When working with AI models, crafting the right prompts is key to receiving insightful responses. If you’re looking to create a structured user prompt from a dictionary input in Python, you’ve come to the right place! In this guide, we’ll break down an intriguing Python code sample focusing on how to manipulate dictionaries and formulate user prompts seamlessly. Let’s dive in!

The Code Breakdown

The following Python code demonstrates extracting information from a dictionary called gpt_dict to create a formatted user prompt. Here’s how it works:

gpt_dict = [          
    src: 1,          
    dst: 1,          
    info: 1,        
]

gpt_dict_text_list = []        

for gpt in gpt_dict:            
    src = gpt[src]            
    dst = gpt[dst]            
    info = gpt[info] if info in gpt.keys() else None            
    
    if info:                
        single = f"{src}-{dst} # {info}"            
    else:                
        single = f"{src}-{dst}"            

    gpt_dict_text_list.append(single)        

gpt_dict_raw_text = '\n'.join(gpt_dict_text_list)        

user_prompt = '\n' + gpt_dict_raw_text + '\n' + 'japanese'        

prompt = "im_start_system\n" + "nim_end\n"  # system prompt        
+ "im_start_user\n" + user_prompt + "im_end\n"  # user prompt        
+ "im_start_assistant\n"  # assistant prompt start

Understanding the Process Through Analogy

Think of the gpt_dict as a recipe box filled with different recipes (in this case, pieces of information). Each recipe has ingredients: src, dst, and info, which you can think of as the different components that make up the dish. The code extracts each component from these recipes to create a new dish (or in our case, a user prompt).

• First, it gathers the ingredients from each recipe.
• Then, if an additional ingredient (info) is available, it adds flavor to the dish by including it in the final prompt.
• Finally, all the creations are served in a well-structured format, ready for the AI to consume and provide an output.

Troubleshooting Common Issues

If you encounter issues while implementing the above code, here are some troubleshooting tips:

• Error: NameError
  Ensure that all necessary variables are defined correctly. The src, dst, and info should be properly initialized.
• Issue: Unexpected Output
  Double-check the formats in which you’re joining the strings. Minor syntax errors can lead to significant issues in output formatting.
• Concern: Indentation Error
  Python is sensitive to indentation. Ensure that your loops and conditions are correctly indented.

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Conclusion

In summary, creating a user prompt involves a structured approach to extracting and formatting information from Python dictionaries. This guide not only walks you through the code but also helps you understand it with an engaging analogy. At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.