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			56 lines
		
	
	
		
			1.6 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			56 lines
		
	
	
		
			1.6 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from openai import OpenAI
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| 
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| # os.environ["OPENAI_API_KEY"] = ""
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| 
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| 
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| def openai_complete_if_cache(
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|     model="gpt-4o-mini", prompt=None, system_prompt=None, history_messages=[], **kwargs
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| ) -> str:
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|     openai_client = OpenAI()
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| 
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|     messages = []
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|     if system_prompt:
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|         messages.append({"role": "system", "content": system_prompt})
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|     messages.extend(history_messages)
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|     messages.append({"role": "user", "content": prompt})
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| 
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|     response = openai_client.chat.completions.create(
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|         model=model, messages=messages, **kwargs
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|     )
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|     return response.choices[0].message.content
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| 
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| 
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| if __name__ == "__main__":
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|     description = ""
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|     prompt = f"""
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|     Given the following description of a dataset:
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| 
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|     {description}
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| 
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|     Please identify 5 potential users who would engage with this dataset. For each user, list 5 tasks they would perform with this dataset. Then, for each (user, task) combination, generate 5 questions that require a high-level understanding of the entire dataset.
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| 
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|     Output the results in the following structure:
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|     - User 1: [user description]
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|         - Task 1: [task description]
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|             - Question 1:
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|             - Question 2:
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|             - Question 3:
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|             - Question 4:
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|             - Question 5:
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|         - Task 2: [task description]
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|             ...
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|         - Task 5: [task description]
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|     - User 2: [user description]
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|         ...
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|     - User 5: [user description]
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|         ...
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|     """
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| 
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|     result = openai_complete_if_cache(model="gpt-4o-mini", prompt=prompt)
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| 
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|     file_path = "./queries.txt"
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|     with open(file_path, "w") as file:
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|         file.write(result)
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| 
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|     print(f"Queries written to {file_path}")
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