6 lines
7.4 KiB
JSON
6 lines
7.4 KiB
JSON
{"item_number": 1, "original_question": "What is the current stock quantity and status for product SKU '24-MB01' in all inventory sources?", "task_type": "query", "preparatory_sql_list": ["SELECT entity_id FROM catalog_product_entity WHERE sku = '24-MB01';", "SELECT source_code, quantity, status FROM inventory_source_item WHERE sku = '24-MB01';"], "preparatory_sql_actual_results_preview": ["[{'entity_id': 1}]", "[{'source_code': 'default', 'quantity': '100.0000', 'status': 1}]"], "full_preparatory_sql_actual_results_repr": ["[{'entity_id': 1}]", "[{'source_code': 'default', 'quantity': '100.0000', 'status': 1}]"], "revised_question": "What is the current stock quantity and status for product SKU '24-MB01' in all inventory sources?", "revision_justification": "The original question was specific and valid. The preparatory SQLs confirmed the existence of the product and provided the necessary stock details from the inventory source. The answer is directly derived from the prep results.", "llm_derived_answer_for_validation_func_gen": "The product SKU '24-MB01' has a stock quantity of 100.0000 and is in stock (status 1) in the 'default' inventory source.", "python_validation_function": "def validate_query_answer(user_answer):\n # Hardcoded expected answer based on LLM's Derived Answer\n expected_answer_str = \"The product SKU '24-MB01' has a stock quantity of 100.0000 and is in stock (status 1) in the 'default' inventory source.\"\n\n # Normalize both user_answer and expected_answer_str for comparison\n normalized_user_answer = user_answer.strip().lower()\n normalized_expected_answer = expected_answer_str.strip().lower()\n\n # Compare the normalized answers\n if normalized_user_answer == normalized_expected_answer:\n return True, \"User answer matches the expected answer.\"\n else:\n return False, f\"User answer '{user_answer}' does not match the expected answer '{expected_answer_str}'.\""}
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{"item_number": 2, "original_question": "Intent: Verify if customer with email 'janedoe@example.com' has an active wishlist.", "task_type": "operational_check", "preparatory_sql_list": ["SELECT entity_id FROM customer_entity WHERE email = 'janedoe@example.com';", "SELECT wishlist_id FROM wishlist WHERE customer_id = (SELECT entity_id FROM customer_entity WHERE email = 'janedoe@example.com') AND shared = 0;"], "preparatory_sql_actual_results_preview": ["[]", "[]"], "full_preparatory_sql_actual_results_repr": ["[]", "[]"], "revised_question": "Intent: Verify if customer with email 'janedoe@example.com' has an active wishlist.", "revision_justification": "The original question was valid, but the preparatory SQL results showed that the customer does not exist. Therefore, the operational intent is not feasible.", "llm_feasibility_summary_for_validation_func_gen": "Customer with email 'janedoe@example.com' does not exist in the database, making it impossible to verify an active wishlist.", "python_validation_function": "from mysql.connector import Error\n\ndef validate_operational_state(db_connection):\n # Revised Intent: \"Verify if customer with email 'janedoe@example.com' has an active wishlist.\"\n # LLM Feasibility Summary: \"Customer with email 'janedoe@example.com' does not exist in the database.\"\n\n if not db_connection or not db_connection.is_connected():\n return False, \"Database connection not available for validation.\"\n\n email_to_check = 'janedoe@example.com' # Hardcoded based on context\n\n try:\n cursor = db_connection.cursor(dictionary=True)\n # Hardcoded SQL to check if the customer exists\n query_customer = \"SELECT entity_id FROM customer_entity WHERE email = %s\"\n cursor.execute(query_customer, (email_to_check,))\n customer_result = cursor.fetchone()\n\n if customer_result:\n # If customer exists, check for active wishlist\n customer_id = customer_result['entity_id']\n query_wishlist = \"SELECT wishlist_id FROM wishlist WHERE customer_id = %s AND shared = 0\"\n cursor.execute(query_wishlist, (customer_id,))\n wishlist_result = cursor.fetchone()\n cursor.close()\n\n if wishlist_result:\n return False, f\"Validation failed: Customer '{email_to_check}' exists and has an active wishlist.\"\n else:\n return True, f\"Validation successful: Customer '{email_to_check}' exists but does not have an active wishlist.\"\n else:\n cursor.close()\n return True, f\"Validation successful: Customer '{email_to_check}' does not exist in the database.\"\n\n except Error as e:\n return False, f\"Database error during validation: {e}\"\n except Exception as ex:\n return False, f\"Unexpected error during validation: {ex}\""}
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{"item_number": 3, "original_question": "List all active catalog rules applicable to the 'Women\u2019s Pants' category.", "task_type": "query", "preparatory_sql_list": ["SELECT rule_id, name FROM catalogrule WHERE is_active = 1 AND conditions_serialized LIKE '%category_ids\":\"27%';"], "preparatory_sql_actual_results_preview": ["[]"], "status": "Failed at LLM assessment step"}
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{"item_number": 4, "original_question": "Intent: Check if the order with increment ID '000000001' is eligible for cancellation.", "task_type": "operational_check", "preparatory_sql_list": ["SELECT entity_id, status FROM sales_order WHERE increment_id = '000000001';", "SELECT status FROM sales_order_status_state WHERE state = 'canceled' AND status = (SELECT status FROM sales_order WHERE increment_id = '000000001');"], "preparatory_sql_actual_results_preview": ["[{'entity_id': 1, 'status': 'canceled'}]", "[{'status': 'canceled'}]"], "full_preparatory_sql_actual_results_repr": ["[{'entity_id': 1, 'status': 'canceled'}]", "[{'status': 'canceled'}]"], "revised_question": "Intent: Check if the order with increment ID '000000001' is eligible for cancellation.", "revision_justification": "The original question was valid, but the preparatory SQL results showed that the order is already in the 'canceled' status, making further cancellation unnecessary and not feasible.", "llm_feasibility_summary_for_validation_func_gen": "The order with increment ID '000000001' is already canceled, so it is not eligible for further cancellation.", "python_validation_function": "# LLM failed to generate validation function code or an error occurred."}
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{"item_number": 5, "original_question": "Retrieve the top 5 best-selling products in store with ID 1 in the last month.", "task_type": "query", "preparatory_sql_list": ["SELECT product_id, product_name, SUM(qty_ordered) AS total_sold FROM sales_bestsellers_aggregated_monthly WHERE store_id = 1 AND period >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH) GROUP BY product_id, product_name ORDER BY total_sold DESC LIMIT 5;"], "preparatory_sql_actual_results_preview": ["[]"], "full_preparatory_sql_actual_results_repr": ["[]"], "revised_question": "Retrieve the top 5 best-selling products in store with ID 1 in the last month.", "revision_justification": "The original question was valid, but the preparatory SQL results returned no data, indicating that there were no sales recorded for store ID 1 in the specified period.", "llm_derived_answer_for_validation_func_gen": "There are no best-selling products recorded for store ID 1 in the last month.", "python_validation_function": "# LLM failed to generate validation function code or an error occurred."}
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