diff --git a/evaluation/evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/metadata.json b/evaluation/evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/metadata.json deleted file mode 100644 index e1d31d34a41..00000000000 --- a/evaluation/evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/metadata.json +++ /dev/null @@ -1,10 +0,0 @@ -{ - "Dataset": "ProntoQA", - "Data split": "validation", - "Number of Samples": 6, - "Agent class": "CodeActAgent", - "Model name": "gpt-4o-2024-05-13", - "Start_time": "2024-05-29 17:51:09", - "End_time": "2024-05-29 17:52:24", - "Final Accuracy": "0.83" -} \ No newline at end of file diff --git a/evaluation/evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/output.jsonl b/evaluation/evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/output.jsonl deleted file mode 100644 index 5a6eff4e18a..00000000000 --- a/evaluation/evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/output.jsonl +++ /dev/null @@ -1,6 +0,0 @@ -{"id": "ProntoQA_1", "instance": {"id": "ProntoQA_1", "answer": "B", "context": "Jompuses are not shy. Jompuses are yumpuses. Each yumpus is aggressive. Each yumpus is a dumpus. Dumpuses are not wooden. Dumpuses are wumpuses. Wumpuses are red. Every wumpus is an impus. Each impus is opaque. Impuses are tumpuses. Numpuses are sour. Tumpuses are not sour. Tumpuses are vumpuses. Vumpuses are earthy. Every vumpus is a zumpus. Zumpuses are small. Zumpuses are rompuses. Max is a yumpus.", "options": ["A) True", "B) False"], "question": "Is the following statement true or false? Max is sour.", "raw_logic_programs": ["Predicates:\nJompus($x, bool) ::: Does x belong to Jompus?\nShy($x, bool) ::: Is x shy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nAggressive($x, bool) ::: Is x aggressive?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nWooden($x, bool) ::: Is x wooden?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nRed($x, bool) ::: Is x red?\nImpus($x, bool) ::: Does x belong to Impus?\nOpaque($x, bool) ::: Is x opaque?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nSour($x, bool) ::: Is x sour?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nEarthy($x, bool) ::: Is x earthy?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\n\nFacts:\nYumpus(Max, True)\n\nRules:\nJompus($x, True) >>> Shy($x, False)\nJompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Aggressive($x, True)\nYumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Wooden($x, False)\nDumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Red($x, True)\nWumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Opaque($x, True)\nImpus($x, True) >>> Tumpus($x, True)\nNumpus($x, True) >>> Sour($x, True)\nTumpus($x, True) >>> Sour($x, False)\nTumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Earthy($x, True)\nVumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Small($x, True)\nZumpus($x, True) >>> Rompus($x, True)\n\nQuery:\nSour(Max, False)"]}, "instruction": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/42483/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nJompus($x, bool) ::: Does x belong to Jompus?\nShy($x, bool) ::: Is x shy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nAggressive($x, bool) ::: Is x aggressive?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nWooden($x, bool) ::: Is x wooden?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nRed($x, bool) ::: Is x red?\nImpus($x, bool) ::: Does x belong to Impus?\nOpaque($x, bool) ::: Is x opaque?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nSour($x, bool) ::: Is x sour?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nEarthy($x, bool) ::: Is x earthy?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\n\nFacts:\nYumpus(Max, True)\n\nRules:\nJompus($x, True) >>> Shy($x, False)\nJompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Aggressive($x, True)\nYumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Wooden($x, False)\nDumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Red($x, True)\nWumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Opaque($x, True)\nImpus($x, True) >>> Tumpus($x, True)\nNumpus($x, True) >>> Sour($x, True)\nTumpus($x, True) >>> Sour($x, False)\nTumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Earthy($x, True)\nVumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Small($x, True)\nZumpus($x, True) >>> Rompus($x, True)\n\nQuery:\nSour(Max, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "metadata": {"dataset": "ProntoQA", "data_split": "validation", "agent_class": "CodeActAgent", "model_name": "gpt-4o-2024-05-13", "max_iterations": 10, "start_time": "2024-05-29 10:41:37"}, "history": [[{"id": 0, "timestamp": "2024-05-29T10:42:13.877632", "source": "user", "message": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/42483/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nJompus($x, bool) ::: Does x belong to Jompus?\nShy($x, bool) ::: Is x shy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nAggressive($x, bool) ::: Is x aggressive?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nWooden($x, bool) ::: Is x wooden?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nRed($x, bool) ::: Is x red?\nImpus($x, bool) ::: Does x belong to Impus?\nOpaque($x, bool) ::: Is x opaque?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nSour($x, bool) ::: Is x sour?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nEarthy($x, bool) ::: Is x earthy?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\n\nFacts:\nYumpus(Max, True)\n\nRules:\nJompus($x, True) >>> Shy($x, False)\nJompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Aggressive($x, True)\nYumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Wooden($x, False)\nDumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Red($x, True)\nWumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Opaque($x, True)\nImpus($x, True) >>> Tumpus($x, True)\nNumpus($x, True) >>> Sour($x, True)\nTumpus($x, True) >>> Sour($x, False)\nTumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Earthy($x, True)\nVumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Small($x, True)\nZumpus($x, True) >>> Rompus($x, True)\n\nQuery:\nSour(Max, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "action": "message", "args": {"content": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/42483/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nJompus($x, bool) ::: Does x belong to Jompus?\nShy($x, bool) ::: Is x shy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nAggressive($x, bool) ::: Is x aggressive?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nWooden($x, bool) ::: Is x wooden?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nRed($x, bool) ::: Is x red?\nImpus($x, bool) ::: Does x belong to Impus?\nOpaque($x, bool) ::: Is x opaque?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nSour($x, bool) ::: Is x sour?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nEarthy($x, bool) ::: Is x earthy?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\n\nFacts:\nYumpus(Max, True)\n\nRules:\nJompus($x, True) >>> Shy($x, False)\nJompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Aggressive($x, True)\nYumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Wooden($x, False)\nDumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Red($x, True)\nWumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Opaque($x, True)\nImpus($x, True) >>> Tumpus($x, True)\nNumpus($x, True) >>> Sour($x, True)\nTumpus($x, True) >>> Sour($x, False)\nTumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Earthy($x, True)\nVumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Small($x, True)\nZumpus($x, True) >>> Rompus($x, True)\n\nQuery:\nSour(Max, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 3, "timestamp": "2024-05-29T10:42:15.986571", "source": "agent", "message": "Running Python code interactively: %pip install scitools-pyke", "action": "run_ipython", "args": {"code": "%pip install scitools-pyke", "thought": "Let's start by installing the required package `scitools-pyke` and then proceed with the logic reasoning task.\n\nFirst, I will install the package:", "kernel_init_code": "from agentskills import *"}}, {"id": 4, "timestamp": "2024-05-29T10:42:20.571809", "source": "agent", "message": "Code executed in IPython cell.", "cause": 3, "observation": "run_ipython", "content": "[Package installed successfully]\n[Kernel restarted successfully to load the package]", "extras": {"code": "%pip install scitools-pyke"}}], [{"id": 5, "timestamp": "2024-05-29T10:42:30.538420", "source": "agent", "message": "Running Python code interactively: import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/42483')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/42483\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n\nlogic_programs = \"\"\"\nPredicates:\nJompus($x, bool) ::: Does x belong to Jompus?\nShy($x, bool) ::: Is x shy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nAggressive($x, bool) ::: Is x aggressive?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nWooden($x, bool) ::: Is x wooden?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nRed($x, bool) ::: Is x red?\nImpus($x, bool) ::: Does x belong to Impus?\nOpaque($x, bool) ::: Is x opaque?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nSour($x, bool) ::: Is x sour?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nEarthy($x, bool) ::: Is x earthy?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\n\nFacts:\nYumpus(Max, True)\n\nRules:\nJompus($x, True) >>> Shy($x, False)\nJompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Aggressive($x, True)\nYumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Wooden($x, False)\nDumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Red($x, True)\nWumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Opaque($x, True)\nImpus($x, True) >>> Tumpus($x, True)\nNumpus($x, True) >>> Sour($x, True)\nTumpus($x, True) >>> Sour($x, False)\nTumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Earthy($x, True)\nVumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Small($x, True)\nZumpus($x, True) >>> Rompus($x, True)\n\nQuery:\nSour(Max, False)\n\"\"\"\n\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "action": "run_ipython", "args": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/42483')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/42483\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n\nlogic_programs = \"\"\"\nPredicates:\nJompus($x, bool) ::: Does x belong to Jompus?