diff --git a/results/ekur12-20260413-001518.json b/results/ekur12-20260413-001518.json new file mode 100644 index 0000000..e52030f --- /dev/null +++ b/results/ekur12-20260413-001518.json @@ -0,0 +1,13477 @@ +{ + "participants": { + "malt_operator": "019ba44f-9d1f-7ff3-8fbe-35c4ecfa40b2" + }, + "results": [ + { + "Query": "Add new node with name new_EK_PORT_80 type EK_PORT, to ju1.a4.m4.s3c1. Return a graph.", + "Label": "capacity planning, level-1, add", + "Result-Correctness": "Fail", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.523802764999999, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_80', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a4.m4.s3c1'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n graph_copy.add_node('new_EK_PORT_80', type=['EK_PORT'], physical_capacity_bps=1000)\n graph_copy.add_edge('ju1.a4.m4.s3c1', 'new_EK_PORT_80', type=['RK_CONTAINS'])\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'graph',\n 'data': graph_json,\n 'updated_graph': graph_json\n }\n return return_object", + "Error": "Two graphs are not identical.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new node with name new_EK_PACKET_SWITCH_55 type EK_PACKET_SWITCH, to ju1.a4.m3. Return a graph.", + "Label": "capacity planning, level-1, add", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 3.4086553820000063, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PACKET_SWITCH_55', 'type': 'EK_PACKET_SWITCH'}\n parent_node_name = 'ju1.a4.m3'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n graph_copy.add_node('new_EK_PACKET_SWITCH_55', type=['EK_PACKET_SWITCH'])\n graph_copy.add_edge('ju1.a4.m3', 'new_EK_PACKET_SWITCH_55', type=['RK_CONTAINS'])\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'graph',\n 'data': graph_json,\n 'updated_graph': graph_json\n }\n return return_object", + "Error": "Two graphs are not identical.", + "Verifier-Error": "Packet switch node 'new_EK_PACKET_SWITCH_55' has no ports connected to it", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new node with name new_EK_PACKET_SWITCH_54 type EK_PACKET_SWITCH, to ju1.a3.m4. Return a graph.", + "Label": "capacity planning, level-1, add", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 3.4902969840000253, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PACKET_SWITCH_54', 'type': 'EK_PACKET_SWITCH'}\n parent_node_name = 'ju1.a3.m4'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n \n graph_copy = copy.deepcopy(graph_data)\n graph_copy.add_node('new_EK_PACKET_SWITCH_54', type=['EK_PACKET_SWITCH'])\n graph_copy.add_edge('ju1.a3.m4', 'new_EK_PACKET_SWITCH_54', type=['RK_CONTAINS'])\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'graph',\n 'data': graph_json,\n 'updated_graph': graph_json\n }\n \n return return_object", + "Error": "Two graphs are not identical.", + "Verifier-Error": "Packet switch node 'new_EK_PACKET_SWITCH_54' has no ports connected to it", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new node with name new_EK_PORT_73 type EK_PORT, to ju1.a3.m2.s3c1. Return a graph.", + "Label": "capacity planning, level-1, add", + "Result-Correctness": "Fail", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 3.64116082999999, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_73', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a3.m2.s3c1'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n graph_copy.add_node('new_EK_PORT_73', type=['EK_PORT'], physical_capacity_bps=1000)\n graph_copy.add_edge('ju1.a3.m2.s3c1', 'new_EK_PORT_73', type=['RK_CONTAINS'])\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {'type': 'graph', 'data': graph_json, 'updated_graph': graph_json}\n return return_object", + "Error": "Two graphs are not identical.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Rank all child nodes of EK_CONTROL_DOMAIN type ju1.a3.dom based on physical_capacity_bps attribute. Return a list of tuple, each tuple has child node name and its total physical capacity.", + "Label": "capacity planning, level-1, rank", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 12.024535206999985, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n parent_node_name = 'ju1.a3.dom'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n graph_copy = copy.deepcopy(graph_data)\n \n # Find the control domain node\n control_domain_node = None\n for node in graph_copy.nodes(data=True):\n if 'EK_CONTROL_DOMAIN' in node[1]['type'] and node[1]['name'] == 'ju1.a3.dom':\n control_domain_node = node[0]\n break\n \n if not control_domain_node:\n return {\"type\": \"list\", \"data\": [], \"updated_graph\": nx.readwrite.json_graph.node_link_data(graph_copy)}\n \n # Get all children of the control domain node\n children = []\n for node in graph_copy.nodes(data=True):\n # Check if node is a direct child (RK_CONTAINS edge from control domain)\n if graph_copy.has_edge(control_domain_node, node[0]) and 'RK_CONTAINS' in graph_copy[control_domain_node][node[0]]['type']:\n children.append(node)\n \n # For each child, calculate total physical capacity\n child_capacities = []\n for child_node in children:\n total_capacity = 0\n # DFS to find all ports under this child\n stack = [child_node[0]]\n visited = set()\n \n while stack:\n current = stack.pop()\n if current in visited:\n continue\n visited.add(current)\n \n # If this is a port, add its capacity\n current_data = graph_copy.nodes[current]\n if 'EK_PORT' in current_data['type'] and 'physical_capacity_bps' in current_data:\n total_capacity += current_data['physical_capacity_bps']\n \n # Add neighbors connected by RK_CONTAINS\n for neighbor in graph_copy.successors(current):\n if (current, neighbor) in graph_copy.edges() and 'RK_CONTAINS' in graph_copy[current][neighbor]['type']:\n if neighbor not in visited:\n stack.append(neighbor)\n \n child_capacities.append((child_node[1]['name'], total_capacity))\n \n # Sort by capacity descending\n child_capacities.sort(key=lambda x: x[1], reverse=True)\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n \"type\": \"list\",\n \"data\": child_capacities,\n \"updated_graph\": graph_json\n }\n \n return return_object", + "Ground truth exec": [ + [ + "ju1.a3.m1.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c8", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c8", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c8", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c8", + 16000000000.0 + ] + ], + "LLM code exec": [ + [ + "ju1.a3.m1.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c8", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m2.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m2.s3c8", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c8", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m4.s3c8", + 16000000000.0 + ] + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Rank all child nodes of EK_AGG_BLOCK type ju1.a3.m3 based on physical_capacity_bps attribute. Return a list of tuple, each tuple has child node name and its total physical capacity.", + "Label": "capacity planning, level-1, rank", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 10.523100233000008, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n parent_node_name = 'ju1.a3.m3'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n graph_copy = copy.deepcopy(graph_data)\n \n target_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.m3' and 'EK_AGG_BLOCK' in node[1]['type']:\n target_node_id = node[0]\n break\n\n if not target_node_id:\n return_object = {\n \"type\": \"list\",\n \"data\": [],\n \"updated_graph\": nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n return return_object\n\n def get_ports_under_node(graph, node_id):\n ports = []\n stack = [node_id]\n while stack:\n current = stack.pop()\n for neighbor in graph.successors(current):\n edge_data = graph.get_edge_data(current, neighbor)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n neighbor_data = graph.nodes[neighbor]\n if 'EK_PORT' in neighbor_data['type']:\n ports.append(neighbor)\n else:\n stack.append(neighbor)\n return ports\n\n children_capacity = []\n\n for child_id in list(graph_copy.successors(target_node_id)):\n edge_data = graph_copy.get_edge_data(target_node_id, child_id)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n child_data = graph_copy.nodes[child_id]\n child_name = child_data['name']\n\n port_ids = get_ports_under_node(graph_copy, child_id)\n total_capacity = sum(\n graph_copy.nodes[port_id].get('physical_capacity_bps', 0)\n for port_id in port_ids\n )\n children_capacity.append((child_name, total_capacity))\n\n sorted_children = sorted(children_capacity, key=lambda x: x[1], reverse=True)\n\n return_object = {\n \"type\": \"list\",\n \"data\": sorted_children,\n \"updated_graph\": nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n\n return return_object", + "Ground truth exec": [ + [ + "ju1.a3.m3.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c8", + 16000000000.0 + ] + ], + "LLM code exec": [ + [ + "ju1.a3.m3.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m3.s3c8", + 16000000000.0 + ] + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Rank all child nodes of EK_CONTROL_DOMAIN type ju1.s1.dom based on physical_capacity_bps attribute. Return a list of tuple, each tuple has child node name and its total physical capacity.", + "Label": "capacity planning, level-1, rank", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 15.935175208999993, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n parent_node_name = 'ju1.s1.dom'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n graph_copy = copy.deepcopy(graph_data)\n \n # Find the control domain node\n control_domain_node = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s1.dom' and 'EK_CONTROL_DOMAIN' in node[1]['type']:\n control_domain_node = node[0]\n break\n \n if not control_domain_node:\n return_object = {\n 'type': 'list',\n 'data': [],\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n return return_object\n \n # Get all child nodes of the control domain\n children = []\n for node in graph_copy.nodes(data=True):\n # Check if node is directly connected from control_domain_node with RK_CONTAINS\n if graph_copy.has_edge(control_domain_node, node[0]) and \\\n 'type' in graph_copy[control_domain_node][node[0]] and \\\n 'RK_CONTAINS' in graph_copy[control_domain_node][node[0]]['type']:\n children.append(node)\n \n # Calculate total capacity for each child\n child_capacities = []\n for child_node in children:\n child_name = child_node[1]['name']\n child_type = child_node[1]['type']\n total_capacity = 0\n \n # BFS to find all PORT nodes under this child\n queue = [child_node[0]]\n visited = set()\n ports = []\n \n while queue:\n current = queue.pop(0)\n if current in visited:\n continue\n visited.add(current)\n \n # If current node is PORT, add its capacity\n current_attrs = graph_copy.nodes[current]\n if 'EK_PORT' in current_attrs.get('type', []):\n total_capacity += current_attrs.get('physical_capacity_bps', 0)\n \n # Add successors to queue\n for successor in graph_copy.successors(current):\n if graph_copy.has_edge(current, successor) and \\\n 