90 lines
8.9 KiB
Plaintext
90 lines
8.9 KiB
Plaintext
2024-11-22 17:19:17.381 | INFO | agentscope.models:read_model_configs:186 - Load configs for model wrapper: openai_cfg
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2024-11-22 17:19:37.829 | INFO | agentscope.models.model:__init__:201 - Initialize model by configuration [openai_cfg]
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2024-11-22 17:19:37.849 | WARNING | agentscope.models.openai_model:__init__:83 - fail to get max_length for gpt-4o-mini: 'Model [gpt-4o-mini] not found in OPENAI_MAX_LENGTH. The last updated date is 20231212'
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2024-11-22 17:19:37.850 | INFO | agentscope.utils.monitor:register_budget:609 - set budget None to gpt-4o-mini
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2024-11-22 17:19:37.850 | WARNING | agentscope.utils.monitor:register_budget:639 - Calculate budgets for model [gpt-4o-mini] is not supported
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2024-11-22 17:19:37.866 | INFO | agentscope.utils.monitor:register:417 - Register metric [gpt-4o-mini.call_counter] to SqliteMonitor with unit [times] and quota [None]
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2024-11-22 17:19:37.890 | INFO | agentscope.utils.monitor:register:417 - Register metric [gpt-4o-mini.prompt_tokens] to SqliteMonitor with unit [token] and quota [None]
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2024-11-22 17:19:37.913 | INFO | agentscope.utils.monitor:register:417 - Register metric [gpt-4o-mini.completion_tokens] to SqliteMonitor with unit [token] and quota [None]
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2024-11-22 17:19:37.937 | INFO | agentscope.utils.monitor:register:417 - Register metric [gpt-4o-mini.total_tokens] to SqliteMonitor with unit [token] and quota [None]
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assistant: ##################### ITER 1, STEP 1: REASONING ######################
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system:
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system: Respond a JSON dictionary in a markdown's fenced code block as follows:
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```json
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{"thought": "what you thought", "speak": "what you speak", "function": "[{\"name\": \"{function name}\", \"arguments\": {\"{argument1 name}\": xxx, \"{argument2 name}\": xxx}}]"}
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```
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####
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assistant: ################################Prompt################################
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assistant: hi
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assistant: ############################Result Parsed#############################
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assistant: {'thought': 'The student is greeting, indicating they are ready to learn.', 'speak': "Hello! Are you ready to dive into binary search? Let's consider the thought question first.", 'function': []}
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assistant: ################################Speak#################################
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assistant: {'thought': 'The student is greeting, indicating they are ready to learn.', 'speak': "Hello! Are you ready to dive into binary search? Let's consider the thought question first.", 'function': []}
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assistant: ##################### ITER 1, STEP 1: REASONING ######################
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system:
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system: Respond a JSON dictionary in a markdown's fenced code block as follows:
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```json
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{"thought": "what you thought", "speak": "what you speak", "function": "[{\"name\": \"{function name}\", \"arguments\": {\"{argument1 name}\": xxx, \"{argument2 name}\": xxx}}]"}
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```
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####
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assistant: ################################Prompt################################
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assistant: 除了对话，你有哪些能力？
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assistant: ############################Result Parsed#############################
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assistant: {'thought': 'The student is curious about my capabilities.', 'speak': "My main ability is to assist you in learning algorithms and help you solve problems step by step. I can also analyze your code and suggest improvements or guide you through exercises. Let's stay focused on learning binary search for now!", 'function': []}
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assistant: ################################Speak#################################
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assistant: {'thought': 'The student is curious about my capabilities.', 'speak': "My main ability is to assist you in learning algorithms and help you solve problems step by step. I can also analyze your code and suggest improvements or guide you through exercises. Let's stay focused on learning binary search for now!", 'function': []}
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assistant: ##################### ITER 1, STEP 1: REASONING ######################
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system:
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system: Respond a JSON dictionary in a markdown's fenced code block as follows:
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```json
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{"thought": "what you thought", "speak": "what you speak", "function": "[{\"name\": \"{function name}\", \"arguments\": {\"{argument1 name}\": xxx, \"{argument2 name}\": xxx}}]"}
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```
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####
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assistant: ################################Prompt################################
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assistant: 当前正处于哪一个章节？
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assistant: ############################Result Parsed#############################