\nShy($x, bool) ::: Is x shy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nAggressive($x, bool) ::: Is x aggressive?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nWooden($x, bool) ::: Is x wooden?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nRed($x, bool) ::: Is x red?\nImpus($x, bool) ::: Does x belong to Impus?\nOpaque($x, bool) ::: Is x opaque?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nSour($x, bool) ::: Is x sour?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nEarthy($x, bool) ::: Is x earthy?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\n\nFacts:\nYumpus(Max, True)\n\nRules:\nJompus($x, True) >>> Shy($x, False)\nJompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Aggressive($x, True)\nYumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Wooden($x, False)\nDumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Red($x, True)\nWumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Opaque($x, True)\nImpus($x, True) >>> Tumpus($x, True)\nNumpus($x, True) >>> Sour($x, True)\nTumpus($x, True) >>> Sour($x, False)\nTumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Earthy($x, True)\nVumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Small($x, True)\nZumpus($x, True) >>> Rompus($x, True)\n\nQuery:\nSour(Max, False)\n\"\"\"\n\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "thought": "Great! Now, let's proceed with the logic reasoning task. I will import the necessary module, instantiate the `LogicInferenceEngine` class, and use the `safe_execute_program` method to prove the logic programs.", "kernel_init_code": "from agentskills import *"}}, {"id": 6, "timestamp": "2024-05-29T10:42:31.030667", "source": "agent", "message": "Code executed in IPython cell.", "cause": 5, "observation": "run_ipython", "content": "'A'", "extras": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/42483')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/42483\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n\nlogic_programs = \"\"\"\nPredicates:\nJompus($x, bool) ::: Does x belong to Jompus?\nShy($x, bool) ::: Is x shy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nAggressive($x, bool) ::: Is x aggressive?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nWooden($x, bool) ::: Is x wooden?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nRed($x, bool) ::: Is x red?\nImpus($x, bool) ::: Does x belong to Impus?\nOpaque($x, bool) ::: Is x opaque?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nSour($x, bool) ::: Is x sour?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nEarthy($x, bool) ::: Is x earthy?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\n\nFacts:\nYumpus(Max, True)\n\nRules:\nJompus($x, True) >>> Shy($x, False)\nJompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Aggressive($x, True)\nYumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Wooden($x, False)\nDumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Red($x, True)\nWumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Opaque($x, True)\nImpus($x, True) >>> Tumpus($x, True)\nNumpus($x, True) >>> Sour($x, True)\nTumpus($x, True) >>> Sour($x, False)\nTumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Earthy($x, True)\nVumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Small($x, True)\nZumpus($x, True) >>> Rompus($x, True)\n\nQuery:\nSour(Max, False)\n\"\"\"\n\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer"}}], [{"id": 7, "timestamp": "2024-05-29T10:42:32.847071", "source": "agent", "message": "The answer to the query `Sour(Max, False)` is 'A', which indicates that the query is true based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "action": "message", "args": {"content": "The answer to the query `Sour(Max, False)` is 'A', which indicates that the query is true based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "wait_for_response": true}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 9, "timestamp": "2024-05-29T10:42:32.847594", "source": "user", "message": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "action": "message", "args": {"content": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 13, "timestamp": "2024-05-29T10:42:35.136123", "source": "agent", "message": "All done! What's next on the agenda?", "action": "finish", "args": {"outputs": {}, "thought": ""}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}]], "final_message": "'A'", "messages": ["", "", "", "'A'"], "error": null, "test_result": {"result": false}} -{"id": "ProntoQA_2", "instance": {"id": "ProntoQA_2", "answer": "A", "context": "Every tumpus is not angry. Tumpuses are rompuses. Every numpus is not bright. Rompuses are not luminous. Rompuses are yumpuses. Yumpuses are transparent. Yumpuses are zumpuses. Each zumpus is not bitter. Zumpuses are impuses. Impuses are red. Each impus is a dumpus. Every dumpus is happy. Each dumpus is a vumpus. Vumpuses are bright. Every vumpus is a jompus. Jompuses are large. Each jompus is a wumpus. Stella is a yumpus.", "options": ["A) True", "B) False"], "question": "Is the following statement true or false? Stella is bright.", "raw_logic_programs": ["Predicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nAngry($x, bool) ::: Is x angry?\nRompus($x, bool) ::: Does x belong to Rompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBright($x, bool) ::: Is x bright?\nLuminous($x, bool) ::: Is x luminous?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nTransparent($x, bool) ::: Is x transparent?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nBitter($x, bool) ::: Is x bitter?\nImpus($x, bool) ::: Does x belong to Impus?\nRed($x, bool) ::: Is x red?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nHappy($x, bool) ::: Is x happy?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nJompus($x, bool) ::: Does x belong to Jompus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\n\nFacts:\nYumpus(Stella, True)\n\nRules:\nTumpus($x, True) >>> Angry($x, False)\nTumpus($x, True) >>> Rompus($x, True)\nNumpus($x, True) >>> Bright($x, False)\nRompus($x, True) >>> Luminous($x, False)\nRompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Transparent($x, True)\nYumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Bitter($x, False)\nZumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Red($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Happy($x, True)\nDumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Bright($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Large($x, True)\nJompus($x, True) >>> Wumpus($x, True)\n\nQuery:\nBright(Stella, True)"]}, "instruction": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/35688/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nAngry($x, bool) ::: Is x angry?\nRompus($x, bool) ::: Does x belong to Rompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBright($x, bool) ::: Is x bright?\nLuminous($x, bool) ::: Is x luminous?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nTransparent($x, bool) ::: Is x transparent?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nBitter($x, bool) ::: Is x bitter?\nImpus($x, bool) ::: Does x belong to Impus?\nRed($x, bool) ::: Is x red?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nHappy($x, bool) ::: Is x happy?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nJompus($x, bool) ::: Does x belong to Jompus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\n\nFacts:\nYumpus(Stella, True)\n\nRules:\nTumpus($x, True) >>> Angry($x, False)\nTumpus($x, True) >>> Rompus($x, True)\nNumpus($x, True) >>> Bright($x, False)\nRompus($x, True) >>> Luminous($x, False)\nRompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Transparent($x, True)\nYumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Bitter($x, False)\nZumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Red($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Happy($x, True)\nDumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Bright($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Large($x, True)\nJompus($x, True) >>> Wumpus($x, True)\n\nQuery:\nBright(Stella, True)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "metadata": {"dataset": "ProntoQA", "data_split": "validation", "agent_class": "CodeActAgent", "model_name": "gpt-4o-2024-05-13", "max_iterations": 10, "start_time": "2024-05-29 15:05:58"}, "history": [[{"id": 0, "timestamp": "2024-05-29T15:06:38.661585", "source": "user", "message": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/35688/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nAngry($x, bool) ::: Is x angry?\nRompus($x, bool) ::: Does x belong to Rompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBright($x, bool) ::: Is x bright?\nLuminous($x, bool) ::: Is x luminous?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nTransparent($x, bool) ::: Is x transparent?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nBitter($x, bool) ::: Is x bitter?\nImpus($x, bool) ::: Does x belong to Impus?\nRed($x, bool) ::: Is x red?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nHappy($x, bool) ::: Is x happy?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nJompus($x, bool) ::: Does x belong to Jompus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\n\nFacts:\nYumpus(Stella, True)\n\nRules:\nTumpus($x, True) >>> Angry($x, False)\nTumpus($x, True) >>> Rompus($x, True)\nNumpus($x, True) >>> Bright($x, False)\nRompus($x, True) >>> Luminous($x, False)\nRompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Transparent($x, True)\nYumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Bitter($x, False)\nZumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Red($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Happy($x, True)\nDumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Bright($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Large($x, True)\nJompus($x, True) >>> Wumpus($x, True)\n\nQuery:\nBright(Stella, True)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "action": "message", "args": {"content": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/35688/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nAngry($x, bool) ::: Is x angry?