReasoningStrategy): """Implements quantum-inspired reasoning using superposition and entanglement principles.""" async def reason(self, query: str, context: Dict[str, Any]) -> Dict[str, Any]: try: # Create superposition of possibilities superposition = await self._create_superposition(query, context) # Analyze entanglements entanglements = await self._analyze_entanglements(superposition, context) # Perform quantum interference interference = await self._quantum_interference(superposition, entanglements, context) # Collapse to solution solution = await self._collapse_to_solution(interference, context) return { "success": True, "answer": solution["conclusion"], "superposition": superposition, "entanglements": entanglements, "interference_patterns": interference, "measurement": solution["measurement"], "confidence": solution["confidence"] } except Exception as e: return {"success": False, "error": str(e)} async def _create_superposition(self, query: str, context: Dict[str, Any]) -> List[Dict[str, Any]]: prompt = f""" Create superposition of possible solutions: Query: {query} Context: {json.dumps(context)} For each possibility state: 1. [State]: Description of possibility 2. [Amplitude]: Relative strength (0-1) 3. [Phase]: Relationship to other states 4. [Basis]: Underlying assumptions Format as: [S1] State: ... Amplitude: ... Phase: ... Basis: ... """ response = await context["groq_api"].predict(prompt) return self._parse_superposition(response["answer"]) async def _analyze_entanglements(self, superposition: List[Dict[str, Any]], context: Dict[str, Any]) -> List[Dict[str, Any]]: prompt = f""" Analyze entanglements between possibilities: Superposition: {json.dumps(superposition)} Context: {json.dumps(context)} For each entanglement describe: 1. [States]: Entangled states 2. [Type]: Nature of entanglement 3. [Strength]: Correlation strength 4. [Impact]: Effect on outcomes Format as: [E1] States: ... Type: ... Strength: ... Impact: ... """ response = await context["groq_api"].predict(prompt) return self._parse_entanglements(response["answer"]) async def _quantum_interference(self, superposition: List[Dict[str, Any]], entanglements: List[Dict[str, Any]], context: Dict[str, Any]) -> List[Dict[str, Any]]: prompt = f""" Calculate quantum interference patterns: Superposition: {json.dumps(superposition)} Entanglements: {json.dumps(entanglements)} Context: {json.dumps(context)} For each interference pattern: 1. [Pattern]: Description 2. [Amplitude]: Combined strength 3. [Phase]: Combined phase 4. [Effect]: Impact on solution space Format as: [I1] Pattern: ... Amplitude: ... Phase: ... Effect: ... """ response = await context["groq_api"].predict(prompt) return self._parse_interference(response["answer"]) async def _collapse_to_solution(self, interference: List[Dict[str, Any]], context: Dict[str, Any]) -> Dict[str, Any]: prompt = f""" Collapse quantum state to final solution: Interference: {json.dumps(interference)} Context: {json.dumps(context)} Provide: 1. Final measured state 2. Measurement confidence 3. Key quantum effects utilized 4. Overall conclusion 5. Confidence level (0-1) """ response = await context["groq_api"].predict(prompt) return self._parse_collapse(response["answer"]) def _parse_superposition(self, response: str) -> List[Dict[str, Any]]: """Parse superposition states from response.""" superposition = [] current_state = None for line in response.split('\n'): line = line.strip() if not line: continue if line.startswith('[S'): if current_state: superposition.append(current_state) current_state = { "state": "", "amplitude": 0.0, "phase": "", "basis": "" } elif current_state: if line.startswith('State:'): current_state["state"] = line[6:].strip() elif line.startswith('Amplitude:'): try: current_state["amplitude"] = float(line[10:].strip()) except: pass elif line.startswith('Phase:'): current_state["phase"] = line[6:].strip() elif line.startswith('Basis:'): current_state["basis"] = line[6:].strip() if current_state: superposition.append(current_state) return superposition def _parse_entanglements(self, response: str) -> List[Dict[str, Any]]: """Parse entanglements from response.""" entanglements = [] current_entanglement = None for line in response.split('\n'): line = line.strip() if not line: continue if line.startswith('[E'): if current_entanglement: entanglements.append(current_entanglement) current_entanglement = { "states": "", "type": "", "strength": 0.0, "impact": "" } elif current_entanglement: if line.startswith('States:'): current_entanglement["states"] = line[7:].strip() elif line.startswith('Type:'): current_entanglement["type"] = line[5:].strip() elif line.startswith('Strength:'): try: current_entanglement["strength"] = float(line[9:].strip()) except: pass elif line.startswith('Impact:'): current_entanglement["impact"] = line[7:].strip() if current_entanglement: entanglements.append(current_entanglement) return entanglements def _parse_interference(self, response: str) -> List[Dict[str, Any]]: """Parse interference patterns from response.""" interference = [] current_pattern = None for line in response.split('\n'): line = line.strip() if not line: continue if line.startswith('[I'): if current_pattern: interference.append(current_pattern) current_pattern = { "pattern": "", "amplitude": 0.0, "phase": "", "effect": "" } elif current_pattern: if line.startswith('Pattern:'): current_pattern["pattern"] = line[8:].strip() elif line.startswith('Amplitude:'): try: current_pattern["amplitude"] = float(line[10:].strip()) except: pass elif line.startswith('Phase:'): current_pattern["phase"] = line[6:].strip() elif line.startswith('Effect:'): current_pattern["effect"] = line[7:].strip() if current_pattern: interference.append(current_pattern) return interference def _parse_collapse(self, response: str) -> Dict[str, Any]: """Parse collapse to solution from response.""" collapse = { "measurement": "", "confidence": 0.0, "quantum_effects": [], "conclusion": "" } mode = None for line in response.split('\n'): line = line.strip() if not line: continue if line.startswith('Measurement:'): collapse["measurement"] = line[12:].strip() elif line.startswith('Confidence:'): try: collapse["confidence"] = float(line[11:].strip()) except: collapse["confidence"] = 0.5 elif line.startswith('Quantum Effects:'): mode = "effects" elif mode == "effects" and line.startswith('- '): collapse["quantum_effects"].append(line[2:].strip()) elif line.startswith('Conclusion:'): collapse["conclusion"] = line[11:].strip() return collapse class QuantumInspiredStrategy(ReasoningStrategy): """Implements Quantum-Inspired reasoning.""" async def reason(self, query: str, context: Dict[str, Any]) -> Dict[str, Any]: try: # Create a clean context for serialization clean_context = {k: v for k, v in context.items() if k != "groq_api"} prompt = f""" You are a meta-learning reasoning system that adapts its approach based on problem characteristics. Problem Type: Query: {query} Context: {json.dumps(clean_context)} Analyze this problem using meta-learning principles. Structure your response EXACTLY as follows: PROBLEM ANALYSIS: - [First key aspect or complexity factor] - [Second key aspect or complexity factor] - [Third key aspect or complexity factor] SOLUTION PATHS: - Path 1: [Specific solution approach] - Path 2: [Alternative solution approach] - Path 3: [Another alternative approach] META INSIGHTS: - Learning 1: [Key insight about the problem space] - Learning 2: [Key insight about solution approaches] - Learning 3: [Key insight about trade-offs] CONCLUSION: [Final synthesized solution incorporating meta-learnings] """ response = await context["groq_api"].predict(prompt) if not response["success"]: return response # Parse response into components lines = response["answer"].split("\n") problem_analysis = [] solution_paths = [] meta_insights = [] conclusion = "" section = None for line in lines: line = line.strip() if not line: continue if "PROBLEM ANALYSIS:" in line: section = "analysis" elif "SOLUTION PATHS:" in line: section = "paths" elif "META INSIGHTS:" in line: section = "insights" elif "CONCLUSION:" in line: section = "conclusion" elif line.startswith("-"): content = line.lstrip("- ").strip() if section == "analysis": problem_analysis.append(content) elif section == "paths": solution_paths.append(content) elif section == "insights": meta_insights.append(content) elif section == "conclusion": conclusion += line + " " return { "success": True, "problem_analysis": problem_analysis, "solution_paths": solution_paths, "meta_insights": meta_insights, "conclusion": conclusion.strip(), # Add standard fields for compatibility "reasoning_path": problem_analysis + solution_paths + meta_insights, "conclusion": conclusion.strip() } except Exception as e: return {"success": False, "error": str(e)}