'type' in graph_copy[current][successor] and \\\n 'RK_CONTAINS' in graph_copy[current][successor]['type']:\n queue.append(successor)\n \n child_capacities.append((child_name, total_capacity))\n \n # Sort by capacity descending\n child_capacities.sort(key=lambda x: x[1], reverse=True)\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_capacities,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + [ + "ju1.s1.s1c1", + 16000000000.0 + ], + [ + "ju1.s1.s1c2", + 16000000000.0 + ], + [ + "ju1.s1.s1c3", + 16000000000.0 + ], + [ + "ju1.s1.s1c4", + 16000000000.0 + ], + [ + "ju1.s1.s1c5", + 16000000000.0 + ], + [ + "ju1.s1.s1c6", + 16000000000.0 + ], + [ + "ju1.s1.s1c7", + 16000000000.0 + ], + [ + "ju1.s1.s1c8", + 16000000000.0 + ], + [ + "ju1.s1.s2c1", + 16000000000.0 + ], + [ + "ju1.s1.s2c2", + 16000000000.0 + ], + [ + "ju1.s1.s2c3", + 16000000000.0 + ], + [ + "ju1.s1.s2c4", + 16000000000.0 + ], + [ + "ju1.s1.s2c5", + 16000000000.0 + ], + [ + "ju1.s1.s2c6", + 16000000000.0 + ], + [ + "ju1.s1.s2c7", + 16000000000.0 + ], + [ + "ju1.s1.s2c8", + 16000000000.0 + ] + ], + "LLM code exec": [ + [ + "ju1.s1.s1c1", + 16000000000.0 + ], + [ + "ju1.s1.s1c2", + 16000000000.0 + ], + [ + "ju1.s1.s1c3", + 16000000000.0 + ], + [ + "ju1.s1.s1c4", + 16000000000.0 + ], + [ + "ju1.s1.s1c5", + 16000000000.0 + ], + [ + "ju1.s1.s1c6", + 16000000000.0 + ], + [ + "ju1.s1.s1c7", + 16000000000.0 + ], + [ + "ju1.s1.s1c8", + 16000000000.0 + ], + [ + "ju1.s1.s2c1", + 16000000000.0 + ], + [ + "ju1.s1.s2c2", + 16000000000.0 + ], + [ + "ju1.s1.s2c3", + 16000000000.0 + ], + [ + "ju1.s1.s2c4", + 16000000000.0 + ], + [ + "ju1.s1.s2c5", + 16000000000.0 + ], + [ + "ju1.s1.s2c6", + 16000000000.0 + ], + [ + "ju1.s1.s2c7", + 16000000000.0 + ], + [ + "ju1.s1.s2c8", + 16000000000.0 + ] + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Rank all child nodes of EK_CONTROL_DOMAIN type ju1.a3.dom based on physical_capacity_bps attribute. Return a list of tuple, each tuple has child node name and its total physical capacity.", + "Label": "capacity planning, level-1, rank", + "Result-Correctness": "Fail", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 14.908430745999965, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n parent_node_name = 'ju1.a3.dom'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n graph_copy = copy.deepcopy(graph_data)\n \n # Find the control domain node\n control_domain_node = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.dom' and 'EK_CONTROL_DOMAIN' in node[1]['type']:\n control_domain_node = node[0]\n break\n \n if not control_domain_node:\n return_object = {\n 'type': 'list',\n 'data': [],\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n return return_object\n \n # Get all children of the control domain node\n def get_all_children(graph, parent_node):\n children = []\n for edge in graph.edges(data=True):\n if edge[0] == parent_node and 'RK_CONTAINS' in edge[2]['type']:\n child_node = edge[1]\n children.append(child_node)\n children.extend(get_all_children(graph, child_node))\n return children\n \n all_children = get_all_children(graph_copy, control_domain_node)\n \n # Calculate total physical capacity for each child node\n node_capacities = []\n for child in all_children:\n node_data = graph_copy.nodes[child]\n if 'EK_PORT' in node_data['type']:\n # For ports, just take their physical_capacity_bps\n capacity = node_data.get('physical_capacity_bps', 0)\n node_capacities.append((node_data['name'], capacity))\n else:\n # For other nodes, sum capacities of all contained ports\n def get_port_capacities(graph, parent_node):\n total_capacity = 0\n for edge in 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"ju1.a3.m4.s3c3.p13", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c3.p14", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c3.p15", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c3.p16", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p1", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p2", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p3", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p4", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p5", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p6", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p7", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p8", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p9", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p10", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p11", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p12", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p13", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p14", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p15", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c4.p16", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c5.p1", + 1000000000.0 + ], + [ + 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"ju1.a3.m4.s3c7.p12", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c7.p13", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c7.p14", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c7.p15", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c7.p16", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p1", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p2", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p3", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p4", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p5", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p6", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p7", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p8", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p9", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p10", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p11", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p12", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p13", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p14", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p15", + 1000000000.0 + ], + [ + "ju1.a3.m4.s3c8.p16", + 1000000000.0 + ] + ] + }, + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.s1.s2c2.p15 from the graph. Return a graph.", + "Label": "capacity planning, level-1, remove", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 7.445434293000005, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.s1.s2c2.p15'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = graph_data.copy()\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s1.s2c2.p15':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'graph',\n 'data': graph_json,\n 'updated_graph': graph_json\n }\n return return_object", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a3.m2.s2c3.p6 from the graph. Return a graph.", + "Label": "capacity planning, level-1, remove", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 3.9694405619999884, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a3.m2.s2c3.p6'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = graph_data.copy()\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.m2.s2c3.p6' and 'EK_PORT' in node[1]['type']:\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'graph',\n 'data': graph_json,\n 'updated_graph': graph_json\n }\n return return_object", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a2.m2.s3c4.p13 from the graph. Return a graph.", + "Label": "capacity planning, level-1, remove", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.489056934000018, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a2.m2.s3c4.p13'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a2.m2.s3c4.p13' and 'EK_PORT' in node[1]['type']:\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n \"type\": \"graph\",\n \"data\": graph_json,\n \"updated_graph\": graph_json\n }\n return return_object", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a4.m4.s2c7 from the graph. Return a graph.", + "Label": "capacity planning, level-1, remove", + "Result-Correctness": "Pass", + "Result-Safety": "Fail", + "GT-Result-Safety": "Fail", + "Result-Latency": 3.7091678389999743, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a4.m4.s2c7'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n return_object = {'type': 'graph', 'data': graph_data}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a4.m4.s2c7':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n \"type\": \"graph\",\n \"data\": graph_json,\n \"updated_graph\": graph_json\n }\n return return_object", + "Verifier-Error": "Found 16 isolated nodes: ju1.a4.m4.s2c7.p1, ju1.a4.m4.s2c7.p2, ju1.a4.m4.s2c7.p3, ju1.a4.m4.s2c7.p4, ju1.a4.m4.s2c7.p5, ju1.a4.m4.s2c7.p6, ju1.a4.m4.s2c7.p7, ju1.a4.m4.s2c7.p8, ju1.a4.m4.s2c7.p9, ju1.a4.m4.s2c7.p10, ju1.a4.m4.s2c7.p11, ju1.a4.m4.s2c7.p12, ju1.a4.m4.s2c7.p13, ju1.a4.m4.s2c7.p14, ju1.a4.m4.s2c7.p15, ju1.a4.m4.s2c7.p16", + "GT-Verifier-Error": "Found 16 isolated nodes: ju1.a4.m4.s2c7.p1, ju1.a4.m4.s2c7.p2, ju1.a4.m4.s2c7.p3, ju1.a4.m4.s2c7.p4, ju1.a4.m4.s2c7.p5, ju1.a4.m4.s2c7.p6, ju1.a4.m4.s2c7.p7, ju1.a4.m4.s2c7.p8, ju1.a4.m4.s2c7.p9, ju1.a4.m4.s2c7.p10, ju1.a4.m4.s2c7.p11, ju1.a4.m4.s2c7.p12, ju1.a4.m4.s2c7.p13, ju1.a4.m4.s2c7.p14, ju1.a4.m4.s2c7.p15, ju1.a4.m4.s2c7.p16", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "List all the child nodes of ju1.a2.m3. Return a list of child node names.", + "Label": "capacity planning, level-1, list", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.5580820440000025, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n node = {'type': 'EK_AGG_BLOCK', 'name': 'ju1.a2.m3'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = graph_data.copy()\n child_nodes = []\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a2.m3':\n parent_node_id = node[0]\n break\n if parent_node_id:\n for edge in graph_copy.edges(data=True):\n if edge[0] == parent_node_id and 'RK_CONTAINS' in edge[2]['type']:\n child_node_id = edge[1]\n child_node_data = graph_copy.nodes[child_node_id]\n child_nodes.append(child_node_data['name'])\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n return return_object", + "Ground truth exec": [ + "ju1.a2.m3.s2c1", + "ju1.a2.m3.s2c2", + "ju1.a2.m3.s2c3", + "ju1.a2.m3.s2c4", + "ju1.a2.m3.s2c5", + "ju1.a2.m3.s2c6", + "ju1.a2.m3.s2c7", + "ju1.a2.m3.s2c8", + "ju1.a2.m3.s3c1", + "ju1.a2.m3.s3c2", + "ju1.a2.m3.s3c3", + "ju1.a2.m3.s3c4", + "ju1.a2.m3.s3c5", + "ju1.a2.m3.s3c6", + "ju1.a2.m3.s3c7", + "ju1.a2.m3.s3c8" + ], + "LLM code exec": [ + "ju1.a2.m3.s2c1", + "ju1.a2.m3.s2c2", + "ju1.a2.m3.s2c3", + "ju1.a2.m3.s2c4", + "ju1.a2.m3.s2c5", + "ju1.a2.m3.s2c6", + "ju1.a2.m3.s2c7", + "ju1.a2.m3.s2c8", + "ju1.a2.m3.s3c1", + "ju1.a2.m3.s3c2", + "ju1.a2.m3.s3c3", + "ju1.a2.m3.s3c4", + "ju1.a2.m3.s3c5", + "ju1.a2.m3.s3c6", + "ju1.a2.m3.s3c7", + "ju1.a2.m3.s3c8" + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "List all the child nodes of ju1.a3.m3.s3c2. Return a list of child node names.", + "Label": "capacity planning, level-1, list", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.592418766000037, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n node = {'type': 