\nRompus($x, bool) ::: Does x belong to Rompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBright($x, bool) ::: Is x bright?\nLuminous($x, bool) ::: Is x luminous?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nTransparent($x, bool) ::: Is x transparent?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nBitter($x, bool) ::: Is x bitter?\nImpus($x, bool) ::: Does x belong to Impus?\nRed($x, bool) ::: Is x red?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nHappy($x, bool) ::: Is x happy?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nJompus($x, bool) ::: Does x belong to Jompus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\n\nFacts:\nYumpus(Stella, True)\n\nRules:\nTumpus($x, True) >>> Angry($x, False)\nTumpus($x, True) >>> Rompus($x, True)\nNumpus($x, True) >>> Bright($x, False)\nRompus($x, True) >>> Luminous($x, False)\nRompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Transparent($x, True)\nYumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Bitter($x, False)\nZumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Red($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Happy($x, True)\nDumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Bright($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Large($x, True)\nJompus($x, True) >>> Wumpus($x, True)\n\nQuery:\nBright(Stella, True)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 3, "timestamp": "2024-05-29T15:06:40.628273", "source": "agent", "message": "Running Python code interactively: %pip install scitools-pyke", "action": "run_ipython", "args": {"code": "%pip install scitools-pyke", "thought": "Let's start by installing the required package `scitools-pyke`.", "kernel_init_code": "from agentskills import *"}}, {"id": 4, "timestamp": "2024-05-29T15:06:45.277211", "source": "agent", "message": "Code executed in IPython cell.", "cause": 3, "observation": "run_ipython", "content": "[Package installed successfully]\n[Kernel restarted successfully to load the package]", "extras": {"code": "%pip install scitools-pyke"}}], [{"id": 5, "timestamp": "2024-05-29T15:07:06.638816", "source": "agent", "message": "Running Python code interactively: import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nAngry($x, bool) ::: Is x angry?\nRompus($x, bool) ::: Does x belong to Rompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBright($x, bool) ::: Is x bright?\nLuminous($x, bool) ::: Is x luminous?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nTransparent($x, bool) ::: Is x transparent?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nBitter($x, bool) ::: Is x bitter?\nImpus($x, bool) ::: Does x belong to Impus?\nRed($x, bool) ::: Is x red?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nHappy($x, bool) ::: Is x happy?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nJompus($x, bool) ::: Does x belong to Jompus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\n\nFacts:\nYumpus(Stella, True)\n\nRules:\nTumpus($x, True) >>> Angry($x, False)\nTumpus($x, True) >>> Rompus($x, True)\nNumpus($x, True) >>> Bright($x, False)\nRompus($x, True) >>> Luminous($x, False)\nRompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Transparent($x, True)\nYumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Bitter($x, False)\nZumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Red($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Happy($x, True)\nDumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Bright($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Large($x, True)\nJompus($x, True) >>> Wumpus($x, True)\n\nQuery:\nBright(Stella, True)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "action": "run_ipython", "args": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nAngry($x, bool) ::: Is x angry?\nRompus($x, bool) ::: Does x belong to Rompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBright($x, bool) ::: Is x bright?\nLuminous($x, bool) ::: Is x luminous?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nTransparent($x, bool) ::: Is x transparent?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nBitter($x, bool) ::: Is x bitter?\nImpus($x, bool) ::: Does x belong to Impus?\nRed($x, bool) ::: Is x red?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nHappy($x, bool) ::: Is x happy?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nJompus($x, bool) ::: Does x belong to Jompus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\n\nFacts:\nYumpus(Stella, True)\n\nRules:\nTumpus($x, True) >>> Angry($x, False)\nTumpus($x, True) >>> Rompus($x, True)\nNumpus($x, True) >>> Bright($x, False)\nRompus($x, True) >>> Luminous($x, False)\nRompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Transparent($x, True)\nYumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Bitter($x, False)\nZumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Red($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Happy($x, True)\nDumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Bright($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Large($x, True)\nJompus($x, True) >>> Wumpus($x, True)\n\nQuery:\nBright(Stella, True)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "thought": "Now, let's proceed with the logic reasoning task. I will import the necessary module, instantiate the `LogicInferenceEngine` class, and use the `safe_execute_program` method to prove the logic programs.", "kernel_init_code": "from agentskills import *"}}, {"id": 6, "timestamp": "2024-05-29T15:07:07.122155", "source": "agent", "message": "Code executed in IPython cell.", "cause": 5, "observation": "run_ipython", "content": "'A'", "extras": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nAngry($x, bool) ::: Is x angry?\nRompus($x, bool) ::: Does x belong to Rompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBright($x, bool) ::: Is x bright?\nLuminous($x, bool) ::: Is x luminous?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nTransparent($x, bool) ::: Is x transparent?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nBitter($x, bool) ::: Is x bitter?\nImpus($x, bool) ::: Does x belong to Impus?\nRed($x, bool) ::: Is x red?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nHappy($x, bool) ::: Is x happy?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nJompus($x, bool) ::: Does x belong to Jompus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\n\nFacts:\nYumpus(Stella, True)\n\nRules:\nTumpus($x, True) >>> Angry($x, False)\nTumpus($x, True) >>> Rompus($x, True)\nNumpus($x, True) >>> Bright($x, False)\nRompus($x, True) >>> Luminous($x, False)\nRompus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Transparent($x, True)\nYumpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Bitter($x, False)\nZumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Red($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Happy($x, True)\nDumpus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Bright($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Large($x, True)\nJompus($x, True) >>> Wumpus($x, True)\n\nQuery:\nBright(Stella, True)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer"}}], [{"id": 7, "timestamp": "2024-05-29T15:07:09.295867", "source": "agent", "message": "The answer to the query `Bright(Stella, True)` is `A`, which indicates that the query is true based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "action": "message", "args": {"content": "The answer to the query `Bright(Stella, True)` is `A`, which indicates that the query is true based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "wait_for_response": true}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 9, "timestamp": "2024-05-29T15:07:09.296958", "source": "user", "message": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "action": "message", "args": {"content": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 13, "timestamp": "2024-05-29T15:07:11.075946", "source": "agent", "message": "All done! What's next on the agenda?", "action": "finish", "args": {"outputs": {}, "thought": ""}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}]], "final_message": "'A'", "messages": ["", "", "", "'A'"], "error": null, "test_result": {"result": true}} -{"id": "ProntoQA_3", "instance": {"id": "ProntoQA_3", "answer": "A", "context": "Vumpuses are floral. Vumpuses are tumpuses. Tumpuses are brown. Each tumpus is a wumpus. Wumpuses are small. Each wumpus is a rompus. Each zumpus is metallic. Every rompus is happy. Rompuses are impuses. Each impus is amenable. Each impus is a dumpus. Every dumpus is not metallic. Dumpuses are numpuses. Each numpus is bitter. Each numpus is a jompus. Every jompus is cold. Each jompus is a yumpus. Wren is a tumpus.", "options": ["A) True", "B) False"], "question": "Is the following statement true or false? Wren is not metallic.", "raw_logic_programs": ["Predicates:\nVumpus($x, bool) ::: Does x belong to Vumpus?\nFloral($x, bool) ::: Is x floral?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nBrown($x, bool) ::: Is x brown?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nMetallic($x, bool) ::: Is x metallic?\nHappy($x, bool) ::: Is x happy?\nImpus($x, bool) ::: Does x belong to Impus?\nAmenable($x, bool) ::: Is x amenable?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBitter($x, bool) ::: Is x bitter?\nJompus($x, bool) ::: Does x belong to Jompus?\nCold($x, bool) ::: Is x cold?\nYumpus($x, bool) ::: Does x belong to Yumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nVumpus($x, True) >>> Floral($x, True)\nVumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Brown($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Small($x, True)\nWumpus($x, True) >>> Rompus($x, True)\nZumpus($x, True) >>> Metallic($x, True)\nRompus($x, True) >>> Happy($x, True)\nRompus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Amenable($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Metallic($x, False)\nDumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Bitter($x, True)\nNumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Cold($x, True)\nJompus($x, True) >>> Yumpus($x, True)\n\nQuery:\nMetallic(Wren, False)"]}, "instruction": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/35688/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nVumpus($x, bool) ::: Does x belong to Vumpus?