"""Response Validator - Validate AI generated responses""" import re from typing import Dict, List, Optional, Tuple from dataclasses import dataclass from enum import Enum class ResponseQuality(Enum): """Response quality levels""" EXCELLENT = "excellent" GOOD = "good" ADEQUATE = "adequate" POOR = "poor" INVALID = "invalid" @dataclass class ValidationResult: """Validation result container""" quality: ResponseQuality score: float issues: List[str] suggestions: List[str] class ResponseValidator: """Validate AI generated code responses""" def __init__(self): self.min_code_length = 50 self.max_issues = 3 self.quality_threshold = 0.6 def validate(self, response: str, instruction: str) -> ValidationResult: """Validate response quality""" issues: List[str] = [] suggestions: List[str] = [] score = 1.0 if len(response) < self.min_code_length: issues.append("Response too short") score -= 0.3 if not self._contains_code(response): issues.append("No code block found in response") score -= 0.5 if not self._is_relevant(response, instruction): issues.append("Response may not address the instruction") score -= 0.2 if self._has_obvious_errors(response): issues.append("Potential errors detected in code") score -= 0.2 code_blocks = self._extract_code_blocks(response) for i, block in enumerate(code_blocks): if block_language := self._detect_language(block): lang_issues = self._check_language_specific(block, block_language) issues.extend([f"Block {i+1}: {issue}" for issue in lang_issues]) if not issues: suggestions.append("Response looks good!") else: suggestions.append("Consider adding more explanatory comments") quality = self._determine_quality(score, issues) return ValidationResult( quality=quality, score=max(0, score), issues=issues, suggestions=suggestions ) def _contains_code(self, response: str) -> bool: """Check if response contains code blocks""" return bool(re.search(r"```[\s\S]*?```", response)) def _is_relevant(self, response: str, instruction: str) -> bool: """Check if response is relevant to instruction""" instruction_words = set( re.findall(r"\b\w+\b", instruction.lower()) ) response_words = set(re.findall(r"\b\w+\b", response.lower())) overlap = instruction_words & response_words return len(overlap) >= min(3, len(instruction_words) * 0.3) def _has_obvious_errors(self, response: str) -> bool: """Check for obvious code errors""" error_patterns = [ r"undefined\s+variable", r"cannot\s+find\s+module", r"syntax\s+error", r"indentation\s+error", ] for pattern in error_patterns: if re.search(pattern, response, re.IGNORECASE): return True return False def _extract_code_blocks(self, response: str) -> List[str]: """Extract all code blocks from response""" pattern = r"```[\w]*\n?([\s\S]*?)```" matches = re.findall(pattern, response) return [match.strip() for match in matches] def _detect_language(self, code: str) -> Optional[str]: """Detect programming language from code""" language_signatures = { "python": [r"def\s+\w+\s*\(", r"import\s+\w+", r"if\s+__name__"], "javascript": [r"const\s+\w+", r"function\s+\w+\s*\(", r"=>\s*{"], "typescript": [r":\s*(string|number|boolean)\b", r"interface\s+\w+"], "java": [r"public\s+class\s+\w+", r"System\.out\.println"], "sql": [r"SELECT\s+.+\s+FROM", r"INSERT\s+INTO", r"CREATE\s+TABLE"], "bash": [r"#!/bin/bash", r"echo\s+", r"\$\w+"], } for lang, patterns in language_signatures.items(): if any(re.search(p, code) for p in patterns): return lang return None def _check_language_specific(self, code: str, language: str) -> List[str]: """Language-specific validation checks""" issues = [] if language == "python": if re.search(r"def\s+\w+\s*\([^)]*$", code): issues.append("Missing colon at end of function definition") if language == "javascript": if re.search(r"const\s+\w+\s*=\s*\w+\s*\+\s*['\"]\s*['\"]", code): issues.append("Empty string concatenation detected") return issues def _determine_quality( self, score: float, issues: List[str] ) -> ResponseQuality: """Determine response quality based on score and issues""" if score <= 0: return ResponseQuality.INVALID elif score >= 0.8 and len(issues) == 0: return ResponseQuality.EXCELLENT elif score >= 0.6: return ResponseQuality.GOOD elif score >= 0.4: return ResponseQuality.ADEQUATE else: return ResponseQuality.POOR def validate_multiple( self, responses: List[str], instruction: str ) -> List[ValidationResult]: """Validate multiple responses and rank them""" results = [self.validate(resp, instruction) for resp in responses] return sorted(results, key=lambda r: r.score, reverse=True)