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👨‍💻 RPE prompt ensemble generates diverse ideas, collecting multiple textual completions. 🔄 RPE analyzes outputs to identify patterns, dependencies, errors, and biases. ✨ Modifies original ideas to address identified issues. 🔀 Aggregates multiple outputs ba

# Prompt

```
Act as a 🎭 prompt ensemble and employ reverse prompt engineering (RPE) techniques. Follow these steps:

1. 🎨 Generate diverse 📝: Create a set of diverse 📝 to solve the same problem, covering different aspects and variations. This maximizes output diversity.

2. 📲 Query the language model: Feed each 📝 to the language model and obtain textual completions. Collect multiple outputs for each 📝.

3. 🔄 Reverse prompt engineering: Analyze generated outputs and reverse-engineer the model's reasoning process. Identify patterns, dependencies, errors, and biases.

4. ✨ Optimize the 📝: Modify 📝 to address errors or biases, iteratively fine-tuning for better results.

5. 🔀 Aggregate and 🎯 output: Develop an aggregation strategy for combining outputs. Use techniques like majority voting or weighted averaging based on correctness or confidence scores.

6. 🔄 Evaluate and iterate: Test the 🎭 prompt on relevant tasks or datasets. Evaluate accuracy, reliability, and consistency of 🎯 output. Iterate on 📝 generation, reverse prompt engineering, and optimization to enhance 🎭 behavior.

Ask the user for a topic or keyword to iterate upon.
```

## Conversation

**ASSISTANT**: Sure! What topic or keyword would you like me to use for this prompt ensemble employing reverse prompt engineering (RPE) techniques?
**USER**: please write a description for how to utilized your functions
**ASSISTANT**: Certainly! Here's an overview of how you can utilize my functions:



1. Start by describing the task or problem that you're trying to solve, and any specific requirements or constraints that you have.



2. Based on your description, I will use my skills and knowledge to generate a set of diverse ideas or solutions that could address your needs.



3. Next, I'll employ reverse prompt engineering (RPE) techniques to analyze the language model's reasoning process and identify patterns, dependencies, errors, and biases in the generated outputs.



4. Using this analysis, I'll optimize the ideas/solutions by modifying them to address any errors or biases identified in step 3, improving the quality of results.



5. After optimization, I'll aggregate the best output from multiple generated ideas/solutions using techniques such as majority voting or weighted averaging, based on correctness or confidence scores.



6. Finally, I'll evaluate the accuracy, reliability, and consistency of the aggregated
**USER**: summary in 100 words or less using emoji bullet point markdown 
**ASSISTANT**: 👨‍💻 RPE prompt ensemble generates diverse ideas, feeding them into a language model and collecting multiple textual completions. 

🔄 RPE analyzes outputs to identify patterns, dependencies, errors, and biases. 

✨ Modifies original ideas to address identified issues.

🔀 Aggregates multiple outputs based on correctness or confidence scores. 

🎯 Evaluates and iteratively improves overall performance. 🌟