\nFloral($x, bool) ::: Is x floral?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nBrown($x, bool) ::: Is x brown?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nMetallic($x, bool) ::: Is x metallic?\nHappy($x, bool) ::: Is x happy?\nImpus($x, bool) ::: Does x belong to Impus?\nAmenable($x, bool) ::: Is x amenable?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBitter($x, bool) ::: Is x bitter?\nJompus($x, bool) ::: Does x belong to Jompus?\nCold($x, bool) ::: Is x cold?\nYumpus($x, bool) ::: Does x belong to Yumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nVumpus($x, True) >>> Floral($x, True)\nVumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Brown($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Small($x, True)\nWumpus($x, True) >>> Rompus($x, True)\nZumpus($x, True) >>> Metallic($x, True)\nRompus($x, True) >>> Happy($x, True)\nRompus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Amenable($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Metallic($x, False)\nDumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Bitter($x, True)\nNumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Cold($x, True)\nJompus($x, True) >>> Yumpus($x, True)\n\nQuery:\nMetallic(Wren, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "metadata": {"dataset": "ProntoQA", "data_split": "validation", "agent_class": "CodeActAgent", "model_name": "gpt-4o-2024-05-13", "max_iterations": 10, "start_time": "2024-05-29 15:05:58"}, "history": [[{"id": 17, "timestamp": "2024-05-29T15:07:45.612184", "source": "user", "message": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/35688/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nVumpus($x, bool) ::: Does x belong to Vumpus?\nFloral($x, bool) ::: Is x floral?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nBrown($x, bool) ::: Is x brown?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nMetallic($x, bool) ::: Is x metallic?\nHappy($x, bool) ::: Is x happy?\nImpus($x, bool) ::: Does x belong to Impus?\nAmenable($x, bool) ::: Is x amenable?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBitter($x, bool) ::: Is x bitter?\nJompus($x, bool) ::: Does x belong to Jompus?\nCold($x, bool) ::: Is x cold?\nYumpus($x, bool) ::: Does x belong to Yumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nVumpus($x, True) >>> Floral($x, True)\nVumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Brown($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Small($x, True)\nWumpus($x, True) >>> Rompus($x, True)\nZumpus($x, True) >>> Metallic($x, True)\nRompus($x, True) >>> Happy($x, True)\nRompus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Amenable($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Metallic($x, False)\nDumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Bitter($x, True)\nNumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Cold($x, True)\nJompus($x, True) >>> Yumpus($x, True)\n\nQuery:\nMetallic(Wren, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "action": "message", "args": {"content": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/35688/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nVumpus($x, bool) ::: Does x belong to Vumpus?\nFloral($x, bool) ::: Is x floral?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nBrown($x, bool) ::: Is x brown?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nMetallic($x, bool) ::: Is x metallic?\nHappy($x, bool) ::: Is x happy?\nImpus($x, bool) ::: Does x belong to Impus?\nAmenable($x, bool) ::: Is x amenable?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBitter($x, bool) ::: Is x bitter?\nJompus($x, bool) ::: Does x belong to Jompus?\nCold($x, bool) ::: Is x cold?\nYumpus($x, bool) ::: Does x belong to Yumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nVumpus($x, True) >>> Floral($x, True)\nVumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Brown($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Small($x, True)\nWumpus($x, True) >>> Rompus($x, True)\nZumpus($x, True) >>> Metallic($x, True)\nRompus($x, True) >>> Happy($x, True)\nRompus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Amenable($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Metallic($x, False)\nDumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Bitter($x, True)\nNumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Cold($x, True)\nJompus($x, True) >>> Yumpus($x, True)\n\nQuery:\nMetallic(Wren, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 20, "timestamp": "2024-05-29T15:07:47.955137", "source": "agent", "message": "Running Python code interactively: %pip install scitools-pyke", "action": "run_ipython", "args": {"code": "%pip install scitools-pyke", "thought": "Let's start by installing the required package `scitools-pyke`.", "kernel_init_code": "from agentskills import *"}}, {"id": 21, "timestamp": "2024-05-29T15:07:52.300112", "source": "agent", "message": "Code executed in IPython cell.", "cause": 20, "observation": "run_ipython", "content": "[Package installed successfully]\n[Kernel restarted successfully to load the package]", "extras": {"code": "%pip install scitools-pyke"}}], [{"id": 22, "timestamp": "2024-05-29T15:08:08.081969", "source": "agent", "message": "Running Python code interactively: import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nVumpus($x, bool) ::: Does x belong to Vumpus?\nFloral($x, bool) ::: Is x floral?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nBrown($x, bool) ::: Is x brown?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nMetallic($x, bool) ::: Is x metallic?\nHappy($x, bool) ::: Is x happy?\nImpus($x, bool) ::: Does x belong to Impus?\nAmenable($x, bool) ::: Is x amenable?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBitter($x, bool) ::: Is x bitter?\nJompus($x, bool) ::: Does x belong to Jompus?\nCold($x, bool) ::: Is x cold?\nYumpus($x, bool) ::: Does x belong to Yumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nVumpus($x, True) >>> Floral($x, True)\nVumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Brown($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Small($x, True)\nWumpus($x, True) >>> Rompus($x, True)\nZumpus($x, True) >>> Metallic($x, True)\nRompus($x, True) >>> Happy($x, True)\nRompus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Amenable($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Metallic($x, False)\nDumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Bitter($x, True)\nNumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Cold($x, True)\nJompus($x, True) >>> Yumpus($x, True)\n\nQuery:\nMetallic(Wren, False)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "action": "run_ipython", "args": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nVumpus($x, bool) ::: Does x belong to Vumpus?\nFloral($x, bool) ::: Is x floral?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nBrown($x, bool) ::: Is x brown?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nMetallic($x, bool) ::: Is x metallic?\nHappy($x, bool) ::: Is x happy?\nImpus($x, bool) ::: Does x belong to Impus?\nAmenable($x, bool) ::: Is x amenable?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBitter($x, bool) ::: Is x bitter?\nJompus($x, bool) ::: Does x belong to Jompus?\nCold($x, bool) ::: Is x cold?\nYumpus($x, bool) ::: Does x belong to Yumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nVumpus($x, True) >>> Floral($x, True)\nVumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Brown($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Small($x, True)\nWumpus($x, True) >>> Rompus($x, True)\nZumpus($x, True) >>> Metallic($x, True)\nRompus($x, True) >>> Happy($x, True)\nRompus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Amenable($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Metallic($x, False)\nDumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Bitter($x, True)\nNumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Cold($x, True)\nJompus($x, True) >>> Yumpus($x, True)\n\nQuery:\nMetallic(Wren, False)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "thought": "Now, let's proceed with the logic reasoning task by using the code in `/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688/logic_inference.py`.", "kernel_init_code": "from agentskills import *"}}, {"id": 23, "timestamp": "2024-05-29T15:08:08.562428", "source": "agent", "message": "Code executed in IPython cell.", "cause": 22, "observation": "run_ipython", "content": "'A'", "extras": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nVumpus($x, bool) ::: Does x belong to Vumpus?\nFloral($x, bool) ::: Is x floral?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nBrown($x, bool) ::: Is x brown?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nSmall($x, bool) ::: Is x small?\nRompus($x, bool) ::: Does x belong to Rompus?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nMetallic($x, bool) ::: Is x metallic?\nHappy($x, bool) ::: Is x happy?\nImpus($x, bool) ::: Does x belong to Impus?\nAmenable($x, bool) ::: Is x amenable?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nBitter($x, bool) ::: Is x bitter?\nJompus($x, bool) ::: Does x belong to Jompus?\nCold($x, bool) ::: Is x cold?\nYumpus($x, bool) ::: Does x belong to Yumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nVumpus($x, True) >>> Floral($x, True)\nVumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Brown($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Small($x, True)\nWumpus($x, True) >>> Rompus($x, True)\nZumpus($x, True) >>> Metallic($x, True)\nRompus($x, True) >>> Happy($x, True)\nRompus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Amenable($x, True)\nImpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Metallic($x, False)\nDumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Bitter($x, True)\nNumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Cold($x, True)\nJompus($x, True) >>> Yumpus($x, True)\n\nQuery:\nMetallic(Wren, False)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/35688')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer"}}], [{"id": 24, "timestamp": "2024-05-29T15:08:10.035241", "source": "agent", "message": "The answer to the query `Metallic(Wren, False)` is `A`.