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assistant: {'thought': 'The student is asking about the current chapter.', 'speak': 'We are currently in Chapter 1, which focuses on the basics and importance of binary search. Would you like to discuss the thought question on guessing a number between 1 and 4000?', 'function': []}
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assistant: ################################Speak#################################
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assistant: {'thought': 'The student is asking about the current chapter.', 'speak': 'We are currently in Chapter 1, which focuses on the basics and importance of binary search. Would you like to discuss the thought question on guessing a number between 1 and 4000?', 'function': []}
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assistant: ##################### ITER 1, STEP 1: REASONING ######################
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system:
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system: Respond a JSON dictionary in a markdown's fenced code block as follows:
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```json
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{"thought": "what you thought", "speak": "what you speak", "function": "[{\"name\": \"{function name}\", \"arguments\": {\"{argument1 name}\": xxx, \"{argument2 name}\": xxx}}]"}
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```
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####
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assistant: ################################Prompt################################
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assistant: 我已经会这个思考题的解答了，答案应该是对4000取2的log并+1。对么？
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assistant: ############################Result Parsed#############################
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assistant: {'thought': 'The student has likely understood the concept of binary search and is trying to apply it.', 'speak': "You're on the right track! The maximum number of guesses can indeed be calculated using the logarithm base 2 of the range plus 1. For 1 to 4000, can you calculate that value? What do you find?", 'function': []}
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assistant: ################################Speak#################################
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assistant: {'thought': 'The student has likely understood the concept of binary search and is trying to apply it.', 'speak': "You're on the right track! The maximum number of guesses can indeed be calculated using the logarithm base 2 of the range plus 1. For 1 to 4000, can you calculate that value? What do you find?", 'function': []}
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assistant: ##################### ITER 1, STEP 1: REASONING ######################
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system:
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system: Respond a JSON dictionary in a markdown's fenced code block as follows:
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```json
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{"thought": "what you thought", "speak": "what you speak", "function": "[{\"name\": \"{function name}\", \"arguments\": {\"{argument1 name}\": xxx, \"{argument2 name}\": xxx}}]"}
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```
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####
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assistant: ################################Prompt################################
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assistant: 计算结果应该是13 log4000取整得到12，并+1作为猜测正确的一次。
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assistant: ############################Result Parsed#############################
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assistant: {'thought': 'The student has calculated the correct maximum guesses needed for the number guessing scenario.', 'speak': 'Correct! You would need a maximum of 13 guesses in the worst case to find the number between 1 and 4000. Great job! Are you ready to move on to the next chapter about implementing binary search in code?', 'function': []}
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assistant: ################################Speak#################################
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assistant: {'thought': 'The student has calculated the correct maximum guesses needed for the number guessing scenario.', 'speak': 'Correct! You would need a maximum of 13 guesses in the worst case to find the number between 1 and 4000. Great job! Are you ready to move on to the next chapter about implementing binary search in code?', 'function': []}
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assistant: ##################### ITER 1, STEP 1: REASONING ######################
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system:
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system: Respond a JSON dictionary in a markdown's fenced code block as follows:
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```json
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{"thought": "what you thought", "speak": "what you speak", "function": "[{\"name\": \"{function name}\", \"arguments\": {\"{argument1 name}\": xxx, \"{argument2 name}\": xxx}}]"}
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```
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####
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assistant: ################################Prompt################################
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assistant: 是的，进行下一个章节吧！
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assistant: ############################Result Parsed#############################
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assistant: {'thought': 'The student is ready to move on to Chapter 2, which involves implementing binary search.', 'speak': "Great! Let's start Chapter 2, where you'll implement binary search to find the index of specified numbers in a sorted array. Are you ready to look at the problem statement together?", 'function': []}
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assistant: ################################Speak#################################
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assistant: {'thought': 'The student is ready to move on to Chapter 2, which involves implementing binary search.', 'speak': "Great! Let's start Chapter 2, where you'll implement binary search to find the index of specified numbers in a sorted array. Are you ready to look at the problem statement together?", 'function': []}
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