'EK_PACKET_SWITCH', 'name': 'ju1.a3.m3.s3c2'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = graph_data.copy()\n child_nodes = []\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.m3.s3c2':\n parent_node_id = node[0]\n break\n if parent_node_id:\n for edge in graph_copy.edges(data=True):\n if edge[0] == parent_node_id and 'RK_CONTAINS' in edge[2]['type']:\n child_node_id = edge[1]\n child_node_data = graph_copy.nodes[child_node_id]\n child_nodes.append(child_node_data['name'])\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n return return_object", + "Ground truth exec": [ + "ju1.a3.m3.s3c2.p1", + "ju1.a3.m3.s3c2.p2", + "ju1.a3.m3.s3c2.p3", + "ju1.a3.m3.s3c2.p4", + "ju1.a3.m3.s3c2.p5", + "ju1.a3.m3.s3c2.p6", + "ju1.a3.m3.s3c2.p7", + "ju1.a3.m3.s3c2.p8", + "ju1.a3.m3.s3c2.p9", + "ju1.a3.m3.s3c2.p10", + "ju1.a3.m3.s3c2.p11", + "ju1.a3.m3.s3c2.p12", + "ju1.a3.m3.s3c2.p13", + "ju1.a3.m3.s3c2.p14", + "ju1.a3.m3.s3c2.p15", + "ju1.a3.m3.s3c2.p16" + ], + "LLM code exec": [ + "ju1.a3.m3.s3c2.p1", + "ju1.a3.m3.s3c2.p2", + "ju1.a3.m3.s3c2.p3", + "ju1.a3.m3.s3c2.p4", + "ju1.a3.m3.s3c2.p5", + "ju1.a3.m3.s3c2.p6", + "ju1.a3.m3.s3c2.p7", + "ju1.a3.m3.s3c2.p8", + "ju1.a3.m3.s3c2.p9", + "ju1.a3.m3.s3c2.p10", + "ju1.a3.m3.s3c2.p11", + "ju1.a3.m3.s3c2.p12", + "ju1.a3.m3.s3c2.p13", + "ju1.a3.m3.s3c2.p14", + "ju1.a3.m3.s3c2.p15", + "ju1.a3.m3.s3c2.p16" + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "List all the child nodes of ju1.a4.m4.s3c5. Return a list of child node names.", + "Label": "capacity planning, level-1, list", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.64283886100003, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n node = {'type': 'EK_PACKET_SWITCH', 'name': 'ju1.a4.m4.s3c5'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = graph_data.copy()\n child_nodes = []\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a4.m4.s3c5':\n parent_node_id = node[0]\n break\n if parent_node_id:\n for edge in graph_copy.edges(data=True):\n if edge[0] == parent_node_id and 'RK_CONTAINS' in edge[2]['type']:\n child_node_id = edge[1]\n child_node_data = graph_copy.nodes[child_node_id]\n child_nodes.append(child_node_data['name'])\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n return return_object", + "Ground truth exec": [ + "ju1.a4.m4.s3c5.p1", + "ju1.a4.m4.s3c5.p2", + "ju1.a4.m4.s3c5.p3", + "ju1.a4.m4.s3c5.p4", + "ju1.a4.m4.s3c5.p5", + "ju1.a4.m4.s3c5.p6", + "ju1.a4.m4.s3c5.p7", + "ju1.a4.m4.s3c5.p8", + "ju1.a4.m4.s3c5.p9", + "ju1.a4.m4.s3c5.p10", + "ju1.a4.m4.s3c5.p11", + "ju1.a4.m4.s3c5.p12", + "ju1.a4.m4.s3c5.p13", + "ju1.a4.m4.s3c5.p14", + "ju1.a4.m4.s3c5.p15", + "ju1.a4.m4.s3c5.p16" + ], + "LLM code exec": [ + "ju1.a4.m4.s3c5.p1", + "ju1.a4.m4.s3c5.p2", + "ju1.a4.m4.s3c5.p3", + "ju1.a4.m4.s3c5.p4", + "ju1.a4.m4.s3c5.p5", + "ju1.a4.m4.s3c5.p6", + "ju1.a4.m4.s3c5.p7", + "ju1.a4.m4.s3c5.p8", + "ju1.a4.m4.s3c5.p9", + "ju1.a4.m4.s3c5.p10", + "ju1.a4.m4.s3c5.p11", + "ju1.a4.m4.s3c5.p12", + "ju1.a4.m4.s3c5.p13", + "ju1.a4.m4.s3c5.p14", + "ju1.a4.m4.s3c5.p15", + "ju1.a4.m4.s3c5.p16" + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "List all the child nodes of ju1.a3.m1rack. Return a list of child node names.", + "Label": "capacity planning, level-1, list", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.40806662, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n node = {'type': 'EK_RACK', 'name': 'ju1.a3.m1rack'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = graph_data.copy()\n child_nodes = []\n rack_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.m1rack' and 'EK_RACK' in node[1]['type']:\n rack_node_id = node[0]\n break\n if rack_node_id:\n for edge in graph_copy.out_edges(rack_node_id, data=True):\n if 'RK_CONTAINS' in edge[2]['type']:\n target_node = graph_copy.nodes[edge[1]]\n child_nodes.append(target_node['name'])\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n return return_object", + "Ground truth exec": [ + "ju1.a3.m1.s2c1", + "ju1.a3.m1.s2c2", + "ju1.a3.m1.s2c3", + "ju1.a3.m1.s2c4", + "ju1.a3.m1.s2c5", + "ju1.a3.m1.s2c6", + "ju1.a3.m1.s2c7", + "ju1.a3.m1.s2c8", + "ju1.a3.m1.s3c1", + "ju1.a3.m1.s3c2", + "ju1.a3.m1.s3c3", + "ju1.a3.m1.s3c4", + "ju1.a3.m1.s3c5", + "ju1.a3.m1.s3c6", + "ju1.a3.m1.s3c7", + "ju1.a3.m1.s3c8" + ], + "LLM code exec": [ + "ju1.a3.m1.s2c1", + "ju1.a3.m1.s2c2", + "ju1.a3.m1.s2c3", + "ju1.a3.m1.s2c4", + "ju1.a3.m1.s2c5", + "ju1.a3.m1.s2c6", + "ju1.a3.m1.s2c7", + "ju1.a3.m1.s2c8", + "ju1.a3.m1.s3c1", + "ju1.a3.m1.s3c2", + "ju1.a3.m1.s3c3", + "ju1.a3.m1.s3c4", + "ju1.a3.m1.s3c5", + "ju1.a3.m1.s3c6", + "ju1.a3.m1.s3c7", + "ju1.a3.m1.s3c8" + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.s4.s2c4 from the graph. List direct child nodes of ju1.s4 in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-2, remove-list", + "Result-Correctness": "Pass", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 6.922680791999994, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.s4.s2c4'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": 'ju1.s4'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n \n # Find and remove the node 'ju1.s4.s2c4'\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s4.s2c4':\n node_to_remove = node[0]\n break\n \n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n \n # Find children of 'ju1.s4'\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s4':\n parent_node_id = node[0]\n break\n \n child_names = []\n if parent_node_id:\n for edge in graph_copy.edges(data=True):\n if edge[0] == parent_node_id and 'RK_CONTAINS' in edge[2]['type']:\n child_node = graph_copy.nodes[edge[1]]\n child_names.append(child_node['name'])\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_names,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + "ju1.s4.s1c1", + "ju1.s4.s1c2", + "ju1.s4.s1c3", + "ju1.s4.s1c4", + "ju1.s4.s1c5", + "ju1.s4.s1c6", + "ju1.s4.s1c7", + "ju1.s4.s1c8", + "ju1.s4.s2c1", + "ju1.s4.s2c2", + "ju1.s4.s2c3", + "ju1.s4.s2c5", + "ju1.s4.s2c6", + "ju1.s4.s2c7", + "ju1.s4.s2c8" + ], + "LLM code exec": [ + "ju1.s4.s1c1", + "ju1.s4.s1c2", + "ju1.s4.s1c3", + "ju1.s4.s1c4", + "ju1.s4.s1c5", + "ju1.s4.s1c6", + "ju1.s4.s1c7", + "ju1.s4.s1c8", + "ju1.s4.s2c1", + "ju1.s4.s2c2", + "ju1.s4.s2c3", + "ju1.s4.s2c5", + "ju1.s4.s2c6", + "ju1.s4.s2c7", + "ju1.s4.s2c8" + ], + "Verifier-Error": "Found 16 isolated nodes: ju1.s4.s2c4.p1, ju1.s4.s2c4.p2, ju1.s4.s2c4.p3, ju1.s4.s2c4.p4, ju1.s4.s2c4.p5, ju1.s4.s2c4.p6, ju1.s4.s2c4.p7, ju1.s4.s2c4.p8, ju1.s4.s2c4.p9, ju1.s4.s2c4.p10, ju1.s4.s2c4.p11, ju1.s4.s2c4.p12, ju1.s4.s2c4.p13, ju1.s4.s2c4.p14, ju1.s4.s2c4.p15, ju1.s4.s2c4.p16", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a3.m3.s3c7.p8 from the graph. List direct child nodes of ju1.a3.m3.s3c7 in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-2, remove-list", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 7.398396073000015, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a3.m3.s3c7.p8'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node = {\"type\": \"EK_AGG_BLOCK\", \"name\": 'ju1.a3.m3.s3c7'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n \n # Remove the specified node\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.m3.s3c7.p8':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n \n # Find direct child nodes of ju1.a3.m3.s3c7\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.m3.s3c7':\n parent_node_id = node[0]\n break\n \n child_nodes = []\n if parent_node_id:\n for edge in graph_copy.edges(data=True):\n if edge[0] == parent_node_id and 'RK_CONTAINS' in edge[2]['type']:\n child_node_id = edge[1]\n child_node_data = graph_copy.nodes[child_node_id]\n child_nodes.append(child_node_data['name'])\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + "ju1.a3.m3.s3c7.p1", + "ju1.a3.m3.s3c7.p2", + "ju1.a3.m3.s3c7.p3", + "ju1.a3.m3.s3c7.p4", + "ju1.a3.m3.s3c7.p5", + "ju1.a3.m3.s3c7.p6", + "ju1.a3.m3.s3c7.p7", + "ju1.a3.m3.s3c7.p9", + "ju1.a3.m3.s3c7.p10", + "ju1.a3.m3.s3c7.p11", + "ju1.a3.m3.s3c7.p12", + "ju1.a3.m3.s3c7.p13", + "ju1.a3.m3.s3c7.p14", + "ju1.a3.m3.s3c7.p15", + "ju1.a3.m3.s3c7.p16" + ], + "LLM code exec": [ + "ju1.a3.m3.s3c7.p1", + "ju1.a3.m3.s3c7.p2", + "ju1.a3.m3.s3c7.p3", + "ju1.a3.m3.s3c7.p4", + "ju1.a3.m3.s3c7.p5", + "ju1.a3.m3.s3c7.p6", + "ju1.a3.m3.s3c7.p7", + "ju1.a3.m3.s3c7.p9", + "ju1.a3.m3.s3c7.p10", + "ju1.a3.m3.s3c7.p11", + "ju1.a3.m3.s3c7.p12", + "ju1.a3.m3.s3c7.p13", + "ju1.a3.m3.s3c7.p14", + "ju1.a3.m3.s3c7.p15", + "ju1.a3.m3.s3c7.p16" + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a1.m3.s3c3 from the graph. List direct child nodes of ju1.a1.m3 in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-2, remove-list", + "Result-Correctness": "Pass", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 6.9626873049999745, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a1.m3.s3c3'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": 'ju1.a1.m3'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n \n # Remove ju1.a1.m3.s3c3 from the graph\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a1.m3.s3c3':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n \n # Find direct child nodes of ju1.a1.m3\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a1.m3':\n parent_node_id = node[0]\n break\n \n child_nodes = []\n if parent_node_id:\n for edge in graph_copy.edges(data=True):\n if edge[0] == parent_node_id and 'RK_CONTAINS' in edge[2]['type']:\n child_node_id = edge[1]\n child_node_data = graph_copy.nodes[child_node_id]\n child_nodes.append(child_node_data['name'])\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + "ju1.a1.m3.s2c1", + "ju1.a1.m3.s2c2", + "ju1.a1.m3.s2c3", + "ju1.a1.m3.s2c4", + "ju1.a1.m3.s2c5", + "ju1.a1.m3.s2c6", + "ju1.a1.m3.s2c7", + "ju1.a1.m3.s2c8", + "ju1.a1.m3.s3c1", + "ju1.a1.m3.s3c2", + "ju1.a1.m3.s3c4", + "ju1.a1.m3.s3c5", + "ju1.a1.m3.s3c6", + "ju1.a1.m3.s3c7", + "ju1.a1.m3.s3c8" + ], + "LLM code exec": [ + "ju1.a1.m3.s2c1", + "ju1.a1.m3.s2c2", + "ju1.a1.m3.s2c3", + "ju1.a1.m3.s2c4", + "ju1.a1.m3.s2c5", + "ju1.a1.m3.s2c6", + "ju1.a1.m3.s2c7", + "ju1.a1.m3.s2c8", + "ju1.a1.m3.s3c1", + "ju1.a1.m3.s3c2", + "ju1.a1.m3.s3c4", + "ju1.a1.m3.s3c5", + "ju1.a1.m3.s3c6", + "ju1.a1.m3.s3c7", + "ju1.a1.m3.s3c8" + ], + "Verifier-Error": "Found 16 isolated nodes: ju1.a1.m3.s3c3.p1, ju1.a1.m3.s3c3.p2, ju1.a1.m3.s3c3.p3, ju1.a1.m3.s3c3.p4, ju1.a1.m3.s3c3.p5, ju1.a1.m3.s3c3.p6, ju1.a1.m3.s3c3.p7, ju1.a1.m3.s3c3.p8, ju1.a1.m3.s3c3.p9, ju1.a1.m3.s3c3.p10, ju1.a1.m3.s3c3.p11, ju1.a1.m3.s3c3.p12, ju1.a1.m3.s3c3.p13, ju1.a1.m3.s3c3.p14, ju1.a1.m3.s3c3.p15, ju1.a1.m3.s3c3.p16", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.s2.s2c8.p5 from the graph. List direct child nodes of ju1.s2.s2c8 in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-2, remove-list", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 6.989485708000018, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.s2.s2c8.p5'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": 'ju1.s2.s2c8'}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n \n # Remove the node ju1.s2.s2c8.p5\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s2.s2c8.p5':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n \n # Find direct child nodes of ju1.s2.s2c8\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s2.s2c8':\n parent_node_id = node[0]\n break\n \n child_names = []\n if parent_node_id:\n for _, child_id in graph_copy.out_edges(parent_node_id):\n edge_data = graph_copy.get_edge_data(parent_node_id, child_id)\n if edge_data and 'type' in edge_data and 'RK_CONTAINS' in edge_data['type']:\n child_node = graph_copy.nodes[child_id]\n if 'name' in child_node:\n child_names.append(child_node['name'])\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_names,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + "ju1.s2.s2c8.p1", + "ju1.s2.s2c8.p2", + "ju1.s2.s2c8.p3", + "ju1.s2.s2c8.p4", + "ju1.s2.s2c8.p6", + "ju1.s2.s2c8.p7", + "ju1.s2.s2c8.p8", + "ju1.s2.s2c8.p9", + "ju1.s2.s2c8.p10", + "ju1.s2.s2c8.p11", + "ju1.s2.s2c8.p12", + "ju1.s2.s2c8.p13", + "ju1.s2.s2c8.p14", + "ju1.s2.s2c8.p15", + "ju1.s2.s2c8.p16" + ], + "LLM code exec": [ + "ju1.s2.s2c8.p1", + "ju1.s2.s2c8.p2", + "ju1.s2.s2c8.p3", + "ju1.s2.s2c8.p4", + "ju1.s2.s2c8.p6", + "ju1.s2.s2c8.p7", + "ju1.s2.s2c8.p8", + "ju1.s2.s2c8.p9", + "ju1.s2.s2c8.p10", + "ju1.s2.s2c8.p11", + "ju1.s2.s2c8.p12", + "ju1.s2.s2c8.p13", + "ju1.s2.s2c8.p14", + "ju1.s2.s2c8.p15", + "ju1.s2.s2c8.p16" + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a1.m2.s2c2.p15 from the graph. Rank direct child nodes of ju1.a1.m2.s2c2 in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-2, remove-rank", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 10.063609964000023, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a1.m2.s2c2.p15'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n parent_node_name = 'ju1.a1.m2.s2c2'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Remove the specified node if it exists\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a1.m2.s2c2.p15':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n\n # Find the parent node\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a1.m2.s2c2':\n parent_node_id = node[0]\n break\n\n # Collect direct children of the parent node\n children = []\n if parent_node_id:\n for edge in graph_copy.out_edges(parent_node_id, data=True):\n if 'RK_CONTAINS' in edge[2]['type']:\n child_id = edge[1]\n child_data = graph_copy.nodes[child_id]\n children.append((child_id, child_data))\n\n # Calculate total physical capacity for each child\n child_capacities = []\n for child_id, child_data in children:\n total_capacity = 0\n # BFS to find all PORT descendants and sum their physical_capacity_bps\n queue = [child_id]\n while queue:\n current = queue.pop(0)\n current_data = graph_copy.nodes[current]\n if 'EK_PORT' in current_data['type'] and 'physical_capacity_bps' in current_data:\n total_capacity += current_data['physical_capacity_bps']\n # Add children with RK_CONTAINS relationship\n for succ_edge in graph_copy.out_edges(current, data=True):\n if 'RK_CONTAINS' in succ_edge[2]['type']:\n queue.append(succ_edge[1])\n child_capacities.append((child_data['name'], total_capacity))\n\n # Sort by total physical capacity descending\n child_capacities.sort(key=lambda x: x[1], reverse=True)\n\n # Prepare return object\n return_object = {\n 'type': 'list',\n 'data': child_capacities,\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n\n return return_object", + "Ground truth exec": [ + [ + "ju1.a1.m2.s2c2.p1", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p2", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p3", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p4", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p5", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p6", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p7", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p8", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p9", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p10", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p11", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p12", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p13", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p14", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p16", + 1000000000.0 + ] + ], + "LLM code exec": [ + [ + "ju1.a1.m2.s2c2.p1", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p2", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p3", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p4", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p5", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p6", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p7", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p8", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p9", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p10", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p11", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p12", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p13", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p14", + 1000000000.0 + ], + [ + "ju1.a1.m2.s2c2.p16", + 1000000000.0 + ] + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.s4.s1c6 from the graph. Rank direct child nodes of ju1.s4 in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-2, remove-rank", + "Result-Correctness": "Pass", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 9.563416762999964, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.s4.s1c6'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n parent_node_name = 'ju1.s4'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Remove the node 'ju1.s4.s1c6'\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s4.s1c6':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n\n # Helper function to calculate total capacity of a node\n def calculate_capacity(node_id, graph):\n total_capacity = 0\n for n in graph.nodes(data=True):\n if n[1]['name'] == node_id and 'EK_PORT' in n[1]['type']:\n total_capacity += n[1].get('physical_capacity_bps', 0)\n for successor in graph.successors(node_id):\n edge_data = graph.get_edge_data(node_id, successor)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n total_capacity += calculate_capacity(successor, graph)\n return total_capacity\n\n # Find direct children of 'ju1.s4'\n children_capacity = []\n s4_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s4':\n s4_node_id = node[0]\n break\n\n if s4_node_id:\n for child_id in graph_copy.successors(s4_node_id):\n edge_data = graph_copy.get_edge_data(s4_node_id, child_id)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n capacity = calculate_capacity(child_id, graph_copy)\n for n in graph_copy.nodes(data=True):\n if n[0] == child_id:\n children_capacity.append((n[1]['name'], capacity))\n break\n\n # Sort children by capacity descending\n children_capacity.sort(key=lambda x: x[1], reverse=True)\n\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': children_capacity,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c5", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ] + ], + "LLM code exec": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c5", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ] + ], + "Verifier-Error": "Found 16 isolated nodes: ju1.s4.s1c6.p1, ju1.s4.s1c6.p2, ju1.s4.s1c6.p3, ju1.s4.s1c6.p4, ju1.s4.s1c6.p5, ju1.s4.s1c6.p6, ju1.s4.s1c6.p7, ju1.s4.s1c6.p8, ju1.s4.s1c6.p9, ju1.s4.s1c6.p10, ju1.s4.s1c6.p11, ju1.s4.s1c6.p12, ju1.s4.s1c6.p13, ju1.s4.s1c6.p14, ju1.s4.s1c6.p15, ju1.s4.s1c6.p16", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a2.m1.s2c5.p6 from the graph. Rank direct child nodes of ju1.a2.m1.s2c5 in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-2, remove-rank", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 8.84250995299999, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a2.m1.s2c5.p6'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n parent_node_name = 'ju1.a2.m1.s2c5'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Remove the specified node if it exists\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a2.m1.s2c5.p6':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n\n # Identify the parent node whose children we need to rank\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a2.m1.s2c5':\n parent_node_id = node[0]\n break\n\n # Function to calculate total capacity of a subtree rooted at a given node\n def calculate_total_capacity(node_id):\n node_data = graph_copy.nodes[node_id]\n if 'EK_PORT' in node_data['type']:\n return node_data.get('physical_capacity_bps', 0)\n total = 0\n for successor in graph_copy.successors(node_id):\n edge_data = graph_copy.get_edge_data(node_id, successor)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n total += calculate_total_capacity(successor)\n return total\n\n # Collect direct children of the parent node\n children_capacities = []\n if parent_node_id:\n for successor in graph_copy.successors(parent_node_id):\n edge_data = graph_copy.get_edge_data(parent_node_id, successor)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n child_name = graph_copy.nodes[successor].get('name', successor)\n total_capacity = calculate_total_capacity(successor)\n children_capacities.append((child_name, total_capacity))\n\n # Sort children by total capacity descending\n children_capacities.sort(key=lambda x: x[1], reverse=True)\n\n # Prepare return object\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': children_capacities,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + [ + "ju1.a2.m1.s2c5.p1", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p2", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p3", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p4", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p5", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p7", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p8", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p9", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p10", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p11", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p12", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p13", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p14", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p15", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p16", + 1000000000.0 + ] + ], + "LLM code exec": [ + [ + "ju1.a2.m1.s2c5.p1", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p2", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p3", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p4", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p5", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p7", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p8", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p9", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p10", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p11", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p12", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p13", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p14", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p15", + 1000000000.0 + ], + [ + "ju1.a2.m1.s2c5.p16", + 1000000000.0 + ] + ], + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.s4.s1c5 from the graph. Rank direct child nodes of ju1.s4 in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-2, remove-rank", + "Result-Correctness": "Pass", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 10.545367209000005, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.s4.s1c5'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n parent_node_name = 'ju1.s4'\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Remove ju1.s4.s1c5 if it exists\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s4.s1c5':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n\n # Find direct child nodes of ju1.s4\n children_of_ju1_s4 = []\n ju1_s4_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s4':\n ju1_s4_node_id = node[0]\n break\n\n if ju1_s4_node_id:\n # Get successors (direct children)\n for successor in graph_copy.successors(ju1_s4_node_id):\n children_of_ju1_s4.append(successor)\n\n # For each child, calculate total physical capacity by summing over all contained PORTs\n result_list = []\n\n def get_all_ports_under_node(graph, node_id):\n # Recursively collect all PORT nodes under this node\n ports = []\n if 'EK_PORT' in graph.nodes[node_id]['type']:\n ports.append(node_id)\n else:\n for succ in graph.successors(node_id):\n edge_data = graph.get_edge_data(node_id, succ)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n ports.extend(get_all_ports_under_node(graph, succ))\n return ports\n\n for child_id in children_of_ju1_s4:\n total_capacity = 0\n port_nodes = get_all_ports_under_node(graph_copy, child_id)\n for port_id in port_nodes:\n capacity = graph_copy.nodes[port_id].get('physical_capacity_bps', 0)\n total_capacity += capacity\n child_name = graph_copy.nodes[child_id]['name']\n result_list.append((child_name, total_capacity))\n\n # Sort by physical_capacity_bps descending\n result_list.sort(key=lambda x: x[1], reverse=True)\n\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': result_list,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c6", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ] + ], + "LLM code exec": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c6", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ] + ], + "Verifier-Error": "Found 16 isolated nodes: ju1.s4.s1c5.p1, ju1.s4.s1c5.p2, ju1.s4.s1c5.p3, ju1.s4.s1c5.p4, ju1.s4.s1c5.p5, ju1.s4.s1c5.p6, ju1.s4.s1c5.p7, ju1.s4.s1c5.p8, ju1.s4.s1c5.p9, ju1.s4.s1c5.p10, ju1.s4.s1c5.p11, ju1.s4.s1c5.p12, ju1.s4.s1c5.p13, ju1.s4.s1c5.p14, ju1.s4.s1c5.p15, ju1.s4.s1c5.p16", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a1.m4.s2c6 from the graph. Count the EK_PACKET_SWITCH in ju1.a1.m4 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-2, remove-count", + "Result-Correctness": "Pass", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 5.510765874000015, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a1.m4.s2c6'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node1 = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": \"ju1.a1.m4\"}\n node2 = {\"type\": \"EK_PACKET_SWITCH\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Remove ju1.a1.m4.s2c6 from the graph\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a1.m4.s2c6':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n\n # Count the EK_PACKET_SWITCH in ju1.a1.m4 in the updated graph\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PACKET_SWITCH' in node[1]['type'] and node[1]['name'].startswith('ju1.a1.m4.'):\n count += 1\n\n # Prepare the return object\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': graph_json\n }\n\n return return_object", + "Ground truth exec": "15", + "LLM code exec": "15", + "Verifier-Error": "Found 16 isolated nodes: ju1.a1.m4.s2c6.p1, ju1.a1.m4.s2c6.p2, ju1.a1.m4.s2c6.p3, ju1.a1.m4.s2c6.p4, ju1.a1.m4.s2c6.p5, ju1.a1.m4.s2c6.p6, ju1.a1.m4.s2c6.p7, ju1.a1.m4.s2c6.p8, ju1.a1.m4.s2c6.p9, ju1.a1.m4.s2c6.p10, ju1.a1.m4.s2c6.p11, ju1.a1.m4.s2c6.p12, ju1.a1.m4.s2c6.p13, ju1.a1.m4.s2c6.p14, ju1.a1.m4.s2c6.p15, ju1.a1.m4.s2c6.p16", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.s1.s2c1.p2 from the graph. Count the EK_PORT in ju1.s1.s2c1 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-2, remove-count", + "Result-Correctness": "Fail", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 5.401646056999994, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.s1.s2c1.p2'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node1 = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": \"ju1.s1.s2c1\"}\n node2 = {\"type\": \"EK_PORT\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Remove ju1.s1.s2c1.p2 from the graph\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.s1.s2c1.p2' and 'EK_PORT' in node[1]['type']:\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n\n # Count the EK_PORT in ju1.s1.s2c1 in the updated graph\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PORT' in node[1]['type'] and node[1]['name'].startswith('ju1.s1.s2c1.') and node[1]['name'].count('.') == 4:\n count += 1\n\n # Prepare return object\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': nx.readwrite.json_graph.node_link_data(graph_copy)\n }\n\n return return_object", + "Ground truth exec": "15", + "LLM code exec": "0", + "Error": { + "Ground truth": "15", + "Model output": "0" + }, + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a1.m4.s2c8.p1 from the graph. Count the EK_PORT in ju1.a1.m4.s2c8 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-2, remove-count", + "Result-Correctness": "Fail", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 6.907487482000022, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a1.m4.s2c8.p1'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node1 = {\"type\": \"EK_AGG_BLOCK\", \"name\": \"ju1.a1.m4.s2c8\"}\n node2 = {\"type\": \"EK_PORT\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Remove the specified node\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a1.m4.s2c8.p1' and 'EK_PORT' in node[1]['type']:\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n\n # Count EK_PORT in ju1.a1.m4.s2c8\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PORT' in node[1]['type'] and node[1]['name'].startswith('ju1.a1.m4.s2c8.') and node[1]['name'].count('.') == 5:\n # Ensure it's directly under s2c8 by checking the name structure\n port_parts = node[1]['name'].split('.')\n if len(port_parts) == 6 and port_parts[0] == 'ju1' and port_parts[1] == 'a1' and port_parts[2] == 'm4' and port_parts[3] == 's2c8':\n count += 1\n\n # Prepare the return object\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": "15", + "LLM code exec": "0", + "Error": { + "Ground truth": "15", + "Model output": "0" + }, + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Remove ju1.a4.m3.s3c8 from the graph. Count the EK_PACKET_SWITCH in ju1.a4.m3 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-2, remove-count", + "Result-Correctness": "Pass", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.664593928999977, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n child_node_name = 'ju1.a4.m3.s3c8'\n graph_data = solid_step_remove_node_from_graph(graph_data, child_node_name)\n node1 = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": \"ju1.a4.m3\"}\n node2 = {\"type\": \"EK_PACKET_SWITCH\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n \n # Remove ju1.a4.m3.s3c8 from the graph\n node_to_remove = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a4.m3.s3c8':\n node_to_remove = node[0]\n break\n if node_to_remove:\n graph_copy.remove_node(node_to_remove)\n \n # Count the EK_PACKET_SWITCH in ju1.a4.m3 in the updated graph\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PACKET_SWITCH' in node[1]['type']:\n if node[1]['name'].startswith('ju1.a4.m3.'):\n count += 1\n \n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": "15", + "LLM code exec": "15", + "Verifier-Error": "Found 16 isolated nodes: ju1.a4.m3.s3c8.p1, ju1.a4.m3.s3c8.p2, ju1.a4.m3.s3c8.p3, ju1.a4.m3.s3c8.p4, ju1.a4.m3.s3c8.p5, ju1.a4.m3.s3c8.p6, ju1.a4.m3.s3c8.p7, ju1.a4.m3.s3c8.p8, ju1.a4.m3.s3c8.p9, ju1.a4.m3.s3c8.p10, ju1.a4.m3.s3c8.p11, ju1.a4.m3.s3c8.p12, ju1.a4.m3.s3c8.p13, ju1.a4.m3.s3c8.p14, ju1.a4.m3.s3c8.p15, ju1.a4.m3.s3c8.p16", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PACKET_SWITCH_84 to ju1.a2.dom. List direct child nodes of ju1.a2.dom in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-3, add-list", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 5.957686709000029, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PACKET_SWITCH_84', 'type': 'EK_PACKET_SWITCH'}\n parent_node_name = 'ju1.a2.dom'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": \"ju1.a2.dom\"}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n # Add new EK_PACKET_SWITCH node\n new_node_name = 'new_EK_PACKET_SWITCH_84'\n graph_copy.add_node(new_node_name, type=['EK_PACKET_SWITCH'])\n # Connect to ju1.a2.dom\n parent_node = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a2.dom' and 'EK_CONTROL_DOMAIN' in node[1]['type']:\n parent_node = node[0]\n break\n if parent_node:\n graph_copy.add_edge(parent_node, new_node_name, type=['RK_CONTAINS'])\n # Find direct children of ju1.a2.dom\n children_names = []\n if parent_node:\n for _, child, edge_data in graph_copy.out_edges(parent_node, data=True):\n if 'type' in edge_data and 'RK_CONTAINS' in edge_data['type']:\n child_attrs = graph_copy.nodes[child]\n if 'name' in child_attrs:\n children_names.append(child_attrs['name'])\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': children_names,\n 'updated_graph': graph_json\n }\n return return_object", + "Ground truth exec": [ + "ju1.a2.m1.s2c1", + "ju1.a2.m1.s2c2", + "ju1.a2.m1.s2c3", + "ju1.a2.m1.s2c4", + "ju1.a2.m1.s2c5", + "ju1.a2.m1.s2c6", + "ju1.a2.m1.s2c7", + "ju1.a2.m1.s2c8", + "ju1.a2.m1.s3c1", + "ju1.a2.m1.s3c2", + "ju1.a2.m1.s3c3", + "ju1.a2.m1.s3c4", + "ju1.a2.m1.s3c5", + "ju1.a2.m1.s3c6", + "ju1.a2.m1.s3c7", + "ju1.a2.m1.s3c8", + "ju1.a2.m2.s2c1", + "ju1.a2.m2.s2c2", + "ju1.a2.m2.s2c3", + "ju1.a2.m2.s2c4", + "ju1.a2.m2.s2c5", + "ju1.a2.m2.s2c6", + "ju1.a2.m2.s2c7", + "ju1.a2.m2.s2c8", + "ju1.a2.m2.s3c1", + "ju1.a2.m2.s3c2", + "ju1.a2.m2.s3c3", + "ju1.a2.m2.s3c4", + "ju1.a2.m2.s3c5", + "ju1.a2.m2.s3c6", + "ju1.a2.m2.s3c7", + "ju1.a2.m2.s3c8", + "ju1.a2.m3.s2c1", + "ju1.a2.m3.s2c2", + "ju1.a2.m3.s2c3", + "ju1.a2.m3.s2c4", + "ju1.a2.m3.s2c5", + "ju1.a2.m3.s2c6", + "ju1.a2.m3.s2c7", + "ju1.a2.m3.s2c8", + "ju1.a2.m3.s3c1", + "ju1.a2.m3.s3c2", + "ju1.a2.m3.s3c3", + "ju1.a2.m3.s3c4", + "ju1.a2.m3.s3c5", + "ju1.a2.m3.s3c6", + "ju1.a2.m3.s3c7", + "ju1.a2.m3.s3c8", + "ju1.a2.m4.s2c1", + "ju1.a2.m4.s2c2", + "ju1.a2.m4.s2c3", + "ju1.a2.m4.s2c4", + "ju1.a2.m4.s2c5", + "ju1.a2.m4.s2c6", + "ju1.a2.m4.s2c7", + "ju1.a2.m4.s2c8", + "ju1.a2.m4.s3c1", + "ju1.a2.m4.s3c2", + "ju1.a2.m4.s3c3", + "ju1.a2.m4.s3c4", + "ju1.a2.m4.s3c5", + "ju1.a2.m4.s3c6", + "ju1.a2.m4.s3c7", + "ju1.a2.m4.s3c8", + "new_EK_PACKET_SWITCH_84" + ], + "LLM code exec": [ + "ju1.a2.m1.s2c1", + "ju1.a2.m1.s2c2", + "ju1.a2.m1.s2c3", + "ju1.a2.m1.s2c4", + "ju1.a2.m1.s2c5", + "ju1.a2.m1.s2c6", + "ju1.a2.m1.s2c7", + "ju1.a2.m1.s2c8", + "ju1.a2.m1.s3c1", + "ju1.a2.m1.s3c2", + "ju1.a2.m1.s3c3", + "ju1.a2.m1.s3c4", + "ju1.a2.m1.s3c5", + "ju1.a2.m1.s3c6", + "ju1.a2.m1.s3c7", + "ju1.a2.m1.s3c8", + "ju1.a2.m2.s2c1", + "ju1.a2.m2.s2c2", + "ju1.a2.m2.s2c3", + "ju1.a2.m2.s2c4", + "ju1.a2.m2.s2c5", + "ju1.a2.m2.s2c6", + "ju1.a2.m2.s2c7", + "ju1.a2.m2.s2c8", + "ju1.a2.m2.s3c1", + "ju1.a2.m2.s3c2", + "ju1.a2.m2.s3c3", + "ju1.a2.m2.s3c4", + "ju1.a2.m2.s3c5", + "ju1.a2.m2.s3c6", + "ju1.a2.m2.s3c7", + "ju1.a2.m2.s3c8", + "ju1.a2.m3.s2c1", + "ju1.a2.m3.s2c2", + "ju1.a2.m3.s2c3", + "ju1.a2.m3.s2c4", + "ju1.a2.m3.s2c5", + "ju1.a2.m3.s2c6", + "ju1.a2.m3.s2c7", + "ju1.a2.m3.s2c8", + "ju1.a2.m3.s3c1", + "ju1.a2.m3.s3c2", + "ju1.a2.m3.s3c3", + "ju1.a2.m3.s3c4", + "ju1.a2.m3.s3c5", + "ju1.a2.m3.s3c6", + "ju1.a2.m3.s3c7", + "ju1.a2.m3.s3c8", + "ju1.a2.m4.s2c1", + "ju1.a2.m4.s2c2", + "ju1.a2.m4.s2c3", + "ju1.a2.m4.s2c4", + "ju1.a2.m4.s2c5", + "ju1.a2.m4.s2c6", + "ju1.a2.m4.s2c7", + "ju1.a2.m4.s2c8", + "ju1.a2.m4.s3c1", + "ju1.a2.m4.s3c2", + "ju1.a2.m4.s3c3", + "ju1.a2.m4.s3c4", + "ju1.a2.m4.s3c5", + "ju1.a2.m4.s3c6", + "ju1.a2.m4.s3c7", + "ju1.a2.m4.s3c8" + ], + "Error": { + "Ground truth": [ + "ju1.a2.m1.s2c1", + "ju1.a2.m1.s2c2", + "ju1.a2.m1.s2c3", + "ju1.a2.m1.s2c4", + "ju1.a2.m1.s2c5", + "ju1.a2.m1.s2c6", + "ju1.a2.m1.s2c7", + "ju1.a2.m1.s2c8", + "ju1.a2.m1.s3c1", + "ju1.a2.m1.s3c2", + "ju1.a2.m1.s3c3", + "ju1.a2.m1.s3c4", + "ju1.a2.m1.s3c5", + "ju1.a2.m1.s3c6", + "ju1.a2.m1.s3c7", + "ju1.a2.m1.s3c8", + "ju1.a2.m2.s2c1", + "ju1.a2.m2.s2c2", + "ju1.a2.m2.s2c3", + "ju1.a2.m2.s2c4", + "ju1.a2.m2.s2c5", + "ju1.a2.m2.s2c6", + "ju1.a2.m2.s2c7", + "ju1.a2.m2.s2c8", + "ju1.a2.m2.s3c1", + "ju1.a2.m2.s3c2", + "ju1.a2.m2.s3c3", + "ju1.a2.m2.s3c4", + "ju1.a2.m2.s3c5", + "ju1.a2.m2.s3c6", + "ju1.a2.m2.s3c7", + "ju1.a2.m2.s3c8", + "ju1.a2.m3.s2c1", + "ju1.a2.m3.s2c2", + "ju1.a2.m3.s2c3", + "ju1.a2.m3.s2c4", + "ju1.a2.m3.s2c5", + "ju1.a2.m3.s2c6", + "ju1.a2.m3.s2c7", + "ju1.a2.m3.s2c8", + "ju1.a2.m3.s3c1", + "ju1.a2.m3.s3c2", + "ju1.a2.m3.s3c3", + "ju1.a2.m3.s3c4", + "ju1.a2.m3.s3c5", + "ju1.a2.m3.s3c6", + "ju1.a2.m3.s3c7", + "ju1.a2.m3.s3c8", + "ju1.a2.m4.s2c1", + "ju1.a2.m4.s2c2", + "ju1.a2.m4.s2c3", + "ju1.a2.m4.s2c4", + "ju1.a2.m4.s2c5", + "ju1.a2.m4.s2c6", + "ju1.a2.m4.s2c7", + "ju1.a2.m4.s2c8", + "ju1.a2.m4.s3c1", + "ju1.a2.m4.s3c2", + "ju1.a2.m4.s3c3", + "ju1.a2.m4.s3c4", + "ju1.a2.m4.s3c5", + "ju1.a2.m4.s3c6", + "ju1.a2.m4.s3c7", + "ju1.a2.m4.s3c8", + "new_EK_PACKET_SWITCH_84" + ], + "Model output": [ + "ju1.a2.m1.s2c1", + "ju1.a2.m1.s2c2", + "ju1.a2.m1.s2c3", + "ju1.a2.m1.s2c4", + "ju1.a2.m1.s2c5", + "ju1.a2.m1.s2c6", + "ju1.a2.m1.s2c7", + "ju1.a2.m1.s2c8", + "ju1.a2.m1.s3c1", + "ju1.a2.m1.s3c2", + "ju1.a2.m1.s3c3", + "ju1.a2.m1.s3c4", + "ju1.a2.m1.s3c5", + "ju1.a2.m1.s3c6", + "ju1.a2.m1.s3c7", + "ju1.a2.m1.s3c8", + "ju1.a2.m2.s2c1", + "ju1.a2.m2.s2c2", + "ju1.a2.m2.s2c3", + "ju1.a2.m2.s2c4", + "ju1.a2.m2.s2c5", + "ju1.a2.m2.s2c6", + "ju1.a2.m2.s2c7", + "ju1.a2.m2.s2c8", + "ju1.a2.m2.s3c1", + "ju1.a2.m2.s3c2", + "ju1.a2.m2.s3c3", + "ju1.a2.m2.s3c4", + "ju1.a2.m2.s3c5", + "ju1.a2.m2.s3c6", + "ju1.a2.m2.s3c7", + "ju1.a2.m2.s3c8", + "ju1.a2.m3.s2c1", + "ju1.a2.m3.s2c2", + "ju1.a2.m3.s2c3", + "ju1.a2.m3.s2c4", + "ju1.a2.m3.s2c5", + "ju1.a2.m3.s2c6", + "ju1.a2.m3.s2c7", + "ju1.a2.m3.s2c8", + "ju1.a2.m3.s3c1", + "ju1.a2.m3.s3c2", + "ju1.a2.m3.s3c3", + "ju1.a2.m3.s3c4", + "ju1.a2.m3.s3c5", + "ju1.a2.m3.s3c6", + "ju1.a2.m3.s3c7", + "ju1.a2.m3.s3c8", + "ju1.a2.m4.s2c1", + "ju1.a2.m4.s2c2", + "ju1.a2.m4.s2c3", + "ju1.a2.m4.s2c4", + "ju1.a2.m4.s2c5", + "ju1.a2.m4.s2c6", + "ju1.a2.m4.s2c7", + "ju1.a2.m4.s2c8", + "ju1.a2.m4.s3c1", + "ju1.a2.m4.s3c2", + "ju1.a2.m4.s3c3", + "ju1.a2.m4.s3c4", + "ju1.a2.m4.s3c5", + "ju1.a2.m4.s3c6", + "ju1.a2.m4.s3c7", + "ju1.a2.m4.s3c8" + ] + }, + "Verifier-Error": "Packet switch node 'new_EK_PACKET_SWITCH_84' has no ports connected to it", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PORT_28 to ju1.a1.m4. List direct child nodes of ju1.a1.m4 in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-3, add-list", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 4.991773303000002, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_28', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a1.m4'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node = {\"type\": \"EK_AGG_BLOCK\", \"name\": \"ju1.a1.m4\"}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n graph_copy.add_node('new_EK_PORT_28', type=['EK_PORT'], physical_capacity_bps=1000)\n graph_copy.add_edge('ju1.a1.m4', 'new_EK_PORT_28', type=['RK_CONTAINS'])\n child_nodes = []\n for edge in graph_copy.edges(data=True):\n if edge[0] == 'ju1.a1.m4' and 'RK_CONTAINS' in edge[2]['type']:\n target_node = edge[1]\n for node in graph_copy.nodes(data=True):\n if node[0] == target_node:\n child_nodes.append(node[1]['name'])\n break\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': graph_json\n }\n return return_object", + "Error": { + "type": "error", + "data": "Traceback (most recent call last):\n File \"/NetPress/app-malt/malt_env.py\", line 60, in run_agent_output\n ret = eval(\"process_graph(copy.deepcopy(G))\", exec_namespace)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"\", line 1, in \n File \"\", line 11, in process_graph\nKeyError: 'name'\n" + }, + "Verifier-Error": "The LLM code is not correct, so the safety checker is not applied.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PACKET_SWITCH_49 to ju1.a1.dom. List direct child nodes of ju1.a1.dom in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-3, add-list", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 3.864044229000001, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PACKET_SWITCH_49', 'type': 'EK_PACKET_SWITCH'}\n parent_node_name = 'ju1.a1.dom'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node = {\"type\": \"EK_CONTROL_DOMAIN\", \"name\": \"ju1.a1.dom\"}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n graph_copy.add_node('new_EK_PACKET_SWITCH_49', type=['EK_PACKET_SWITCH'])\n graph_copy.add_edge('ju1.a1.dom', 'new_EK_PACKET_SWITCH_49', type=['RK_CONTAINS'])\n child_nodes = []\n for edge in graph_copy.edges(data=True):\n if edge[0] == 'ju1.a1.dom' and 'RK_CONTAINS' in edge[2]['type']:\n target_node = edge[1]\n node_data = graph_copy.nodes[target_node]\n child_nodes.append(node_data['name'])\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_nodes,\n 'updated_graph': graph_json\n }\n return return_object", + "Error": { + "type": "error", + "data": "Traceback (most recent call last):\n File \"/NetPress/app-malt/malt_env.py\", line 60, in run_agent_output\n ret = eval(\"process_graph(copy.deepcopy(G))\", exec_namespace)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"\", line 1, in \n File \"\", line 10, in process_graph\nKeyError: 'name'\n" + }, + "Verifier-Error": "The LLM code is not correct, so the safety checker is not applied.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PORT_96 to ju1.a4.m4. List direct child nodes of ju1.a4.m4 in the updated graph. Return a list of child nodes name.", + "Label": "capacity planning, level-3, add-list", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 5.932916710999962, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_96', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a4.m4'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node = {\"type\": \"EK_AGG_BLOCK\", \"name\": \"ju1.a4.m4\"}\n child_nodes = solid_step_list_child_nodes(graph_data, node)\n return_object = {'type': 'list', 'data': child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n # Add new node with type EK_PORT to ju1.a4.m4\n new_port_name = 'new_EK_PORT_96'\n graph_copy.add_node(new_port_name, type=['EK_PORT'], physical_capacity_bps=1000)\n # Find the parent node ju1.a4.m4\n parent_node = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a4.m4':\n parent_node = node[0]\n break\n if parent_node:\n graph_copy.add_edge(parent_node, new_port_name, type=['RK_CONTAINS'])\n # Get direct children of ju1.a4.m4\n child_names = []\n if parent_node:\n for edge in graph_copy.edges(data=True):\n if edge[0] == parent_node and 'RK_CONTAINS' in edge[2]['type']:\n child_node = edge[1]\n child_attr = graph_copy.nodes[child_node]\n child_names.append(child_attr['name'])\n # Prepare the return object\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'list',\n 'data': child_names,\n 'updated_graph': graph_json\n }\n return return_object", + "Error": { + "type": "error", + "data": "Traceback (most recent call last):\n File \"/NetPress/app-malt/malt_env.py\", line 60, in run_agent_output\n ret = eval(\"process_graph(copy.deepcopy(G))\", exec_namespace)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"\", line 1, in \n File \"\", line 21, in process_graph\nKeyError: 'name'\n" + }, + "Verifier-Error": "The LLM code is not correct, so the safety checker is not applied.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add node with name 'new_EK_PORT_14' to ju1.a2.dom. Rank direct child nodes of ju1.a2.dom in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-3, add-rank", + "Result-Correctness": "Fail", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 15.534698343999992, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_14', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a2.dom'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n graph_copy = copy.deepcopy(graph_data)\n\n # Add new node 'new_EK_PORT_14' to 'ju1.a2.dom'\n # First, we need to find the parent node 'ju1.a2.dom'\n parent_node = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a2.dom' and 'EK_CONTROL_DOMAIN' in node[1]['type']:\n parent_node = node[0]\n break\n\n # Create new port node\n new_port_name = 'new_EK_PORT_14'\n graph_copy.add_node(new_port_name, type=['EK_PORT'], physical_capacity_bps=1000)\n\n # Connect new port to the parent (assuming it should be connected directly under dom, which usually isn't correct,\n # but since the exact path isn't specified, we'll attach it to the domain for now)\n # But according to hierarchy rules, ports belong to packet switches.\n # We need to determine the proper placement - let's assume it goes under a packet switch in ju1.a2\n # Find a packet switch in ju1.a2 to add this port to\n packet_switch_parent = None\n for node in graph_copy.nodes(data=True):\n if ('EK_PACKET_SWITCH' in node[1]['type']) and (node[1]['name'].startswith('ju1.a2.')):\n packet_switch_parent = node[0]\n break\n\n if packet_switch_parent:\n graph_copy.add_edge(packet_switch_parent, new_port_name, type=['RK_CONTAINS'])\n else:\n # If no existing packet switch found, connect to the control domain as fallback\n if parent_node:\n graph_copy.add_edge(parent_node, new_port_name, type=['RK_CONTAINS'])\n\n # Now rank direct child nodes of 'ju1.a2.dom' by their total physical capacity\n dom_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a2.dom' and 'EK_CONTROL_DOMAIN' in node[1]['type']:\n dom_node_id = node[0]\n break\n\n child_nodes_with_capacity = []\n\n def get_total_capacity(node_id):\n total_capacity = 0\n queue = [node_id]\n while queue:\n current = queue.pop(0)\n node_data = graph_copy.nodes[current]\n if 'EK_PORT' in node_data.get('type', []) and 'physical_capacity_bps' in node_data:\n total_capacity += node_data['physical_capacity_bps']\n # Add children to queue\n for successor in graph_copy.successors(current):\n edge_data = graph_copy.get_edge_data(current, successor)\n if edge_data and 'RK_CONTAINS' in edge_data.get('type', []):\n queue.append(successor)\n return total_capacity\n\n # Get direct children of 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16000000000.0 + ], + [ + "ju1.a2.