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "action": "message", "args": {"content": "The answer to the query `Metallic(Wren, False)` is `A`.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "wait_for_response": true}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 26, "timestamp": "2024-05-29T15:08:10.035957", "source": "user", "message": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "action": "message", "args": {"content": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 30, "timestamp": "2024-05-29T15:08:11.826573", "source": "agent", "message": "All done! What's next on the agenda?", "action": "finish", "args": {"outputs": {}, "thought": ""}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}]], "final_message": "'A'", "messages": ["", "", "", "'A'"], "error": null, "test_result": {"result": true}} -{"id": "ProntoQA_4", "instance": {"id": "ProntoQA_4", "answer": "B", "context": "Rompuses are spicy. Every rompus is an impus. Yumpuses are not small. Impuses are orange. Impuses are zumpuses. Zumpuses are not hot. Zumpuses are numpuses. Numpuses are metallic. Numpuses are wumpuses. Every wumpus is not kind. Each wumpus is a dumpus. Each dumpus is not bright. Every dumpus is a jompus. Jompuses are small. Jompuses are vumpuses. Each vumpus is not shy. Every vumpus is a tumpus. Alex is a zumpus.", "options": ["A) True", "B) False"], "question": "Is the following statement true or false? Alex is not small.", "raw_logic_programs": ["Predicates:\nSpicy($x, bool) ::: Is x spicy?\nImpus($x, bool) ::: Does x belong to Impus?\nSmall($x, bool) ::: Is x small?\nHot($x, bool) ::: Is x hot?\nMetallic($x, bool) ::: Is x metallic?\nKind($x, bool) ::: Is x kind?\nBright($x, bool) ::: Is x bright?\n\nFacts:\nZumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Spicy($x, True)\nRompus($x, True) >>> Impus($x, True)\nYumpus($x, True) >>> Small($x, False)\nImpus($x, True) >>> Orange($x, True)\nImpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Hot($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Metallic($x, True)\nNumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Kind($x, False)\nWumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Bright($x, False)\nDumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Small($x, True)\nJompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Shy($x, False)\nVumpus($x, True) >>> Tumpus($x, True)\n\nQuery:\nSmall(Alex, False)"]}, "instruction": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/80034/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nSpicy($x, bool) ::: Is x spicy?\nImpus($x, bool) ::: Does x belong to Impus?\nSmall($x, bool) ::: Is x small?\nHot($x, bool) ::: Is x hot?\nMetallic($x, bool) ::: Is x metallic?\nKind($x, bool) ::: Is x kind?\nBright($x, bool) ::: Is x bright?\n\nFacts:\nZumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Spicy($x, True)\nRompus($x, True) >>> Impus($x, True)\nYumpus($x, True) >>> Small($x, False)\nImpus($x, True) >>> Orange($x, True)\nImpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Hot($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Metallic($x, True)\nNumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Kind($x, False)\nWumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Bright($x, False)\nDumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Small($x, True)\nJompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Shy($x, False)\nVumpus($x, True) >>> Tumpus($x, True)\n\nQuery:\nSmall(Alex, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "history": [[{"id": 0, "timestamp": "2024-05-29T17:16:37.408157", "source": "user", "message": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/80034/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nSpicy($x, bool) ::: Is x spicy?\nImpus($x, bool) ::: Does x belong to Impus?\nSmall($x, bool) ::: Is x small?\nHot($x, bool) ::: Is x hot?\nMetallic($x, bool) ::: Is x metallic?\nKind($x, bool) ::: Is x kind?\nBright($x, bool) ::: Is x bright?\n\nFacts:\nZumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Spicy($x, True)\nRompus($x, True) >>> Impus($x, True)\nYumpus($x, True) >>> Small($x, False)\nImpus($x, True) >>> Orange($x, True)\nImpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Hot($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Metallic($x, True)\nNumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Kind($x, False)\nWumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Bright($x, False)\nDumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Small($x, True)\nJompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Shy($x, False)\nVumpus($x, True) >>> Tumpus($x, True)\n\nQuery:\nSmall(Alex, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "action": "message", "args": {"content": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/80034/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nSpicy($x, bool) ::: Is x spicy?\nImpus($x, bool) ::: Does x belong to Impus?\nSmall($x, bool) ::: Is x small?\nHot($x, bool) ::: Is x hot?\nMetallic($x, bool) ::: Is x metallic?\nKind($x, bool) ::: Is x kind?\nBright($x, bool) ::: Is x bright?\n\nFacts:\nZumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Spicy($x, True)\nRompus($x, True) >>> Impus($x, True)\nYumpus($x, True) >>> Small($x, False)\nImpus($x, True) >>> Orange($x, True)\nImpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Hot($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Metallic($x, True)\nNumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Kind($x, False)\nWumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Bright($x, False)\nDumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Small($x, True)\nJompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Shy($x, False)\nVumpus($x, True) >>> Tumpus($x, True)\n\nQuery:\nSmall(Alex, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 3, "timestamp": "2024-05-29T17:16:39.011346", "source": "agent", "message": "Running Python code interactively: %pip install scitools-pyke", "action": "run_ipython", "args": {"code": "%pip install scitools-pyke", "thought": "Let's start by installing the required package `scitools-pyke`.", "kernel_init_code": "from agentskills import *"}}, {"id": 4, "timestamp": "2024-05-29T17:16:44.064480", "source": "agent", "message": "Code executed in IPython cell.", "cause": 3, "observation": "run_ipython", "content": "[Package installed successfully]\n[Kernel restarted successfully to load the package]", "extras": {"code": "%pip install scitools-pyke"}}], [{"id": 5, "timestamp": "2024-05-29T17:16:57.423471", "source": "agent", "message": "Running Python code interactively: import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nSpicy($x, bool) ::: Is x spicy?\nImpus($x, bool) ::: Does x belong to Impus?\nSmall($x, bool) ::: Is x small?\nHot($x, bool) ::: Is x hot?\nMetallic($x, bool) ::: Is x metallic?\nKind($x, bool) ::: Is x kind?\nBright($x, bool) ::: Is x bright?\n\nFacts:\nZumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Spicy($x, True)\nRompus($x, True) >>> Impus($x, True)\nYumpus($x, True) >>> Small($x, False)\nImpus($x, True) >>> Orange($x, True)\nImpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Hot($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Metallic($x, True)\nNumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Kind($x, False)\nWumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Bright($x, False)\nDumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Small($x, True)\nJompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Shy($x, False)\nVumpus($x, True) >>> Tumpus($x, True)\n\nQuery:\nSmall(Alex, False)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "action": "run_ipython", "args": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nSpicy($x, bool) ::: Is x spicy?\nImpus($x, bool) ::: Does x belong to Impus?\nSmall($x, bool) ::: Is x small?\nHot($x, bool) ::: Is x hot?\nMetallic($x, bool) ::: Is x metallic?\nKind($x, bool) ::: Is x kind?\nBright($x, bool) ::: Is x bright?\n\nFacts:\nZumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Spicy($x, True)\nRompus($x, True) >>> Impus($x, True)\nYumpus($x, True) >>> Small($x, False)\nImpus($x, True) >>> Orange($x, True)\nImpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Hot($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Metallic($x, True)\nNumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Kind($x, False)\nWumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Bright($x, False)\nDumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Small($x, True)\nJompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Shy($x, False)\nVumpus($x, True) >>> Tumpus($x, True)\n\nQuery:\nSmall(Alex, False)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "thought": "Now, let's proceed by importing the necessary module and executing the logic program using the provided code.", "kernel_init_code": "from agentskills import *"}}, {"id": 6, "timestamp": "2024-05-29T17:16:57.957336", "source": "agent", "message": "Code executed in IPython cell.", "cause": 5, "observation": "run_ipython", "content": "'B'", "extras": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nlogic_programs = \"\"\"\nPredicates:\nSpicy($x, bool) ::: Is x spicy?\nImpus($x, bool) ::: Does x belong to Impus?\nSmall($x, bool) ::: Is x small?\nHot($x, bool) ::: Is x hot?\nMetallic($x, bool) ::: Is x metallic?\nKind($x, bool) ::: Is x kind?\nBright($x, bool) ::: Is x bright?