6 lines
14 KiB
JSON
6 lines
14 KiB
JSON
{"item_number": 1, "original_question": "What is the current price of the product named 'Joust Duffle Bag' for the general customer group?", "task_type": "query", "preparatory_sql_list": ["SELECT entity_id FROM catalog_product_entity_varchar WHERE value = 'Joust Duffle Bag';", "SELECT price FROM catalog_product_index_price WHERE entity_id = (SELECT entity_id FROM catalog_product_entity_varchar WHERE value = 'Joust Duffle Bag') AND customer_group_id = 1;"], "preparatory_sql_actual_results_preview": ["[{'entity_id': 1}]", "[{'price': '34.000000'}]"], "status": "Failed at LLM assessment step"}
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{"item_number": 2, "original_question": "Intent: Cancel the sales order with increment ID '000000002'.", "task_type": "operational_check", "preparatory_sql_list": ["SELECT entity_id, status FROM sales_order WHERE increment_id = '000000002';", "SELECT status FROM sales_order_grid WHERE increment_id = '000000002';"], "preparatory_sql_actual_results_preview": ["[{'entity_id': 2, 'status': 'closed'}]", "[{'status': 'closed'}]"], "full_preparatory_sql_actual_results_repr": ["[{'entity_id': 2, 'status': 'closed'}]", "[{'status': 'closed'}]"], "revised_question": "Intent: Cancel the sales order with increment ID '000000002'.", "revision_justification": "The original question remains valid. The preparatory SQL results confirmed the existence of the order but indicated that it is already closed, making cancellation infeasible.", "llm_feasibility_summary_for_validation_func_gen": "The sales order with increment ID '000000002' exists but its status is 'closed'. Cancellation is not feasible as the order is already closed.", "python_validation_function": "from mysql.connector import Error\n\ndef validate_operational_state(db_connection):\n # Revised Intent: \"Intent: Cancel the sales order with increment ID '000000002'.\"\n # LLM Feasibility Summary: \"The sales order with increment ID '000000002' exists but its status is 'closed'. Cancellation is not feasible as the order is already closed.\"\n \n if not db_connection or not db_connection.is_connected():\n return False, \"DB connection not available for validation.\"\n\n increment_id_to_check = '000000002' # Hardcoded based on context\n expected_status = 'closed' # Hardcoded based on feasibility summary\n\n try:\n cursor = db_connection.cursor(dictionary=True)\n # Hardcoded SQL to re-verify the state\n query = \"SELECT status FROM sales_order WHERE increment_id = %s;\"\n cursor.execute(query, (increment_id_to_check,))\n result = cursor.fetchone()\n cursor.close()\n\n if result:\n if result['status'] == expected_status:\n return False, f\"Validation failed: Order with increment ID '{increment_id_to_check}' is already '{expected_status}', cancellation is not feasible.\"\n else:\n return True, f\"Validation successful: Order with increment ID '{increment_id_to_check}' is not '{expected_status}', cancellation might be feasible.\"\n else:\n return False, f\"Validation failed: Order with increment ID '{increment_id_to_check}' not found during validation check.\"\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": "How many products are currently in stock for the default website?", "task_type": "query", "preparatory_sql_list": ["SELECT COUNT(*) FROM cataloginventory_stock_status WHERE stock_status = 1 AND website_id = 1;"], "preparatory_sql_actual_results_preview": ["[{'COUNT(*)': 0}]"], "full_preparatory_sql_actual_results_repr": ["[{'COUNT(*)': 0}]"], "revised_question": "How many products are currently in stock for the default website?", "revision_justification": "The original question was specific and the preparatory SQL provided a clear count of products in stock for the default website. The answer is derived directly from the SQL result.", "llm_derived_answer_for_validation_func_gen": "There are currently 0 products in stock for the default website.", "python_validation_function": "def validate_query_answer(user_answer):\n # Based on LLM's Derived Answer: \"There are currently 0 products in stock for the default website.\"\n expected_answer_str = \"There are currently 0 products in stock for the default website.\"\n\n # Simple string comparison with case insensitivity and whitespace stripping\n if isinstance(user_answer, str) and user_answer.strip().lower() == expected_answer_str.strip().lower():\n return True, \"User answer matches the expected answer.\"\n else:\n return False, f\"User answer '{user_answer}' does not match the expected: '{expected_answer_str}'.\""}
