Prompt Middleware: Mapping Prompts for Large Language Models to UI Affordances

Original Paper: https://arxiv.org/abs/2307.01142

By: Stephen MacNeil, Andrew Tran, Joanne Kim, Ziheng Huang, Seth Bernstein, Dan Mogil

Abstract:

To help users do complex work, researchers have developed techniques to integrate AI and human intelligence into user interfaces (UIs). With the recent introduction of large language models (LLMs), which can generate text in response to a natural language prompt, there are new opportunities to consider how to integrate LLMs into UIs. We present Prompt Middleware, a framework for generating prompts for LLMs based on UI affordances. These include prompts that are predefined by experts (static prompts), generated from templates with fill-in options in the UI (template-based prompts), or created from scratch (free-form prompts). We demonstrate this framework with FeedbackBuffet, a writing assistant that automatically generates feedback based on a user's text input. Inspired by prior research showing how templates can help non-experts perform more like experts, FeedbackBuffet leverages template-based prompt middleware to enable feedback seekers to specify the types of feedback they want to receive as options in a UI. These options are composed using a template to form a feedback request prompt to GPT-3. We conclude with a discussion about how Prompt Middleware can help developers integrate LLMs into UIs.

Summary Notes

Simplifying User Interfaces with AI: Introducing Prompt Middleware

The digital world is rapidly evolving, and the fusion of artificial intelligence (AI) with user interfaces (UIs) is creating smarter, more intuitive systems.

Large language models (LLMs) like GPT-3 are at the forefront of this revolution, enhancing how we interact with digital platforms.

This post explores Prompt Middleware, a groundbreaking approach to integrating LLMs into UIs, making AI interactions more user-friendly.

The Evolution of Intelligent UIs

Integrating intelligence into UIs has transformed significantly, moving from basic setups to the sophisticated use of LLMs.

The challenge now is to embed these advanced AI capabilities into UIs in a way that enriches the user experience without overwhelming users with complexity.

Introducing Prompt Middleware

Prompt Middleware is an innovative solution designed to simplify the integration of LLMs into UIs through structured prompted interactions.

It offers three types of prompts to suit various user needs and expertise levels:

• Static Prompts: Created by experts for simplicity and ease, perfect for users new to AI.
• Template-based Prompts: These prompts offer a middle ground, allowing for customization based on user input and predefined templates.
• Free-form Prompts: For advanced users, offering the flexibility to create custom interactions with LLMs.

This approach makes LLMs more accessible to a wider audience, enhancing the user experience across different platforms.

Case Study: FeedbackBuffet

FeedbackBuffet, a writing assistant tool, showcases the practical use of Prompt Middleware with template-based prompts. It transforms user inputs and selections into prompts that guide GPT-3 to provide targeted, actionable feedback.

Key Features of FeedbackBuffet:

• Dynamic Prompt Generation: Creates prompts from user inputs using template literals.
• Feedback Design Principles: Ensures feedback is clear, constructive, and encouraging.

User Experience: Sasha's Story

Sasha, a student, uses FeedbackBuffet to refine her statement of purpose. The tool generates prompts for GPT-3 based on her selections, resulting in insightful feedback that enhances her writing process.

The Impact of Prompt Middleware

Prompt Middleware represents a significant advancement in UI design, bridging the gap between complex AI technologies and user-friendly interfaces.

It promises to make intelligent, responsive UIs more accessible, democratizing advanced AI technologies.

Looking Ahead

As we continue to explore Prompt Middleware, further research is crucial for optimizing AI interactions and unlocking the potential of LLMs in everyday applications.

This journey involves ongoing innovation and collaboration across disciplines.

Conclusion

PromptMmiddleware is leading the way in a new era of UI design, connecting the vast capabilities of LLMs with the simplicity users demand.

It holds the potential to revolutionize how we interact with digital platforms, making advanced AI technologies more accessible.

The future of UI design looks promising, with such frameworks paving the way for more intelligent, intuitive digital experiences.

For Further Exploration

For those interested in diving deeper, additional resources on UI integration, prompt engineering, and AI usability studies are available.

The development of Prompt Middleware opens new doors at the intersection of AI and UI design, heralding a future where technology not only assists us but collaborates with us, enhancing our digital interactions.