\n\nFacts:\nZumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Spicy($x, True)\nRompus($x, True) >>> Impus($x, True)\nYumpus($x, True) >>> Small($x, False)\nImpus($x, True) >>> Orange($x, True)\nImpus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Hot($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Metallic($x, True)\nNumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Kind($x, False)\nWumpus($x, True) >>> Dumpus($x, True)\nDumpus($x, True) >>> Bright($x, False)\nDumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Small($x, True)\nJompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Shy($x, False)\nVumpus($x, True) >>> Tumpus($x, True)\n\nQuery:\nSmall(Alex, False)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, '/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer"}}], [{"id": 7, "timestamp": "2024-05-29T17:17:00.461597", "source": "agent", "message": "The answer to the query `Small(Alex, False)` is 'B', which indicates that the query is false based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "action": "message", "args": {"content": "The answer to the query `Small(Alex, False)` is 'B', which indicates that the query is false based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "wait_for_response": true}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 9, "timestamp": "2024-05-29T17:17:00.461890", "source": "user", "message": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "action": "message", "args": {"content": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 13, "timestamp": "2024-05-29T17:17:02.982155", "source": "agent", "message": "All done! What's next on the agenda?", "action": "finish", "args": {"outputs": {}, "thought": ""}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}]], "final_message": "B", "messages": ["", "", "", "'B'"], "error": null, "test_result": {"result": true}} -{"id": "ProntoQA_5", "instance": {"id": "ProntoQA_5", "answer": "A", "context": "Rompuses are mean. Rompuses are zumpuses. Each zumpus is not happy. Each zumpus is a numpus. Each numpus is not temperate. Each numpus is a tumpus. Tumpuses are not large. Tumpuses are yumpuses. Every yumpus is earthy. Each yumpus is a jompus. Jompuses are blue. Every jompus is a wumpus. Wumpuses are not dull. Wumpuses are impuses. Each vumpus is dull. Impuses are sour. Impuses are dumpuses. Alex is a numpus.", "options": ["A) True", "B) False"], "question": "Is the following statement true or false? Alex is not dull.", "raw_logic_programs": ["Predicates:\nRompus($x, bool) ::: Does x belong to Rompus?\nMean($x, bool) ::: Is x mean?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nHappy($x, bool) ::: Is x happy?\nNumpus($x, bool) ::: Does x belong to Numpus?\nTemperate($x, bool) ::: Is x temperate?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nEarthy($x, bool) ::: Is x earthy?\nJompus($x, bool) ::: Does x belong to Jompus?\nBlue($x, bool) ::: Is x blue?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nDull($x, bool) ::: Is x dull?\nImpus($x, bool) ::: Does x belong to Impus?\nSour($x, bool) ::: Is x sour?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nVumpus($x, bool) ::: Does x belong to Vumpus?\n\nFacts:\nNumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Mean($x, True)\nRompus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Happy($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Temperate($x, False)\nNumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Large($x, False)\nTumpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Earthy($x, True)\nYumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Blue($x, True)\nJompus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Impus($x, True)\nVumpus($x, True) >>> Dull($x, True)\nImpus($x, True) >>> Sour($x, True)\nImpus($x, True) >>> Dumpus($x, True)\n\nQuery:\nDull(Alex, False)"]}, "instruction": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/80034/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nRompus($x, bool) ::: Does x belong to Rompus?\nMean($x, bool) ::: Is x mean?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nHappy($x, bool) ::: Is x happy?\nNumpus($x, bool) ::: Does x belong to Numpus?\nTemperate($x, bool) ::: Is x temperate?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nEarthy($x, bool) ::: Is x earthy?\nJompus($x, bool) ::: Does x belong to Jompus?\nBlue($x, bool) ::: Is x blue?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nDull($x, bool) ::: Is x dull?\nImpus($x, bool) ::: Does x belong to Impus?\nSour($x, bool) ::: Is x sour?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nVumpus($x, bool) ::: Does x belong to Vumpus?\n\nFacts:\nNumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Mean($x, True)\nRompus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Happy($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Temperate($x, False)\nNumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Large($x, False)\nTumpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Earthy($x, True)\nYumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Blue($x, True)\nJompus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Impus($x, True)\nVumpus($x, True) >>> Dull($x, True)\nImpus($x, True) >>> Sour($x, True)\nImpus($x, True) >>> Dumpus($x, True)\n\nQuery:\nDull(Alex, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "history": [[{"id": 17, "timestamp": "2024-05-29T17:17:54.764382", "source": "user", "message": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/80034/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nRompus($x, bool) ::: Does x belong to Rompus?\nMean($x, bool) ::: Is x mean?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nHappy($x, bool) ::: Is x happy?\nNumpus($x, bool) ::: Does x belong to Numpus?\nTemperate($x, bool) ::: Is x temperate?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nEarthy($x, bool) ::: Is x earthy?\nJompus($x, bool) ::: Does x belong to Jompus?\nBlue($x, bool) ::: Is x blue?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nDull($x, bool) ::: Is x dull?\nImpus($x, bool) ::: Does x belong to Impus?\nSour($x, bool) ::: Is x sour?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nVumpus($x, bool) ::: Does x belong to Vumpus?\n\nFacts:\nNumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Mean($x, True)\nRompus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Happy($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Temperate($x, False)\nNumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Large($x, False)\nTumpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Earthy($x, True)\nYumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Blue($x, True)\nJompus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Impus($x, True)\nVumpus($x, True) >>> Dull($x, True)\nImpus($x, True) >>> Sour($x, True)\nImpus($x, True) >>> Dumpus($x, True)\n\nQuery:\nDull(Alex, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "action": "message", "args": {"content": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. You first need to install a python package through ```pip install scitools-pyke```. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/80034/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nRompus($x, bool) ::: Does x belong to Rompus?\nMean($x, bool) ::: Is x mean?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nHappy($x, bool) ::: Is x happy?\nNumpus($x, bool) ::: Does x belong to Numpus?\nTemperate($x, bool) ::: Is x temperate?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nEarthy($x, bool) ::: Is x earthy?\nJompus($x, bool) ::: Does x belong to Jompus?\nBlue($x, bool) ::: Is x blue?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nDull($x, bool) ::: Is x dull?\nImpus($x, bool) ::: Does x belong to Impus?\nSour($x, bool) ::: Is x sour?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nVumpus($x, bool) ::: Does x belong to Vumpus?\n\nFacts:\nNumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Mean($x, True)\nRompus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Happy($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Temperate($x, False)\nNumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Large($x, False)\nTumpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Earthy($x, True)\nYumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Blue($x, True)\nJompus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Impus($x, True)\nVumpus($x, True) >>> Dull($x, True)\nImpus($x, True) >>> Sour($x, True)\nImpus($x, True) >>> Dumpus($x, True)\n\nQuery:\nDull(Alex, False)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 20, "timestamp": "2024-05-29T17:17:56.628057", "source": "agent", "message": "Running Python code interactively: %pip install scitools-pyke", "action": "run_ipython", "args": {"code": "%pip install scitools-pyke", "thought": "Let's start by installing the required package `scitools-pyke`.", "kernel_init_code": "from agentskills import *"}}, {"id": 21, "timestamp": "2024-05-29T17:18:01.477265", "source": "agent", "message": "Code executed in IPython cell.", "cause": 20, "observation": "run_ipython", "content": "[Package installed successfully]\n[Kernel restarted successfully to load the package]", "extras": {"code": "%pip install scitools-pyke"}}], [{"id": 22, "timestamp": "2024-05-29T17:18:17.639407", "source": "agent", "message": "Running Python code interactively: import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n\nlogic_programs = \"\"\"\nPredicates:\nRompus($x, bool) ::: Does x belong to Rompus?\nMean($x, bool) ::: Is x mean?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nHappy($x, bool) ::: Is x happy?\nNumpus($x, bool) ::: Does x belong to Numpus?\nTemperate($x, bool) ::: Is x temperate?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nEarthy($x, bool) ::: Is x earthy?\nJompus($x, bool) ::: Does x belong to Jompus?\nBlue($x, bool) ::: Is x blue?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nDull($x, bool) ::: Is x dull?\nImpus($x, bool) ::: Does x belong to Impus?\nSour($x, bool) ::: Is x sour?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nVumpus($x, bool) ::: Does x belong to Vumpus?\n\nFacts:\nNumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Mean($x, True)\nRompus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Happy($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Temperate($x, False)\nNumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Large($x, False)\nTumpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Earthy($x, True)\nYumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Blue($x, True)\nJompus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Impus($x, True)\nVumpus($x, True) >>> Dull($x, True)\nImpus($x, True) >>> Sour($x, True)\nImpus($x, True) >>> Dumpus($x, True)\n\nQuery:\nDull(Alex, False)\n\"\"\"\n\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "action": "run_ipython", "args": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n\nlogic_programs = \"\"\"\nPredicates:\nRompus($x, bool) ::: Does x belong to Rompus?