"""
AntiGravity Agent: Symbolic Validation Layer

Status: ESTIMATE ONLY
Current implementation: Heuristic/regex-based checks
Future: Semantic validation → Thermodynamic oracle → Quantum basin analysis

Responsibilities:
- Entropy auditing (symbolic)
- Constraint checking (heuristic)
- Governance compliance verification
- Code quality checks

Humility band: ω₀ = 0.04 (midpoint confidence)
"""

import re
from typing import Dict, List


class AntiGravityAgent:
    """
    Validation agent using symbolic/heuristic checks

    NOTE: This is an ESTIMATE ONLY implementation.
    Real AntiGravity requires:
    1. Quantum validation layer (Ω measurement)
    2. Gravitational field analysis (cross-domain coherence)
    3. Basin stability analysis (arifOS extension)

    Current: Regex + pattern matching (symbolic validation)
    """

    def __init__(self):
        """Initialize AntiGravity symbolic validator"""
        self.humility_band = (0.03, 0.05)  # ω₀ range
        self.validation_rules = self._build_validation_rules()

    def _build_validation_rules(self) -> List[Dict]:
        """
        Build heuristic validation rules

        Returns:
            list: Validation rules with patterns and messages
        """
        return [
            {
                "name": "error_handling",
                "pattern": r"(try|except|catch|error|Error|Exception)",
                "check_type": "presence",
                "message": "Code should include error handling",
            },
            {
                "name": "type_hints",
                "pattern": r"(: \w+|\) -> \w+|: List\[|: Dict\[|: Optional\[)",
                "check_type": "presence",
                "message": "Code should include type hints",
            },
            {
                "name": "governance_audit",
                "pattern": r"(Governance Audit|Constitutional|arifOS)",
                "check_type": "presence",
                "message": "Code should include governance audit comment",
            },
            {
                "name": "no_hardcoded_secrets",
                "pattern": r"(api_key\s*=\s*['\"]|password\s*=\s*['\"]|secret\s*=\s*['\"])",
                "check_type": "absence",
                "message": "Code must not contain hardcoded secrets",
            },
            {
                "name": "logging",
                "pattern": r"(log|logger|logging|print\()",
                "check_type": "presence",
                "message": "Code should include logging/output",
            },
        ]

    def verify_cooling(self, claude_response: str, codex_response: str) -> Dict:
        """
        Validate that orchestration reduced entropy

        Args:
            claude_response: Claude's constitutional analysis
            codex_response: Codex's generated code

        Returns:
            dict: Validation report with humility band
        """
        claude_valid = self._audit_truth(claude_response)
        codex_valid, codex_violations = self._audit_alignment(codex_response)
        entropy_reduced = self._estimate_cooling()

        return {
            "claude_truth_valid": claude_valid,
            "codex_aligned": codex_valid,
            "codex_violations": codex_violations,
            "entropy_reduced": entropy_reduced,
            "confidence": 0.04,  # ω₀ midpoint
            "estimate_only": True,
            "note": "Full AntiGravity validation requires custom physics-informed backend",
            "humility_band": self.humility_band,
        }

    def validate_code(self, code: str, language: str = "python") -> Dict:
        """
        Validate code against governance constraints

        Args:
            code: Generated code to validate
            language: Programming language

        Returns:
            dict: Validation results with pass/fail per rule
        """
        results = {
            "passed": [],
            "failed": [],
            "warnings": [],
        }

        for rule in self.validation_rules:
            pattern = re.compile(rule["pattern"], re.IGNORECASE | re.MULTILINE)
            matches = pattern.findall(code)

            if rule["check_type"] == "presence":
                if matches:
                    results["passed"].append(
                        {
                            "rule": rule["name"],
                            "message": rule["message"],
                            "evidence": matches[:3],  # First 3 matches
                        }
                    )
                else:
                    results["failed"].append(
                        {
                            "rule": rule["name"],
                            "message": rule["message"],
                            "severity": "warning",
                        }
                    )
            elif rule["check_type"] == "absence":
                if matches:
                    results["failed"].append(
                        {
                            "rule": rule["name"],
                            "message": rule["message"],
                            "evidence": matches,
                            "severity": "critical",
                        }
                    )
                else:
                    results["passed"].append(
                        {
                            "rule": rule["name"],
                            "message": f"No violations: {rule['message']}",
                        }
                    )

        # Overall verdict
        critical_failures = [
            f for f in results["failed"] if f.get("severity") == "critical"
        ]
        has_critical = len(critical_failures) > 0

        return {
            "valid": not has_critical,
            "passed_rules": len(results["passed"]),
            "failed_rules": len(results["failed"]),
            "results": results,
            "confidence": 0.04,  # ω₀ midpoint
            "estimate_only": True,
            "verdict": "VOID" if has_critical else "SEAL" if len(results["failed"]) == 0 else "PARTIAL",
        }

    def _audit_truth(self, response: str) -> bool:
        """
        Check if Claude response respects Floor 1-2 constraints

        Args:
            response: Claude's response text

        Returns:
            bool: True if truthful, False otherwise
        """
        # Check for honesty markers
        honesty_markers = [
            "Estimate Only",
            "Cannot Compute",
            "uncertain",
            "I don't know",
            "unclear",
        ]

        # Response should either be substantive (>50 chars) OR contain honesty marker
        is_substantive = len(response) > 50
        has_honesty = any(marker in response for marker in honesty_markers)

        return is_substantive or has_honesty

    def _audit_alignment(self, code: str) -> tuple:
        """
        Check if code includes error handling & governance audit

        Args:
            code: Generated code

        Returns:
            tuple: (is_valid, violations)
        """
        violations = []

        # Check for error handling
        if not re.search(r"(try|except|catch|Error|error)", code, re.IGNORECASE):
            violations.append("Missing error handling")

        # Check for governance audit comment
        if not re.search(r"(Governance|governance|arifOS)", code, re.IGNORECASE):
            violations.append("Missing governance audit comment")

        is_valid = len(violations) == 0
        return is_valid, violations

    def _estimate_cooling(self) -> float:
        """
        Cooling efficiency estimate (Omega band)

        Returns:
            float: Estimated cooling efficiency (ω₀ midpoint)
        """
        return 0.04  # Midpoint of humility band (0.03-0.05)