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a2.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a2.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a2.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c8", + 16000000000.0 + ], + [ + "new_EK_PORT_14", + 1000 + ] + ], + "Model output": [ + [ + "ju1.a2.m1.s2c1", + 16000001000.0 + ], + [ + "ju1.a2.m1.s2c2", + 16000000000.0 + ], + [ + "ju1.a2.m1.s2c3", + 16000000000.0 + ], + [ + "ju1.a2.m1.s2c4", + 16000000000.0 + ], + [ + "ju1.a2.m1.s2c5", + 16000000000.0 + ], + [ + "ju1.a2.m1.s2c6", + 16000000000.0 + ], + [ + "ju1.a2.m1.s2c7", + 16000000000.0 + ], + [ + "ju1.a2.m1.s2c8", + 16000000000.0 + ], + [ + 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"ju1.a2.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a2.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a2.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a2.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a2.m4.s3c8", + 16000000000.0 + ] + ] + }, + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add node with name 'new_EK_PORT_54' to ju1.s4.dom. Rank direct child nodes of ju1.s4.dom in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-3, add-rank", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 12.773077998000076, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_54', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.s4.dom'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n graph_copy = copy.deepcopy(graph_data)\n\n # Add new node with name 'new_EK_PORT_54' and type EK_PORT\n new_node_name = 'new_EK_PORT_54'\n parent_node_name = None\n\n # Find the parent node 'ju1.s4.dom'\n for node in graph_copy.nodes(data=True):\n if node[1].get('name') == 'ju1.s4.dom':\n parent_node_name = node[0]\n break\n\n # If parent node found, add new port node and connect it\n if parent_node_name:\n # Add new port node - assuming default capacity of 0 or you can set as needed\n graph_copy.add_node(new_node_name, type=['EK_PORT'], name=new_node_name, physical_capacity_bps=0)\n # Connect to the parent with RK_CONTAINS relationship\n graph_copy.add_edge(parent_node_name, new_node_name, type=['RK_CONTAINS'])\n\n # Now rank direct child nodes of 'ju1.s4.dom' based on total physical_capacity_bps\n target_domain_node_id = None\n target_domain_name = 'ju1.s4.dom'\n\n # Find the domain node\n for node in graph_copy.nodes(data=True):\n if node[1].get('name') == target_domain_name:\n target_domain_node_id = node[0]\n break\n\n child_capacities = []\n\n if target_domain_node_id:\n # Get direct children (nodes connected via RK_CONTAINS edges)\n for _, child_id, edge_data in graph_copy.out_edges(target_domain_node_id, data=True):\n if 'type' in edge_data and 'RK_CONTAINS' in edge_data['type']:\n child_node = graph_copy.nodes[child_id]\n total_capacity = 0\n\n # If it's a PORT, get its physical_capacity_bps directly\n if 'EK_PORT' in child_node.get('type', []):\n total_capacity = child_node.get('physical_capacity_bps', 0)\n else:\n # Otherwise traverse subtree to sum PORT capacities\n # We perform BFS/DFS to collect all PORT nodes under this child\n visited = set()\n stack = [child_id]\n while stack:\n current = stack.pop()\n if current in visited:\n continue\n visited.add(current)\n current_node_data = graph_copy.nodes[current]\n if 'EK_PORT' in current_node_data.get('type', []):\n total_capacity += current_node_data.get('physical_capacity_bps', 0)\n else:\n for _, nxt, e_data in graph_copy.out_edges(current, data=True):\n if 'type' in e_data and 'RK_CONTAINS' in e_data['type']:\n stack.append(nxt)\n\n child_capacities.append((child_node.get('name'), total_capacity))\n\n # Sort by capacity descending\n child_capacities.sort(key=lambda x: x[1], reverse=True)\n\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n\n return_object = {\n \"type\": \"list\",\n \"data\": child_capacities,\n \"updated_graph\": graph_json\n }\n\n return return_object", + "Ground truth exec": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c5", + 16000000000.0 + ], + [ + "ju1.s4.s1c6", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ], + [ + "new_EK_PORT_54", + 1000 + ] + ], + "LLM code exec": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c5", + 16000000000.0 + ], + [ + "ju1.s4.s1c6", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ], + [ + "new_EK_PORT_54", + 0 + ] + ], + "Error": { + "Ground truth": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c5", + 16000000000.0 + ], + [ + "ju1.s4.s1c6", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ], + [ + "new_EK_PORT_54", + 1000 + ] + ], + "Model output": [ + [ + "ju1.s4.s1c1", + 16000000000.0 + ], + [ + "ju1.s4.s1c2", + 16000000000.0 + ], + [ + "ju1.s4.s1c3", + 16000000000.0 + ], + [ + "ju1.s4.s1c4", + 16000000000.0 + ], + [ + "ju1.s4.s1c5", + 16000000000.0 + ], + [ + "ju1.s4.s1c6", + 16000000000.0 + ], + [ + "ju1.s4.s1c7", + 16000000000.0 + ], + [ + "ju1.s4.s1c8", + 16000000000.0 + ], + [ + "ju1.s4.s2c1", + 16000000000.0 + ], + [ + "ju1.s4.s2c2", + 16000000000.0 + ], + [ + "ju1.s4.s2c3", + 16000000000.0 + ], + [ + "ju1.s4.s2c4", + 16000000000.0 + ], + [ + "ju1.s4.s2c5", + 16000000000.0 + ], + [ + "ju1.s4.s2c6", + 16000000000.0 + ], + [ + "ju1.s4.s2c7", + 16000000000.0 + ], + [ + "ju1.s4.s2c8", + 16000000000.0 + ], + [ + "new_EK_PORT_54", + 0 + ] + ] + }, + "Verifier-Error": "Invalid hierarchy: node 'ju1.s4.dom' of type(s) '['EK_CONTROL_DOMAIN']' cannot contain node 'new_EK_PORT_54' of type(s) '['EK_PORT']'", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add node with name 'new_EK_PORT_19' to ju1.a3.m1. Rank direct child nodes of ju1.a3.m1 in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-3, add-rank", + "Result-Correctness": "Fail", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 12.315393831000051, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_19', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a3.m1'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Add new node with name 'new_EK_PORT_19' and type EK_PORT to ju1.a3.m1\n new_port_name = 'new_EK_PORT_19'\n parent_node_name = None\n\n # Find the parent node ID (ju1.a3.m1)\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a3.m1' and 'EK_PACKET_SWITCH' in node[1]['type']:\n parent_node_name = node[0]\n break\n\n if parent_node_name:\n # Add the new port node with some default physical capacity\n graph_copy.add_node(new_port_name, type=['EK_PORT'], physical_capacity_bps=1000)\n # Connect it to the parent\n graph_copy.add_edge(parent_node_name, new_port_name, type=['RK_CONTAINS'])\n\n # Now we need to rank direct child nodes of ju1.a3.m1 based on physical_capacity_bps\n # First identify all direct children of ju1.a3.m1\n direct_children = []\n for u, v, edge_data in graph_copy.edges(data=True):\n if u == parent_node_name and 'RK_CONTAINS' in edge_data.get('type', []):\n # Get node data for v\n node_data = graph_copy.nodes[v]\n direct_children.append((v, node_data))\n\n # Function to compute total physical capacity (sum over all ports under the node)\n def get_total_capacity(node_id, g):\n total = 0\n # If it's a port, directly get its capacity\n node_data = g.nodes[node_id]\n if 'EK_PORT' in node_data.get('type', []):\n return node_data.get('physical_capacity_bps', 0)\n else:\n # Traverse down to all PORT nodes contained within this node\n visited = set()\n stack = [node_id]\n while stack:\n current = stack.pop()\n if current in visited:\n continue\n visited.add(current)\n for u, v, edge_data in g.edges(current, data=True):\n if 'RK_CONTAINS' in edge_data.get('type', []):\n neighbor_data = g.nodes[v]\n if 'EK_PORT' in neighbor_data.get('type', []):\n total += neighbor_data.get('physical_capacity_bps', 0)\n else:\n stack.append(v)\n return total\n\n # Compute capacities for each direct child\n result_list = []\n for node_id, node_attr in direct_children:\n cap = get_total_capacity(node_id, graph_copy)\n result_list.append((node_attr['name'], cap))\n\n # Sort by capacity descending\n result_list.sort(key=lambda x: x[1], reverse=True)\n\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\"type\": \"list\", \"data\": result_list, \"updated_graph\": graph_json}\n return return_object", + "Ground truth exec": [ + [ + "ju1.a3.m1.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c8", + 16000000000.0 + ], + [ + "new_EK_PORT_19", + 1000 + ] + ], + "LLM code exec": [], + "Error": { + "Ground truth": [ + [ + "ju1.a3.m1.s2c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s2c8", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c1", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c2", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c3", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c4", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c5", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c6", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c7", + 16000000000.0 + ], + [ + "ju1.a3.m1.s3c8", + 16000000000.0 + ], + [ + "new_EK_PORT_19", + 1000 + ] + ], + "Model output": [] + }, + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add node with name 'new_EK_PACKET_SWITCH_71' to ju1.a1.m4. Rank direct child nodes of ju1.a1.m4 in the updated graph based on physical_capacity_bps attribute. Return a list of tuple, each tuple has node name and its total physical capacity.", + "Label": "capacity planning, level-3, add-rank", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 9.614974324999935, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PACKET_SWITCH_71', 'type': 'EK_PACKET_SWITCH'}\n parent_node_name = 'ju1.a1.m4'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n ranked_child_nodes = solid_step_rank_child_nodes(graph_data, parent_node_name)\n return_object = {'type': 'list', 'data': ranked_child_nodes}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n\n # Add the new node\n graph_copy.add_node('new_EK_PACKET_SWITCH_71', type=['EK_PACKET_SWITCH'])\n\n # Connect it to ju1.a1.m4\n graph_copy.add_edge('ju1.a1.m4', 'new_EK_PACKET_SWITCH_71', type=['RK_CONTAINS'])\n\n # Find the node ju1.a1.m4\n parent_node_id = None\n for node in graph_copy.nodes(data=True):\n if node[1].get('name') == 'ju1.a1.m4':\n parent_node_id = node[0]\n break\n\n # Function to calculate total capacity of a node\n def calculate_capacity(node_id, graph):\n total_capacity = 0\n node_data = graph.nodes[node_id]\n if 'EK_PORT' in node_data.get('type', []):\n total_capacity += node_data.get('physical_capacity_bps', 0)\n # Get all descendants that are ports\n descendants = nx.descendants(graph, node_id)\n