\nMean($x, bool) ::: Is x mean?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nHappy($x, bool) ::: Is x happy?\nNumpus($x, bool) ::: Does x belong to Numpus?\nTemperate($x, bool) ::: Is x temperate?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nEarthy($x, bool) ::: Is x earthy?\nJompus($x, bool) ::: Does x belong to Jompus?\nBlue($x, bool) ::: Is x blue?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nDull($x, bool) ::: Is x dull?\nImpus($x, bool) ::: Does x belong to Impus?\nSour($x, bool) ::: Is x sour?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nVumpus($x, bool) ::: Does x belong to Vumpus?\n\nFacts:\nNumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Mean($x, True)\nRompus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Happy($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Temperate($x, False)\nNumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Large($x, False)\nTumpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Earthy($x, True)\nYumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Blue($x, True)\nJompus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Impus($x, True)\nVumpus($x, True) >>> Dull($x, True)\nImpus($x, True) >>> Sour($x, True)\nImpus($x, True) >>> Dumpus($x, True)\n\nQuery:\nDull(Alex, False)\n\"\"\"\n\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "thought": "Next, let's import the necessary module and instantiate the `LogicInferenceEngine` class. Then, we will use the `safe_execute_program` method to prove the logic programs.", "kernel_init_code": "from agentskills import *"}}, {"id": 23, "timestamp": "2024-05-29T17:18:18.119648", "source": "agent", "message": "Code executed in IPython cell.", "cause": 22, "observation": "run_ipython", "content": "'A'", "extras": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/80034\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n\nlogic_programs = \"\"\"\nPredicates:\nRompus($x, bool) ::: Does x belong to Rompus?\nMean($x, bool) ::: Is x mean?\nZumpus($x, bool) ::: Does x belong to Zumpus?\nHappy($x, bool) ::: Is x happy?\nNumpus($x, bool) ::: Does x belong to Numpus?\nTemperate($x, bool) ::: Is x temperate?\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nEarthy($x, bool) ::: Is x earthy?\nJompus($x, bool) ::: Does x belong to Jompus?\nBlue($x, bool) ::: Is x blue?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nDull($x, bool) ::: Is x dull?\nImpus($x, bool) ::: Does x belong to Impus?\nSour($x, bool) ::: Is x sour?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nVumpus($x, bool) ::: Does x belong to Vumpus?\n\nFacts:\nNumpus(Alex, True)\n\nRules:\nRompus($x, True) >>> Mean($x, True)\nRompus($x, True) >>> Zumpus($x, True)\nZumpus($x, True) >>> Happy($x, False)\nZumpus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Temperate($x, False)\nNumpus($x, True) >>> Tumpus($x, True)\nTumpus($x, True) >>> Large($x, False)\nTumpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Earthy($x, True)\nYumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Blue($x, True)\nJompus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Impus($x, True)\nVumpus($x, True) >>> Dull($x, True)\nImpus($x, True) >>> Sour($x, True)\nImpus($x, True) >>> Dumpus($x, True)\n\nQuery:\nDull(Alex, False)\n\"\"\"\n\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer"}}], [{"id": 24, "timestamp": "2024-05-29T17:18:19.708516", "source": "agent", "message": "The answer to the query `Dull(Alex, False)` is `A`.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "action": "message", "args": {"content": "The answer to the query `Dull(Alex, False)` is `A`.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "wait_for_response": true}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 26, "timestamp": "2024-05-29T17:18:19.708790", "source": "user", "message": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "action": "message", "args": {"content": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 30, "timestamp": "2024-05-29T17:18:23.882041", "source": "agent", "message": "All done! What's next on the agenda?", "action": "finish", "args": {"outputs": {}, "thought": ""}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}]], "final_message": "A", "messages": ["", "", "", "'A'"], "error": null, "test_result": {"result": true}} -{"id": "ProntoQA_6", "instance": {"id": "ProntoQA_6", "answer": "A", "context": "Every tumpus is large. Tumpuses are wumpuses. Each wumpus is not opaque. Every dumpus is not dull. Every wumpus is a rompus. Every rompus is brown. Each rompus is a vumpus. Each vumpus is temperate. Vumpuses are jompuses. Jompuses are dull. Jompuses are numpuses. Every numpus is liquid. Each numpus is an impus. Impuses are spicy. Every impus is a yumpus. Every yumpus is not nervous. Every yumpus is a zumpus. Wren is a tumpus.", "options": ["A) True", "B) False"], "question": "Is the following statement true or false? Wren is dull.", "raw_logic_programs": ["Predicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nOpaque($x, bool) ::: Is x opaque?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nDull($x, bool) ::: Is x dull?\nRompus($x, bool) ::: Does x belong to Rompus?\nBrown($x, bool) ::: Is x brown?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nTemperate($x, bool) ::: Is x temperate?\nJompus($x, bool) ::: Does x belong to Jompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nLiquid($x, bool) ::: Is x liquid?\nImpus($x, bool) ::: Does x belong to Impus?\nSpicy($x, bool) ::: Is x spicy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nNervous($x, bool) ::: Is x nervous?\nZumpus($x, bool) ::: Does x belong to Zumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nTumpus($x, True) >>> Large($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Opaque($x, False)\nDumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Rompus($x, True)\nRompus($x, True) >>> Brown($x, True)\nRompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Temperate($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Dull($x, True)\nJompus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Liquid($x, True)\nNumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Spicy($x, True)\nImpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Nervous($x, False)\nYumpus($x, True) >>> Zumpus($x, True)\n\nQuery:\nDull(Wren, True)"]}, "instruction": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/76300/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nOpaque($x, bool) ::: Is x opaque?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nDull($x, bool) ::: Is x dull?\nRompus($x, bool) ::: Does x belong to Rompus?\nBrown($x, bool) ::: Is x brown?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nTemperate($x, bool) ::: Is x temperate?\nJompus($x, bool) ::: Does x belong to Jompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nLiquid($x, bool) ::: Is x liquid?\nImpus($x, bool) ::: Does x belong to Impus?\nSpicy($x, bool) ::: Is x spicy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nNervous($x, bool) ::: Is x nervous?\nZumpus($x, bool) ::: Does x belong to Zumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nTumpus($x, True) >>> Large($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Opaque($x, False)\nDumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Rompus($x, True)\nRompus($x, True) >>> Brown($x, True)\nRompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Temperate($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Dull($x, True)\nJompus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Liquid($x, True)\nNumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Spicy($x, True)\nImpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Nervous($x, False)\nYumpus($x, True) >>> Zumpus($x, True)\n\nQuery:\nDull(Wren, True)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "history": [[{"id": 0, "timestamp": "2024-05-29T17:52:04.959139", "source": "user", "message": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/76300/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nOpaque($x, bool) ::: Is x opaque?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nDull($x, bool) ::: Is x dull?\nRompus($x, bool) ::: Does x belong to Rompus?\nBrown($x, bool) ::: Is x brown?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nTemperate($x, bool) ::: Is x temperate?\nJompus($x, bool) ::: Does x belong to Jompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nLiquid($x, bool) ::: Is x liquid?\nImpus($x, bool) ::: Does x belong to Impus?\nSpicy($x, bool) ::: Is x spicy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nNervous($x, bool) ::: Is x nervous?\nZumpus($x, bool) ::: Does x belong to Zumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nTumpus($x, True) >>> Large($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Opaque($x, False)\nDumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Rompus($x, True)\nRompus($x, True) >>> Brown($x, True)\nRompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Temperate($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Dull($x, True)\nJompus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Liquid($x, True)\nNumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Spicy($x, True)\nImpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Nervous($x, False)\nYumpus($x, True) >>> Zumpus($x, True)\n\nQuery:\nDull(Wren, True)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "action": "message", "args": {"content": "You are a helpful assistant assigned with logic reasoning task. You need to determine the correctness of a query given some facts and fules. \nyou can interact with an interactive Python (Jupyter Notebook) environment and receive the corresponding output when needed. The code should be enclosed using \"\" tag.