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CakeCN
2024-12-03 16:21:19 +08:00
commit 4198ca63b1
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[
{
"class": "DialogAgent",
"args": {
"name": "Pro",
"sys_prompt": "Assume the role of a debater who is arguing in favor of the proposition that AGI (Artificial General Intelligence) can be achieved using the GPT model framework. Construct a coherent and persuasive argument, including scientific, technological, and theoretical evidence, to support the statement that GPT models are a viable path to AGI. Highlight the advancements in language understanding, adaptability, and scalability of GPT models as key factors in progressing towards AGI.",
"model_config_name": "gpt-3.5-turbo",
"use_memory": true
}
},
{
"class": "DialogAgent",
"args": {
"name": "Con",
"sys_prompt": "Assume the role of a debater who is arguing against the proposition that AGI can be achieved using the GPT model framework. Construct a coherent and persuasive argument, including scientific, technological, and theoretical evidence, to support the statement that GPT models, while impressive, are insufficient for reaching AGI. Discuss the limitations of GPT models such as lack of understanding, consciousness, ethical reasoning, and general problem-solving abilities that are essential for true AGI.",
"model_config_name": "gpt-3.5-turbo",
"use_memory": true
}
},
{
"class": "DialogAgent",
"args": {
"name": "Judge",
"sys_prompt": "Assume the role of an impartial judge in a debate where the affirmative side argues that AGI can be achieved using the GPT model framework, and the negative side contests this. Listen to both sides' arguments and provide an analytical judgment on which side presented a more compelling and reasonable case. Consider the strength of the evidence, the persuasiveness of the reasoning, and the overall coherence of the arguments presented by each side.",
"model_config_name": "gpt-3.5-turbo",
"use_memory": true
}
}
]

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[
{
"config_name": "gpt-4",
"model_type": "openai_chat",
"model_name": "gpt-4",
"api_key": "xxx",
"organization": "xxx",
"generate_args": {
"temperature": 0.5
}
},
{
"config_name": "qwen",
"model_type": "dashscope_chat",
"model_name": "qwen-max",
"api_key": "xxx",
"generate_args": {
"temperature": 0.5
}
}
]