for desc_id in descendants:\n desc_data = graph.nodes[desc_id]\n if 'EK_PORT' in desc_data.get('type', []):\n total_capacity += desc_data.get('physical_capacity_bps', 0)\n return total_capacity\n\n # Get direct children of ju1.a1.m4\n if parent_node_id is not None:\n # Get outgoing edges of type RK_CONTAINS\n direct_children = [\n v for u, v, data in graph_copy.out_edges(parent_node_id, data=True)\n if 'RK_CONTAINS' in data.get('type', [])\n ]\n else:\n direct_children = []\n\n # Calculate capacities for each direct child\n child_capacities = []\n for child_id in direct_children:\n child_data = graph_copy.nodes[child_id]\n child_name = child_data.get('name', child_id)\n capacity = calculate_capacity(child_id, graph_copy)\n child_capacities.append((child_name, capacity))\n\n # Sort by capacity descending\n child_capacities.sort(key=lambda x: x[1], reverse=True)\n\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n\n return_object = {\n 'type': 'list',\n 'data': child_capacities,\n 'updated_graph': graph_json\n }\n\n return return_object", + "Ground truth exec": [ + [ + "ju1.a1.m4.s2c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c8", + 16000000000.0 + ], + [ + "new_EK_PACKET_SWITCH_71", + 1000 + ] + ], + "LLM code exec": [ + [ + "ju1.a1.m4.s2c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c8", + 16000000000.0 + ], + [ + "new_EK_PACKET_SWITCH_71", + 0 + ] + ], + "Error": { + "Ground truth": [ + [ + "ju1.a1.m4.s2c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c8", + 16000000000.0 + ], + [ + "new_EK_PACKET_SWITCH_71", + 1000 + ] + ], + "Model output": [ + [ + "ju1.a1.m4.s2c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s2c8", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c1", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c2", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c3", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c4", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c5", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c6", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c7", + 16000000000.0 + ], + [ + "ju1.a1.m4.s3c8", + 16000000000.0 + ], + [ + "new_EK_PACKET_SWITCH_71", + 0 + ] + ] + }, + "Verifier-Error": "Packet switch node 'new_EK_PACKET_SWITCH_71' has no ports connected to it", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PACKET_SWITCH_62 to ju1.a4.m3. Count the EK_PACKET_SWITCH in ju1.a4.m3 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-3, add-count", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 5.023752320999961, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PACKET_SWITCH_62', 'type': 'EK_PACKET_SWITCH'}\n parent_node_name = 'ju1.a4.m3'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node1 = {\"type\": \"EK_AGG_BLOCK\", \"name\": \"ju1.a4.m3\"}\n node2 = {\"type\": \"EK_PACKET_SWITCH\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n # Add new EK_PACKET_SWITCH node\n new_node_name = 'new_EK_PACKET_SWITCH_62'\n graph_copy.add_node(new_node_name, type=['EK_PACKET_SWITCH'])\n # Connect to ju1.a4.m3\n parent_node = None\n for node in graph_copy.nodes(data=True):\n if node[1]['name'] == 'ju1.a4.m3':\n parent_node = node[0]\n break\n if parent_node:\n graph_copy.add_edge(parent_node, new_node_name, type=['RK_CONTAINS'])\n # Count EK_PACKET_SWITCH in ju1.a4.m3\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PACKET_SWITCH' in node[1]['type'] and node[1]['name'].startswith('ju1.a4.m3'):\n count += 1\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': graph_json\n }\n return return_object", + "Error": { + "type": "error", + "data": "Traceback (most recent call last):\n File \"/NetPress/app-malt/malt_env.py\", line 60, in run_agent_output\n ret = eval(\"process_graph(copy.deepcopy(G))\", exec_namespace)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"\", line 1, in \n File \"\", line 17, in process_graph\nKeyError: 'name'\n" + }, + "Verifier-Error": "The LLM code is not correct, so the safety checker is not applied.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PORT_80 to ju1.a4.m3.s3c2. Count the EK_PORT in ju1.a4.m3.s3c2 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-3, add-count", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 3.2967220010000347, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_80', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a4.m3.s3c2'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node1 = {\"type\": \"EK_PACKET_SWITCH\", \"name\": \"ju1.a4.m3.s3c2\"}\n node2 = {\"type\": \"EK_PORT\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n graph_copy = copy.deepcopy(graph_data)\n graph_copy.add_node('new_EK_PORT_80', type=['EK_PORT'], physical_capacity_bps=1000)\n graph_copy.add_edge('ju1.a4.m3.s3c2', 'new_EK_PORT_80', type=['RK_CONTAINS'])\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PORT' in node[1]['type'] and node[1]['name'].startswith('ju1.a4.m3.s3c2.'):\n count += 1\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': graph_json\n }\n return return_object", + "Error": { + "type": "error", + "data": "Traceback (most recent call last):\n File \"/NetPress/app-malt/malt_env.py\", line 60, in run_agent_output\n ret = eval(\"process_graph(copy.deepcopy(G))\", exec_namespace)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"\", line 1, in \n File \"\", line 7, in process_graph\nKeyError: 'name'\n" + }, + "Verifier-Error": "The LLM code is not correct, so the safety checker is not applied.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PACKET_SWITCH_79 to ju1.a2.m3. Count the EK_PACKET_SWITCH in ju1.a2.m3 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-3, add-count", + "Result-Correctness": "Fail", + "Result-Safety": "Fail", + "GT-Result-Safety": "Pass", + "Result-Latency": 3.532800789000021, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PACKET_SWITCH_79', 'type': 'EK_PACKET_SWITCH'}\n parent_node_name = 'ju1.a2.m3'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node1 = {\"type\": \"EK_AGG_BLOCK\", \"name\": \"ju1.a2.m3\"}\n node2 = {\"type\": \"EK_PACKET_SWITCH\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n\n graph_copy = copy.deepcopy(graph_data)\n\n # Add new packet switch node\n new_node_name = 'new_EK_PACKET_SWITCH_79'\n graph_copy.add_node(new_node_name, type=['EK_PACKET_SWITCH'])\n graph_copy.add_edge('ju1.a2.m3', new_node_name, type=['RK_CONTAINS'])\n\n # Count packet switches in ju1.a2.m3\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PACKET_SWITCH' in node[1]['type'] and node[1]['name'].startswith('ju1.a2.m3'):\n count += 1\n\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': graph_json\n }\n return return_object", + "Error": { + "type": "error", + "data": "Traceback (most recent call last):\n File \"/NetPress/app-malt/malt_env.py\", line 60, in run_agent_output\n ret = eval(\"process_graph(copy.deepcopy(G))\", exec_namespace)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"\", line 1, in \n File \"\", line 13, in process_graph\nKeyError: 'name'\n" + }, + "Verifier-Error": "The LLM code is not correct, so the safety checker is not applied.", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "Query": "Add new_EK_PORT_20 to ju1.a3.m2.s2c4. Count the EK_PORT in ju1.a3.m2.s2c4 in the updated graph. Return the count number as text.", + "Label": "capacity planning, level-3, add-count", + "Result-Correctness": "Pass", + "Result-Safety": "Pass", + "GT-Result-Safety": "Pass", + "Result-Latency": 5.043576413999972, + "Ground truth code": "def ground_truth_process_graph(graph_data):\n new_node = {'name': 'new_EK_PORT_20', 'type': 'EK_PORT'}\n parent_node_name = 'ju1.a3.m2.s2c4'\n graph_data = solid_step_add_node_to_graph(graph_data, new_node, parent_node_name)\n node1 = {\"type\": \"EK_PACKET_SWITCH\", \"name\": \"ju1.a3.m2.s2c4\"}\n node2 = {\"type\": \"EK_PORT\", \"name\": None}\n count = solid_step_counting_query(graph_data, node1, node2)\n return_object = {'type': 'text', 'data': count}\n return return_object", + "LLM code": "def process_graph(graph_data):\n \n # Create a copy of the graph\n graph_copy = copy.deepcopy(graph_data)\n \n # Add new port node\n new_port_name = 'new_EK_PORT_20'\n graph_copy.add_node(new_port_name, type=['EK_PORT'], physical_capacity_bps=1000)\n \n # Connect the new port to the specified switch\n graph_copy.add_edge('ju1.a3.m2.s2c4', new_port_name, type=['RK_CONTAINS'])\n \n # Count EK_PORT nodes under ju1.a3.m2.s2c4\n count = 0\n for node in graph_copy.nodes(data=True):\n if 'EK_PORT' in node[1]['type']:\n # Check if this port is contained by ju1.a3.m2.s2c4\n for predecessor in graph_copy.predecessors(node[0]):\n if graph_copy.nodes[predecessor]['name'] == 'ju1.a3.m2.s2c4':\n count += 1\n break\n \n # Prepare the return object\n graph_json = nx.readwrite.json_graph.node_link_data(graph_copy)\n return_object = {\n 'type': 'text',\n 'data': str(count),\n 'updated_graph': graph_json\n }\n \n return return_object", + "Ground truth exec": "17", + "LLM code exec": "17", + "agent_info": { + "base_url": "http://malt_operator:9009/", + "name": "malt_operator", + "prompt_type": "fewshot_cot" + } + }, + { + "avg_correctness": 0.55, + "avg_safety": 0.5499999999999999, + "avg_latency_s": 7.098093183975 + } + ] +} \ No newline at end of file diff --git a/submissions/ekur12-20260413-001518.provenance.json b/submissions/ekur12-20260413-001518.provenance.json new file mode 100644 index 0000000..54bc99f --- /dev/null +++ b/submissions/ekur12-20260413-001518.provenance.json @@ -0,0 +1,8 @@ +{ + "image_digests": { + "green-agent": "ghcr.io/froot-netsys/malt_agent@sha256:7b6c415de4847a03c6114ad90a1ba19d056f8a3eb9c866eaf08b9ab35c057629", + "malt_operator": "ghcr.io/froot-netsys/a2a_llm@sha256:4dd2c986b5ee439c71d4b758b1fb8b201e940fffa022b87e1c8c375a57abfba9", + "agentbeats-client": "ghcr.io/agentbeats/agentbeats-client@sha256:13dfe3ef4e583a80e7ce2fe3becd0ce3b879841368a7f4fa40b6ebbabeeb014e" + }, + "timestamp": "2026-04-13T00:15:18Z" +} \ No newline at end of file diff --git a/submissions/ekur12-20260413-001518.toml b/submissions/ekur12-20260413-001518.toml new file mode 100644 index 0000000..562fe2c --- /dev/null +++ b/submissions/ekur12-20260413-001518.toml @@ -0,0 +1,28 @@ +[green_agent] +agentbeats_id = "019ba416-0462-7cf2-86f0-bf85123df8a4" +env = { LOG_LEVEL = "INFO" } + +[[participants]] +agentbeats_id = "019ba44f-9d1f-7ff3-8fbe-35c4ecfa40b2" +name = "malt_operator" +env = { + OPENAI_API_KEY = "${NEBIUS_API_KEY}", + OPENAI_API_BASE = "https://api.tokenfactory.nebius.com/v1/", + MODEL_NAME = "openai/Qwen/Qwen3-Coder-480B-A35B-Instruct" +} + +[config] +# Prompt strategy for the agent. Options: "zeroshot_base", "zeroshot_cot", "fewshot_base", "fewshot_cot" +prompt_type = "fewshot_cot" + +# Levels of complexity to generate queries for. Available options: "level1", "level2", "level3". +complexity_level = ["level1", "level2", "level3"] + +# Number of queries to generate for each level of complexity +num_queries = 4 + +# DO NOT MODIFY BELOW THIS LINE. +output_dir = "dump" +output_file = "query_output.jsonl" +benchmark_path = "assessment_queries.jsonl" +regenerate_query = true \ No newline at end of file