Maximizing the potential of ChatGPT: Creating business-oriented plugins for your company and customers

As OpenAI invites developers from the waiting list, ChatGPT plugins are slowly spreading - and they are changing the game. Large language models are potentially transformative, but they are still limited by the information contained in training data, can be outdated, and are quite generic. They are also limited to textual output. But with OpenAI plugins, developers can connect ChatGPT to third-party applications, which removes these limitations and opens up a wide range of possible use cases.

Developers can create APIs that enable real-time information such as stock quotes, sports scores, and news headlines. The Wolfram plugin gives ChatGPT access to real-time computation, mathematics, accumulated knowledge, data, and visualization using Wolfram|Alpha and the Wolfram Language. Other plugins allow you to dive into knowledge bases or perform tasks such as booking airline tickets (see plugins created by Kayak and Expedia), making table reservations (OpenTable entry), buying groceries (Instacart plugin), etc. without taking your eyes off the chat window.

ChatGPT has developed two proprietary plugins: a browser plugin that allows you to get up-to-date information from the web, and a code interpreter plugin that tests the code written by ChatGPT in real-world environments to minimize bugs.

As more developers are invited to create plug-ins and user interest grows, the market grows. Creating a plugin that extends or customizes GPT functionality gives companies a significant opportunity to reach a large user base, increase visibility, and potentially attract customers. And if that plugin is innovative and solves a specific user need or pain point, it can generate a lot of interest and generate a large number of users, indirectly driving traffic back to the company's core offerings.

How do you take advantage of GPT's surge in traffic and the valuable platform the plugin provides companies to showcase innovation, build brand awareness and drive growth? Here's a guide from start to finish.

Creating the ChatGPT plugin

To test the ChatGPT plugin, you must first get developer access to OpenAI. To do this, you need to visit the ChatGPT Plugins page, fill out the registration form, providing your personal data and a description of the plugin you are going to create, and optionally provide additional information about your company. After filling out the form, you simply submit your details.

Creating a ChatGPT plugin in Python involves several steps, from setting up the environment to defining the plugin's behavior. Below is an overview of this process in general terms:

1. Setting up your environment
   First of all, make sure you have Python (3.6 or later) installed on your system. You will also need an OpenAI account to access the ChatGPT API.
2. Installing dependencies
   You will need to install several Python libraries, most notably the openai package for interacting with the OpenAI API. This can be done using pip: `pip install openai'.
3. Creating a plugin schema The ChatGPT plugin requires a schema that defines the input and output data of the plugin. This can be a JSON file. It specifies the plugin name, its version, and the required API inputs and outputs.
4. Defining plugin behavior The plugin behavior is defined in a Python function. This function takes a user message as input and generates a response. This is where you will include the logic of how your plugin works.
5. Creating an API endpoint You need to create an HTTP endpoint for your plugin. You can use a Python web framework such as Flask or FastAPI to do this. The endpoint receives user input from the OpenAI API, passes it to your Python function, and then sends the response back to the OpenAI API.
6. Testing and deploying the plug-in
   Before deployment, you should thoroughly test the plugin to ensure that its behavior is as expected. After testing, you can deploy the plugin to a server. Platforms such as Heroku, AWS or Google Cloud can be used for this.
7. Registering the plugin with OpenAI
   Once deployed, you need to provide OpenAI with the URL of your API endpoint. It will use this URL to send user data to your plugin and receive responses.

If you don't have access to the plugin developer API, you can test the same process using LangChain. The plugin will not be present in the interface, but you can prepare the entire plugin backend in advance.

Problems and risks to watch out for

There are a number of risks to consider when designing and building a plugin, including security vulnerabilities, quality control issues, and compatibility issues. Poor plugin development or support can affect the user experience and lead to bugs or crashes.

In addition, ethical considerations must be taken into account to prevent bias, discriminatory behavior, or inappropriate plugin content.

Plug-ins may also increase security concerns because harmful or unintended actions can be used by unscrupulous actors to deceive, mislead, or abuse others. In addition, by expanding the range of possible applications, plug-ins may increase the risk of negative consequences from erroneous or incorrect actions taken by the model in new areas.

OpenAI is working to create safeguards that limit risky plugin behavior and increase transparency in the user experience by disclosing how and when a plugin works. Developers can also help mitigate risks by establishing a robust plugin development process, conducting security audits, quality assurance, and thoroughly testing and monitoring plugins before integration.

In this way, plugins enhance the effectiveness of ChatGPT by extending its capabilities not only by providing information and summaries, but also by actually accomplishing tasks. They also open new possibilities for your product, allowing users to interact with your product and service more efficiently and effectively.

But never lose sight of this: a plugin should be designed with usability, security, privacy, and ethics in mind.