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"""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)}
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