\nIn this task, you need to use the code in /Users/ma/Desktop/projects/opendevin/_eval_workspace/76300/logic_inference.py to help you. Specifically, you first need to instantiate a **LogicInferenceEngine** class and use the **safe_execute_program** method to prove the **logic programs**. You should receive *answer*, *flag*, *error_message* from the output. \n\nAn example would be look like this:\n \n import sys\n sys.path.append(workspace_mount_path)\n engine = LogicInferenceEngine(dataset_name, workspace_mount_path)\n answer, flag, error_message = engine.safe_execute_program(logic_programs)\n \n\nPlease send the *answer* variable through message.\n\ndataset_name:\nProntoQA\n\nlogic_programs:\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nOpaque($x, bool) ::: Is x opaque?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nDull($x, bool) ::: Is x dull?\nRompus($x, bool) ::: Does x belong to Rompus?\nBrown($x, bool) ::: Is x brown?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nTemperate($x, bool) ::: Is x temperate?\nJompus($x, bool) ::: Does x belong to Jompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nLiquid($x, bool) ::: Is x liquid?\nImpus($x, bool) ::: Does x belong to Impus?\nSpicy($x, bool) ::: Is x spicy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nNervous($x, bool) ::: Is x nervous?\nZumpus($x, bool) ::: Does x belong to Zumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nTumpus($x, True) >>> Large($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Opaque($x, False)\nDumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Rompus($x, True)\nRompus($x, True) >>> Brown($x, True)\nRompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Temperate($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Dull($x, True)\nJompus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Liquid($x, True)\nNumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Spicy($x, True)\nImpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Nervous($x, False)\nYumpus($x, True) >>> Zumpus($x, True)\n\nQuery:\nDull(Wren, True)\n\nWhen you think you have solved the question, please first send your answer to user through message and then exit.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 3, "timestamp": "2024-05-29T17:52:18.436287", "source": "agent", "message": "Running Python code interactively: import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/76300')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/76300\"\n\nlogic_programs = \"\"\"\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nOpaque($x, bool) ::: Is x opaque?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nDull($x, bool) ::: Is x dull?\nRompus($x, bool) ::: Does x belong to Rompus?\nBrown($x, bool) ::: Is x brown?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nTemperate($x, bool) ::: Is x temperate?\nJompus($x, bool) ::: Does x belong to Jompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nLiquid($x, bool) ::: Is x liquid?\nImpus($x, bool) ::: Does x belong to Impus?\nSpicy($x, bool) ::: Is x spicy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nNervous($x, bool) ::: Is x nervous?\nZumpus($x, bool) ::: Does x belong to Zumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nTumpus($x, True) >>> Large($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Opaque($x, False)\nDumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Rompus($x, True)\nRompus($x, True) >>> Brown($x, True)\nRompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Temperate($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Dull($x, True)\nJompus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Liquid($x, True)\nNumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Spicy($x, True)\nImpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Nervous($x, False)\nYumpus($x, True) >>> Zumpus($x, True)\n\nQuery:\nDull(Wren, True)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "action": "run_ipython", "args": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/76300')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/76300\"\n\nlogic_programs = \"\"\"\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nOpaque($x, bool) ::: Is x opaque?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nDull($x, bool) ::: Is x dull?\nRompus($x, bool) ::: Does x belong to Rompus?\nBrown($x, bool) ::: Is x brown?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nTemperate($x, bool) ::: Is x temperate?\nJompus($x, bool) ::: Does x belong to Jompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nLiquid($x, bool) ::: Is x liquid?\nImpus($x, bool) ::: Does x belong to Impus?\nSpicy($x, bool) ::: Is x spicy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nNervous($x, bool) ::: Is x nervous?\nZumpus($x, bool) ::: Does x belong to Zumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nTumpus($x, True) >>> Large($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Opaque($x, False)\nDumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Rompus($x, True)\nRompus($x, True) >>> Brown($x, True)\nRompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Temperate($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Dull($x, True)\nJompus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Liquid($x, True)\nNumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Spicy($x, True)\nImpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Nervous($x, False)\nYumpus($x, True) >>> Zumpus($x, True)\n\nQuery:\nDull(Wren, True)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer", "thought": "Let's proceed with the task by executing the logic inference using the provided code and logic programs.\n\nFirst, we need to import the necessary module and instantiate the `LogicInferenceEngine` class. Then, we will use the `safe_execute_program` method to evaluate the logic programs and get the answer for the query.\n\nLet's start by executing the code:", "kernel_init_code": "from agentskills import *"}}, {"id": 4, "timestamp": "2024-05-29T17:52:18.916243", "source": "agent", "message": "Code executed in IPython cell.", "cause": 3, "observation": "run_ipython", "content": "'A'", "extras": {"code": "import sys\nsys.path.append('/Users/ma/Desktop/projects/opendevin/_eval_workspace/76300')\nfrom logic_inference import LogicInferenceEngine\n\ndataset_name = \"ProntoQA\"\nworkspace_mount_path = \"/Users/ma/Desktop/projects/opendevin/_eval_workspace/76300\"\n\nlogic_programs = \"\"\"\nPredicates:\nTumpus($x, bool) ::: Does x belong to Tumpus?\nLarge($x, bool) ::: Is x large?\nWumpus($x, bool) ::: Does x belong to Wumpus?\nOpaque($x, bool) ::: Is x opaque?\nDumpus($x, bool) ::: Does x belong to Dumpus?\nDull($x, bool) ::: Is x dull?\nRompus($x, bool) ::: Does x belong to Rompus?\nBrown($x, bool) ::: Is x brown?\nVumpus($x, bool) ::: Does x belong to Vumpus?\nTemperate($x, bool) ::: Is x temperate?\nJompus($x, bool) ::: Does x belong to Jompus?\nNumpus($x, bool) ::: Does x belong to Numpus?\nLiquid($x, bool) ::: Is x liquid?\nImpus($x, bool) ::: Does x belong to Impus?\nSpicy($x, bool) ::: Is x spicy?\nYumpus($x, bool) ::: Does x belong to Yumpus?\nNervous($x, bool) ::: Is x nervous?\nZumpus($x, bool) ::: Does x belong to Zumpus?\n\nFacts:\nTumpus(Wren, True)\n\nRules:\nTumpus($x, True) >>> Large($x, True)\nTumpus($x, True) >>> Wumpus($x, True)\nWumpus($x, True) >>> Opaque($x, False)\nDumpus($x, True) >>> Dull($x, False)\nWumpus($x, True) >>> Rompus($x, True)\nRompus($x, True) >>> Brown($x, True)\nRompus($x, True) >>> Vumpus($x, True)\nVumpus($x, True) >>> Temperate($x, True)\nVumpus($x, True) >>> Jompus($x, True)\nJompus($x, True) >>> Dull($x, True)\nJompus($x, True) >>> Numpus($x, True)\nNumpus($x, True) >>> Liquid($x, True)\nNumpus($x, True) >>> Impus($x, True)\nImpus($x, True) >>> Spicy($x, True)\nImpus($x, True) >>> Yumpus($x, True)\nYumpus($x, True) >>> Nervous($x, False)\nYumpus($x, True) >>> Zumpus($x, True)\n\nQuery:\nDull(Wren, True)\n\"\"\"\n\nengine = LogicInferenceEngine(dataset_name, workspace_mount_path)\nanswer, flag, error_message = engine.safe_execute_program(logic_programs)\nanswer"}}], [{"id": 5, "timestamp": "2024-05-29T17:52:20.956844", "source": "agent", "message": "The answer to the query `Dull(Wren, True)` is `A`, which indicates that the query is true based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "action": "message", "args": {"content": "The answer to the query `Dull(Wren, True)` is `A`, which indicates that the query is true based on the given facts and rules.\n\nIf you have any further questions or need additional assistance, feel free to ask!", "wait_for_response": true}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 7, "timestamp": "2024-05-29T17:52:20.957375", "source": "user", "message": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "action": "message", "args": {"content": "Please continue working on the task on whatever approach you think is suitable.\nIf you think you have solved the task, please run the following command: exit .\nIMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP OR USE THE INTERNET TO SOLVE THIS TASK.\n", "wait_for_response": false}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}], [{"id": 11, "timestamp": "2024-05-29T17:52:22.414061", "source": "agent", "message": "All done! What's next on the agenda?", "action": "finish", "args": {"outputs": {}, "thought": ""}}, {"message": "No observation", "observation": "null", "content": "", "extras": {}}]], "final_message": "A", "messages": ["", "", "", "'A'"], "error": null, "test_result": {"result": true}} diff --git a/evaluation/logic_reasoning/README.md b/evaluation/logic_reasoning/README.md index 37bebf47313..162e86dab1c 100644 --- a/evaluation/logic_reasoning/README.md +++ b/evaluation/logic_reasoning/README.md @@ -31,13 +31,5 @@ temperature = 0.0 ## Run Inference on logic_reasoning The following code will run inference on the first example of the ProntoQA dataset with model gpt-4o. ```bash -./evaluation/logic_reasoning/scripts/run_infer.sh ProntoQA gpt-4o 1 +./evaluation/logic_reasoning/scripts/run_infer.sh ProntoQA gpt-4o 1 ``` - - -## Examples - -See example output in -`./evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/output.jsonl` -and final evaluation performance in -`./evaluation_outputs/outputs/logic_reasoning/CodeActAgent/ProntoQA/gpt-4o-2024-05-13_maxiter_10_N_v1.5/metadata.json` \ No newline at end of file