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from openai import OpenAI |
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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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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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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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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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{description} |
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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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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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result = openai_complete_if_cache(model="gpt-4o-mini", prompt=prompt) |
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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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print(f"Queries written to {file_path}") |
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