The More I Learn, the Less I Know
Each morning I wake up and have a multitude of paths I could take on that day. Depending on who, or what part of me, you ask, various paths and destinations might be more critical in my journey than others. My affinity for a “critical” task is inversely proportional to my procrastination and the likelihood of finding frustration on the project. While creative writing is my constant, currently my affinity lies in exploring Multi-Agent frameworks and automated workflows.
All paths lead to the future, some are just more scenic than the others.
I am amazed by the wild inconsistencies in functional quality when it comes to ChatGPT. When I asked it to help me lay out an automatic multi-agent GPT prompt generator, I was pretty pleased with the results as a place to start my development. See C^Guote below.
“ ChatGPT
To create prompts for each agent within the Evolutionary Algorithm-Based Framework for use in AutoGen Studio, it's crucial to incorporate the defined KPIs directly into the prompts to ensure consistency and alignment with the objectives. Here's how the prompts can be structured for each agent:
1. Initialization Agent
Prompt: "Generate a diverse set of initial prompts based on the user's description: '[User Description]'. Aim for a high diversity score by producing a wide range of unique prompts. Evaluate the initial performance score of each generated prompt based on relevancy and coherence, setting a benchmark for subsequent optimization."
KPIs Embedded:
Diversity of Prompts
Initial Performance Score
2. Evaluation Agent
Prompt: "Assess the effectiveness of the following set of prompts: '[List of Prompts]'. Evaluate each prompt for relevancy, coherence, and potential user engagement. Ensure accuracy and consistency in your evaluations, aligning them with real-world feedback metrics where possible."
KPIs Embedded:
Accuracy of Evaluation
Consistency
3. Evolution Agent
Prompt: "Evolve the provided set of prompts to enhance their performance based on the following KPIs: relevancy, coherence, and user engagement. Use genetic algorithms to select, crossover, and mutate the best-performing prompts, aiming to increase the improvement rate and reduce the convergence time."
KPIs Embedded:
Improvement Rate
Convergence Time
4. Optimization Agent
Prompt: "Optimize the following set of prompts: '[List of Prompts]'. Apply reinforcement learning to iteratively refine each prompt, with the goal of maximizing the optimization success rate and the cumulative reward. Focus on significant improvements in relevancy, coherence, and user engagement."
KPIs Embedded:
Optimization Success Rate
Reward Maximization
In these prompts, the KPIs are directly tied to the tasks each agent is responsible for, ensuring that the evaluation of their performance is consistent and aligned with the overarching goals of the framework. Additionally, the prompts are structured to guide each agent toward specific actions and outcomes, facilitating a cohesive and targeted approach to prompt optimization within the AutoGen Studio environment.”
Then I asked GPT4 (Using DALL-E) to generate a flowchart of the process it had described in the conversation, and I received typical cartoon nonsense, instead of a useful diagram.
Which way did he go, Doc?
