Build Hour: Apps in ChatGPT

OpenAI Build Hours: Apps in ChatGPT - Detailed Summary

Key Concepts:

ChatGPT Apps: Customizable experiences integrated within ChatGPT, leveraging OpenAI models and external data via MCP servers.
MCP (Model Calling Platform): A framework enabling AI clients to access tools, actions, and resources, connecting to external data and logic.
Codecs: An AI-powered coding assistant that can generate and modify code based on natural language prompts, accelerating app development.
Docs MCP Server: A specialized MCP server pre-loaded with OpenAI documentation, assisting Codecs in understanding and utilizing OpenAI APIs and SDKs.
UI/UX Guidelines: Best practices for designing effective and engaging user interfaces within the ChatGPT app environment.
App Submission Flow: The process for submitting developed apps for review and potential inclusion in the ChatGPT app marketplace.

I. Introduction & Overview (Christine & Corey)

The session began with an introduction to OpenAI Build Hours, a program designed to empower developers with the tools and expertise to scale their companies using OpenAI APIs. The primary focus of this session was ChatGPT Apps, a recently launched platform allowing developers to create custom experiences within ChatGPT. The speakers highlighted resources available – past build hours on demand, upcoming session sign-ups (February 18th: Prompt Caching, February 24th: Agent Capabilities) – accessible via the OpenAI developer homepage. The session structure included an overview of the apps platform, a live demo of existing apps, a walkthrough of the app building process (including Codecs and the Docs MCP server), a live app build (ping pong game), best practices for app development, and a Q&A session.

II. Launch Updates & Platform Components (Corey)

Since the launch at Dev Day, OpenAI has released several key components for app development:

Apps SDK: The core framework for integrating UI widgets and functionality within ChatGPT.
Apps Docs Site (developers.openai.com): Comprehensive documentation for all platform components.
Public App Submission Flow: Allows developers to submit apps for review and potential inclusion in the ChatGPT app marketplace.
App Marketplace: A directory for discovering and installing existing ChatGPT apps.
UI Component Library: Pre-styled UI assets to ensure visual consistency with ChatGPT.
App Sample Repo: Example code repositories for developers to learn from.
Docs MCP Server: A newly launched server providing OpenAI documentation context to Codecs for faster development.

III. Demo of Existing ChatGPT Apps (Corey)

Corey demonstrated several existing apps within ChatGPT:

AllTrails: Allows users to search for hiking trails based on location and criteria (e.g., dog-friendly trails). Demonstrated the app’s ability to refine searches based on user input, pulling data directly from the AllTrails platform.
Adobe Express: Enables users to create visual content (flyers, posters) directly within ChatGPT. Showcased the app’s ability to generate templates and incorporate user-provided text.
Quizzes: A quiz app built by OpenAI, demonstrating dynamic content generation based on structured output. The app dynamically renders quiz questions and answers, requiring no backend storage for content. A quiz on espresso making was initiated, showcasing the interactive learning experience.

These demos highlighted the power of apps to integrate external data and logic, enhancing the ChatGPT experience with specialized functionality.

IV. App Architecture & MCP Explained (Corey)

Corey explained the core architecture of ChatGPT apps, focusing on the MCP (Model Calling Platform). MCP provides capabilities for tools, actions, and resources, enabling AI clients to access external data and perform actions on behalf of the user.

MCP Server: Handles data retrieval, logic execution, and tool calls.
Web Component (Optional): Provides a user interface within ChatGPT, allowing for interactive experiences.
window.openai API: Allows web components to interact with ChatGPT, updating state, receiving tool results, and triggering actions.

The framework is designed to be open, allowing developers to build their own MCP servers and integrate them with ChatGPT.

V. Building an App with Codecs & Docs MCP Server (Corey)

This section demonstrated a live app building process using Codecs and the Docs MCP server. The goal was to create a simple ping pong game within ChatGPT.

Installation: Codecs was installed via npm.
Docs MCP Server Integration: The Docs MCP server URL was added to Codecs, providing it with access to OpenAI documentation.
Agent MD File: An agents.md file was created to instruct Codecs to prioritize the OpenAI developer documentation when building the app.
Code Generation: Codecs was prompted to "create a ChatGPT app with a simple UI and MCP server to play a ping pong game."
Server Setup & Tunneling: The generated MCP server was started locally and tunneled using Enro to create a public URL.
App Integration: The app was added to ChatGPT using the tunneled URL.

This process demonstrated how Codecs and the Docs MCP server can significantly accelerate app development by automating code generation and providing access to relevant documentation.

VI. Live App Demo: Multiplayer Ping Pong (Corey)

Corey showcased a more advanced ping pong app built using the same process, demonstrating:

Real-time Multiplayer: Two users (Corey and Christine) played ping pong simultaneously within ChatGPT.
Score Tracking: The app tracked scores and displayed game statistics.
Post-Game Analysis: The app utilized the ChatGPT model to provide personalized feedback and tips based on game performance.

This demo highlighted the potential for creating engaging and interactive experiences within ChatGPT.

VII. Best Practices & Resources (Christine)

Christine outlined best practices for building successful ChatGPT apps:

Focus on User Value: Apps should solve a user problem or provide a unique utility.
Leverage ChatGPT’s Strengths: Utilize the model’s conversational abilities, multi-turn dialogue, and context awareness.
UI/UX Guidelines: Follow OpenAI’s UI/UX guidelines to ensure a consistent and engaging user experience.
Utilize UI Component Library: Leverage pre-styled components to accelerate development.
Monetization: Explore options like authentication flows and external checkouts.

Resources shared included:

Apps SDK Documentation: Comprehensive documentation for the apps SDK.
UI Component Library: Pre-styled UI assets.
App Sample Repo: Example code repositories.
GitHub Examples (Kitchen Sync): A simple example app demonstrating key concepts.
Blog Post: "What Makes a Great ChatGPT App?" (by Corey)

VIII. Q&A (Christine & Corey)

The session concluded with a Q&A session addressing questions about:

MCP Compatibility with OpenAI APIs: MCP is compatible with OpenAI APIs and SDKs.
Local Development Tooling: Enro and Cloudflare are recommended for tunneling local servers.
UI Customization: Developers have significant freedom to customize the UI, within OpenAI’s guidelines.
Adobe Express Account Requirement: An Adobe account is required to use the Adobe Express app.
App Category Priorities: OpenAI is open to various app categories and will evolve its marketplace over time.

Conclusion:

This Build Hour provided a comprehensive overview of ChatGPT Apps, demonstrating the platform’s potential for creating innovative and engaging experiences. The session emphasized the importance of leveraging OpenAI’s tools (Codecs, Docs MCP server) and following best practices to build successful apps. The live demo of the multiplayer ping pong game showcased the power of combining AI, external data, and interactive UI elements within the ChatGPT environment. The resources provided will empower developers to begin building their own ChatGPT apps and contribute to the growing ecosystem.