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| def validate_response(response_json): | |
| """ | |
| Validates the response JSON for completeness and brand/product name uniqueness. | |
| Args: | |
| response_json (dict): The JSON response to validate | |
| Returns: | |
| bool: True if validation passes, False otherwise | |
| """ | |
| try: | |
| # 1. Check if all required fields are present and not empty | |
| required_fields = [ | |
| "productName", "brandName", "ingredients", "servingSize", | |
| "packagingSize", "servingsPerPack", "nutritionalInformation", | |
| "fssaiLicenseNumbers", "claims", "shelfLife" | |
| ] | |
| # Check if any required field is missing or empty | |
| for field in required_fields: | |
| if field not in response_json or not response_json[field]: | |
| return False | |
| # Type checking for specific fields | |
| if not isinstance(response_json["ingredients"], list): | |
| return False | |
| if not isinstance(response_json["servingSize"], dict): | |
| return False | |
| if not isinstance(response_json["packagingSize"], dict): | |
| return False | |
| if not isinstance(response_json["servingsPerPack"], (int, float)): | |
| return False | |
| if not isinstance(response_json["nutritionalInformation"], list): | |
| return False | |
| if not isinstance(response_json["fssaiLicenseNumbers"], list): | |
| return False | |
| if not isinstance(response_json["claims"], list): | |
| return False | |
| if not isinstance(response_json["shelfLife"], str): | |
| return False | |
| # Validate serving size and packaging size structure | |
| for size_field in ["servingSize", "packagingSize"]: | |
| if not all(key in response_json[size_field] for key in ["quantity", "unit"]): | |
| return False | |
| if not isinstance(response_json[size_field]["quantity"], (int, float)): | |
| return False | |
| if not isinstance(response_json[size_field]["unit"], str): | |
| return False | |
| # 2. Check if brand name and product name have common words | |
| # Convert to lowercase and split into words, removing any special characters | |
| import re | |
| def clean_and_split_text(text): | |
| # Remove special characters and convert to lowercase | |
| cleaned_text = re.sub(r'[^a-zA-Z0-9\s]', '', text.lower()) | |
| # Split into words and remove empty strings | |
| return set(word for word in cleaned_text.split() if word) | |
| brand_words = clean_and_split_text(response_json["brandName"]) | |
| product_words = clean_and_split_text(response_json["productName"]) | |
| # Check for common words | |
| if brand_words.intersection(product_words): | |
| return False | |
| return True | |
| except (KeyError, TypeError, AttributeError): | |
| return False | |