Building a plugin for ChatGPT allows you to connect it to third-party applications, enhancing its capabilities and making it an even more powerful tool. The following guide will take you through the steps of building a plugin that enables ChatGPT to intelligently call your API.
Although the process of building a ChatGPT plugin that allows intelligent API interaction might seem complex, you’ll find it is a rewarding journey. With this guide, you’re equipped with the knowledge to create a plugin that enhances ChatGPT’s capabilities, enabling it to fetch real-time data, retrieve knowledge-based information, and assist users with various tasks.
How to build ChatGPT plugin
The beauty of OpenAI plugins is that they act as a bridge, connecting ChatGPT to a multitude of applications defined by developers. These plugins empower ChatGPT to perform an array of actions:
- Fetch real-time data, such as sports scores, stock prices, or the latest news.
- Extract knowledge-based information, including company documents and personal notes.
- Aid users with tasks, like booking a flight or ordering food.
Although plugin development is in a beta phase and developer access might not be available to everyone, joining the waitlist could be your gateway to this fascinating world. Throughout the beta, there will be a constant iterative process with users and developers to enhance the plugin system.
A good starting point for understanding plugins is the quickstart repository, which you can follow along as you navigate the documentation.
Plugin developers are tasked with exposing one or more API endpoints, along with a standardized manifest file and an OpenAPI specification. These elements define the plugin’s functionality and provide the means for ChatGPT to consume the files and call the APIs.
With an API spec and a natural language description of when to use the API, the AI model can proactively call the API to perform actions. This is like having an intelligent API caller at your disposal. For example, if a user wants to know the best places to stay in Paris, the model can call a hotel reservation plugin API, receive the API response, and formulate a user-friendly answer combining the API data and its natural language skills.
As time progresses, expect the system to evolve and cater to more advanced use cases.
Plugin Flow
Understanding the end-to-end flow is crucial when building a plugin. Here’s a simplified guide to the process:
1. Creation of Manifest File
You’ll need to create a manifest file and host it at yourdomain.com/.well-known/ai-plugin.json. This file houses metadata about your plugin, including the name, logo, details about required authentication, and an OpenAPI spec for the endpoints you want to expose.
The model will use the OpenAPI description fields, providing a natural language description for the different fields. It’s recommended to initially expose only 1-2 endpoints with a minimum number of parameters to keep the text length manageable. This is because the plugin description, API requests, and API responses are all inserted into the conversation with ChatGPT and count against the model’s context limit.
2. Registration of Your Plugin
Once your manifest file is ready, you can register your plugin in the ChatGPT UI. You’ll need to select the plugin model from the top dropdown, then navigate to “Plugins”, “Plugin Store”, and finally “Develop your own plugin”. If your plugin requires authentication, you’ll need to provide an OAuth 2 client_id and client_secret or an API key.
3. Activation of Your Plugin
Users must manually activate your plugin in the ChatGPT UI; it will not be used by default. You can share your plugin with up to 100 additional users (only other developers can install unverified plugins). If OAuth is required, users will be redirected via OAuth to sign in to your plugin.
4. Initiation of Conversation
Once your plugin is activated, OpenAI will inject a compact description of your plugin into a message to ChatGPT, which will be invisible to end users. This description will include information about the plugin, endpoints, and examples.
Whena user poses a relevant question, the model may choose to invoke an API call from your plugin if it deems it appropriate. For POST requests, a user confirmation flow is required to avoid destructive actions.
The model will then incorporate the API call results into its response to the user. The response may also include links returned from the API calls. These links will be displayed as rich previews, pulling site_name, title, description, image, and URL fields through the OpenGraph protocol.
Furthermore, the model can format data from your API in markdown, and the ChatGPT UI will render the markdown automatically.
Notably, the user’s country and state will be sent in the Plugin conversation header, such as {“openai-subdivision-1-iso-code”: “US-CA”} for a user in California. This is particularly useful for plugins dealing with shopping, restaurants, weather, and more.
Remember, the system is evolving, and over time we anticipate it will accommodate even more advanced use cases. So, don’t hesitate. Embark on this exciting journey of plugin development today and contribute to the growing ecosystem of ChatGPT plugins. For more information on getting started building your very first ChatGPT API jump over to the official OpenAI documentation for further information and guidance.
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