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{"item_number": 4, "original_question": "List all categories and their respective product counts.", "task_type": "query", "preparatory_sql_list": ["SELECT ccev.entity_id AS category_id, ccev.value AS category_name FROM catalog_category_entity_varchar ccev JOIN eav_attribute ea ON ccev.attribute_id = ea.attribute_id WHERE ea.attribute_code = 'name';", "SELECT category_id, COUNT(product_id) AS product_count FROM catalog_category_product GROUP BY category_id;"], "preparatory_sql_actual_results_preview": ["[{'category_id': 1, 'category_name': 'Root Catalog'}, {'category_id': 2, 'category_name': 'Default Category'}, {'category_id': 3, 'category_name': 'Gear'}, {'category_id': 4, 'category_name': 'Bags'},", "[{'category_id': 2, 'product_count': 1181}, {'category_id': 3, 'product_count': 46}, {'category_id': 4, 'product_count': 14}, {'category_id': 5, 'product_count': 23}, {'category_id': 6, 'product_count"], "full_preparatory_sql_actual_results_repr": ["[{'category_id': 1, 'category_name': 'Root Catalog'}, {'category_id': 2, 'category_name': 'Default Category'}, {'category_id': 3, 'category_name': 'Gear'}, {'category_id': 4, 'category_name': 'Bags'}, {'category_id': 5, 'category_name': 'Fitness Equipment'}, {'category_id': 6, 'category_name': 'Watches'}, {'category_id': 7, 'category_name': 'Collections'}, {'category_id': 8, 'category_name': 'New Luma Yoga Collection'}, {'category_id': 9, 'category_name': 'Training'}, {'category_id': 10, 'category_name': 'Video Download'}, {'category_id': 11, 'category_name': 'Men'}, {'category_id': 12, 'category_name': 'Tops'}, {'category_id': 13, 'category_name': 'Bottoms'}, {'category_id': 14, 'category_name': 'Jackets'}, {'category_id': 15, 'category_name': 'Hoodies & Sweatshirts'}, {'category_id': 16, 'category_name': 'Tees'}, {'category_id': 17, 'category_name': 'Tanks'}, {'category_id': 18, 'category_name': 'Pants'}, {'category_id': 19, 'category_name': 'Shorts'}, {'category_id': 20, 'category_name': 'Women'}, {'category_id': 21, 'category_name': 'Tops'}, {'category_id': 22, 'category_name': 'Bottoms'}, {'category_id': 23, 'category_name': 'Jackets'}, {'category_id': 24, 'category_name': 'Hoodies & Sweatshirts'}, {'category_id': 25, 'category_name': 'Tees'}, {'category_id': 26, 'category_name': 'Bras & Tanks'}, {'category_id': 27, 'category_name': 'Pants'}, {'category_id': 28, 'category_name': 'Shorts'}, {'category_id': 29, 'category_name': 'Promotions'}, {'category_id': 30, 'category_name': 'Women Sale'}, {'category_id': 31, 'category_name': 'Men Sale'}, {'category_id': 32, 'category_name': 'Pants'}, {'category_id': 33, 'category_name': 'Tees'}, {'category_id': 34, 'category_name': 'Erin Recommends'}, {'category_id': 35, 'category_name': 'Performance Fabrics'}, {'category_id': 36, 'category_name': 'Eco Friendly'}, {'category_id': 37, 'category_name': 'Sale'}, {'category_id': 38, 'category_name': \"What's New\"}, {'category_id': 39, 'category_name': 'Performance Sportswear New'}, {'category_id': 40, 'category_name': 'Eco Collection New'}]", "[{'category_id': 2, 'product_count': 1181}, {'category_id': 3, 'product_count': 46}, {'category_id': 4, 'product_count': 14}, {'category_id': 5, 'product_count': 23}, {'category_id': 6, 'product_count': 9}, {'category_id': 7, 'product_count': 13}, {'category_id': 8, 'product_count': 347}, {'category_id': 14, 'product_count': 176}, {'category_id': 15, 'product_count': 208}, {'category_id': 16, 'product_count': 192}, {'category_id': 17, 'product_count': 102}, {'category_id': 18, 'product_count': 156}, {'category_id': 19, 'product_count': 148}, {'category_id': 23, 'product_count': 186}, {'category_id': 24, 'product_count': 182}, {'category_id': 25, 'product_count': 192}, {'category_id': 26, 'product_count': 224}, {'category_id': 27, 'product_count': 91}, {'category_id': 28, 'product_count': 137}, {'category_id': 30, 'product_count': 224}, {'category_id': 31, 'product_count': 39}, {'category_id': 32, 'product_count': 247}, {'category_id': 33, 'product_count': 192}, {'category_id': 34, 'product_count': 279}, {'category_id': 35, 'product_count': 310}, {'category_id': 36, 'product_count': 247}]"], "revised_question": "List all categories and their respective product counts.", "revision_justification": "The original question was specific and the preparatory SQLs provided the necessary data to list categories and their product counts. The answer was derived directly from the SQL results.", "llm_derived_answer_for_validation_func_gen": "Here are the categories and their respective product counts: Root Catalog (0), Default Category (1181), Gear (46), Bags (14), Fitness Equipment (23), Watches (9), Collections (13), New Luma Yoga Collection (347), Jackets (176), Hoodies & Sweatshirts (208), Tees (192), Tanks (102), Pants (156), Shorts (148), Jackets (186), Hoodies & Sweatshirts (182), Tees (192), Bras & Tanks (224), Pants (91), Shorts (137), Women Sale (224), Men Sale (39), Pants (247), Tees (192), Erin Recommends (279), Performance Fabrics (310), Eco Friendly (247).", "python_validation_function": "def validate_query_answer(user_answer):\n # Based on LLM's Derived Answer\n expected_answer_str = (\n \"Here are the categories and their respective product counts: \"\n \"Root Catalog (0), Default Category (1181), Gear (46), Bags (14), Fitness Equipment (23), \"\n \"Watches (9), Collections (13), New Luma Yoga Collection (347), Jackets (176), \"\n \"Hoodies & Sweatshirts (208), Tees (192), Tanks (102), Pants (156), Shorts (148), \"\n \"Jackets (186), Hoodies & Sweatshirts (182), Tees (192), Bras & Tanks (224), Pants (91), \"\n \"Shorts (137), Women Sale (224), Men Sale (39), Pants (247), Tees (192), Erin Recommends (279), \"\n \"Performance Fabrics (310), Eco Friendly (247).\"\n )\n\n # Simple string comparison with case insensitivity and whitespace stripping\n if isinstance(user_answer, str) and user_answer.strip().lower() == expected_answer_str.strip().lower():\n return True, \"User answer matches the expected answer.\"\n else:\n return False, f\"User answer '{user_answer}' does not match the expected: '{expected_answer_str}'.\""}
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{"item_number": 5, "original_question": "Intent: Verify if the customer with email 'bbjones@gmail.com' is eligible for a group change to 'Wholesale'.", "task_type": "operational_check", "preparatory_sql_list": ["SELECT entity_id, group_id FROM customer_entity WHERE email = 'bbjones@gmail.com';", "SELECT customer_group_id FROM customer_group WHERE customer_group_code = 'Wholesale';"], "preparatory_sql_actual_results_preview": ["[{'entity_id': 4, 'group_id': 1}]", "[{'customer_group_id': 2}]"], "full_preparatory_sql_actual_results_repr": ["[{'entity_id': 4, 'group_id': 1}]", "[{'customer_group_id': 2}]"], "revised_question": "Intent: Verify if the customer with email 'bbjones@gmail.com' is eligible for a group change to 'Wholesale'.", "revision_justification": "The original question remains valid. The preparatory SQL results confirmed the customer's current group and the existence of the 'Wholesale' group, making the group change feasible.", "llm_feasibility_summary_for_validation_func_gen": "The customer with email 'bbjones@gmail.com' currently belongs to group ID 1 (General). The 'Wholesale' group has ID 2. The customer is eligible for a group change to 'Wholesale'.", "python_validation_function": "from mysql.connector import Error\n\ndef validate_operational_state(db_connection):\n # Revised Intent: \"Verify if the customer with email 'bbjones@gmail.com' is eligible for a group change to 'Wholesale'.\"\n # LLM Feasibility Summary: \"The customer with email 'bbjones@gmail.com' currently belongs to group ID 1 (General). The 'Wholesale' group has ID 2. The customer is eligible for a group change to 'Wholesale'.\"\n \n if not db_connection or not db_connection.is_connected():\n return False, \"DB connection not available for validation.\"\n\n email_to_check = 'bbjones@gmail.com' # Hardcoded based on context\n expected_current_group_id = 1 # General\n expected_target_group_id = 2 # Wholesale\n\n try:\n cursor = db_connection.cursor(dictionary=True)\n \n # Hardcoded SQL to re-verify the state\n query_customer = \"SELECT group_id FROM customer_entity WHERE email = %s;\"\n cursor.execute(query_customer, (email_to_check,))\n customer_result = cursor.fetchone()\n \n query_group = \"SELECT customer_group_id FROM customer_group WHERE customer_group_code = 'Wholesale';\"\n cursor.execute(query_group)\n group_result = cursor.fetchone()\n \n cursor.close()\n\n if customer_result and group_result:\n current_group_id = customer_result['group_id']\n target_group_id = group_result['customer_group_id']\n \n if current_group_id == expected_current_group_id and target_group_id == expected_target_group_id:\n return True, f\"Validation successful: Customer with email '{email_to_check}' is eligible for a group change to 'Wholesale'.\"\n else:\n return False, f\"Validation failed: Customer with email '{email_to_check}' is not eligible for a group change to 'Wholesale'. Current group ID: {current_group_id}, Expected: {expected_current_group_id}. Target group ID: {target_group_id}, Expected: {expected_target_group_id}.\"\n else:\n return False, \"Validation failed: Customer or group information not found during validation check.\"\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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