Exploring ChatGPT (GPT) Wrappers – What They Are and How They Work

With the rise of user-friendly and versatile AI models like ChatGPT, Google Bard, and Anthropic Claude, many businesses have started creating applications entirely dependent on these tools. These applications, often referred to as GPT Wrappers, provide a layer of functionality on top of large language models (LLMs). ChatGPT Wrappers, in particular, are among the most common due to the widespread adoption of OpenAI's ChatGPT.

What is a GPT Wrapper?

A GPT Wrapper is an application or tool that provides additional functionality, often in the form of a user interface (UI) or user experience (UX), layered on top of API calls to a generative AI (GenAI). These wrappers serve as a bridge between users and the underlying GenAI, enhancing accessibility and usability.

GPT Wrappers simplify the process of interacting with a generative AI by:

• Abstraction: Wrapping complex GenAI operations into easy-to-use tools.
• Personalization: Customizing prompts or outputs for specific tasks or industries.
• Enhanced Usability: Providing user-friendly interfaces to streamline interactions with GenAI.

Essentially, GPT Wrappers enable businesses and developers to package AI capabilities into standalone applications, transforming generic GenAI APIs into tailored, marketable solutions.

GPT Wrapper Meaning

When we talk about GPT Wrappers, we refer to applications or tools that rely on GPT-based models (like GPT-4) to perform tasks. Wrappers can vary in complexity, from simple tools that generate text based on predefined templates to more advanced systems integrating external functionalities like data analysis or API calls.

Key Characteristics of GPT Wrappers

• Dependent on GenAI: They rely entirely or predominantly on API calls to GPT-based models.
• Purpose-Specific: Designed for specific use cases, such as writing, storytelling, coding assistance, or customer support.
• Thin Layer: Often add minimal additional functionality beyond the GenAI capabilities.

Comparisons of Wrapper Types

Not all GPT Wrappers are created equal. Here’s a comparison of different types:

Wrapper Type	Example Applications	Features
Simple Wrappers	Adventure story generators, resume creators	Basic UI for text generation
Interactive Wrappers	Chatbots for customer service	Includes dynamic input/output handling
Tool-Enhanced Wrappers	Code assistance tools like GitHub Copilot	Integrates additional tools or APIs
Autonomous Wrappers	Workflow automation systems	Combines GenAI with logic and workflows

Examples of GPT Wrappers in Action

Simple GPT Wrapper

Consider a website which allows you to put in a description of yourself then creates a story about you going on an adventure. Behind the scenes, this application is just a prompt template which combines with your user input to produce a prompt. This prompt is then sent to a GenAI to create the story.

Interactive GPT Wrapper

A chatbot for customer service, which:

• Handles inquiries dynamically.
• Integrates business-specific FAQs into its responses.

Tool-Enhanced GPT Wrapper

Applications like GitHub Copilot combine GPT models with other systems to assist with coding tasks, offering autocomplete functionality and debugging support.

What Are the Pros and Cons of GPT Wrappers?

Creating GPT Wrappers offers both opportunities and challenges for developers and businesses.

Advantages

• Quick to Build: Wrappers can be developed rapidly using existing GenAI APIs.
• Cost-Effective Startup: Low initial investment required for development.
• Customizable: Flexible in adapting GenAI capabilities to specific user needs.

Disadvantages

• Lack of Competitive Edge: Easy to replicate, making it hard to establish a unique market position.
• Scaling Costs: High traffic can lead to significant API call expenses.
• Vulnerable to Prompt Leaking: Susceptible to attacks like prompt leaking and prompt injection.
• Dependency on Providers: Functionality and availability depend on the GenAI provider.

Pros	Cons
Quick to build	Shallow market moat
Low startup costs	High scaling expenses
Customizable applications	Prone to prompt-based vulnerabilities
	Dependence on changes by GenAI providers

Are GPT Wrappers Still Relevant?

GPT Wrappers remain a key entry point for developers and businesses looking to capitalize on generative AI. However, their long-term viability is subject to:

1. Competition from GenAI Providers: As providers like OpenAI integrate more functionality directly into their platforms (e.g., function calling, browsing), the need for standalone wrappers decreases.
2. Niche Applications: Wrappers that address unique use cases or integrate specialized tools continue to hold value.

While we expect the number of GPT Wrappers to decline in favor of more robust solutions, they still have a role in industries that require tailored AI solutions.

Final Thoughts

GPT Wrappers are a powerful way to bring generative AI to end users, offering unique functionality with minimal development effort. Whether you’re building a simple ChatGPT Wrapper or a tool-enhanced application, understanding the benefits and limitations is crucial for success.

By focusing on innovative and niche applications, developers can create wrappers that stand out, even in a crowded market.

Happy building!

Sander Schulhoff

Sander Schulhoff is the Founder of Learn Prompting and an ML Researcher at the University of Maryland. He created the first open-source Prompt Engineering guide, reaching 3M+ people and teaching them to use tools like ChatGPT. Sander also led a team behind Prompt Report, the most comprehensive study of prompting ever done, co-authored with researchers from the University of Maryland, OpenAI, Microsoft, Google, Princeton, Stanford, and other leading institutions. This 76-page survey analyzed 1,500+ academic papers and covered 200+ prompting techniques.