Connect to the Real ChatGPT and even GPT4!

Table of Contents

1. Introduction
2. Building a Custom Connector for Chat GPT Endpoint
3. Setting Up the Custom Connector
4. Testing the Chat GPT Endpoint
5. Using the Chat GPT Endpoint in an App
6. Using the GPT3 Turbo Model
7. Using the GPT4 Model (Preview Only)
8. Customizing System Messages
9. Conclusion
10. FAQs

Building a Custom Connector for Chat GPT Endpoint

In this article, we will guide You through the process of building a custom connector for the Chat GPT endpoint in the Independent Publisher Connector for OpenAI. Building your own custom connector allows you to use the Chat GPT 3.5 Turbo model or the GPT4 model if you have access to it through the preview feature. We will walk you through the steps of setting up the custom connector, testing it, and using it in an app. Let's get started!

Introduction

The Chat GPT endpoint in the Independent Publisher Connector for OpenAI allows users to generate dynamic and interactive chat responses using AI models. However, since there is currently no Jet GPT endpoint available, we will Show you how to Create a custom connector to access the Chat GPT endpoint. Through this custom connector, you can leverage the power of the Chat GPT 3.5 Turbo model or the GPT4 model.

Setting Up the Custom Connector

To start, head over to the custom connectors section in the Independent Publisher Connector for OpenAI. If you don't find it immediately, you can click on "More" and then "Discover All" to locate it. Create a new custom connector by selecting "Create from a Blank" and name it "Chat GPT".

Next, we need to define the connector's base URL. Refer to the API documentation for the appropriate URL. In this case, we will be using the chat completion API.

Ensure that the authorization property is set in the header of the connector. Copy the authorization value from the API documentation and paste it in the appropriate field in the custom connector settings.

Define the actions for the connector, such as the chat completion operation. Use a sample request and response from the API documentation to set up the request and response for the action. Import the sample request and response using the options provided.

Once you have imported the necessary details and defined the actions, you can create the custom connector.

Testing the Chat GPT Endpoint

To test the custom connector, you need to provide your API key. This can be done by configuring the connection settings. Once the API key is set, you can test the connection to ensure its functionality.

Perform a test operation using the example request and verify that you receive a successful 200 response. This confirms that the custom connector is set up correctly and ready for further use.

Using the Chat GPT Endpoint in an App

To utilize the Chat GPT endpoint in an app, you need to create a new app and select the data source that contains the custom connector. Design the app interface by adding a button, text input, and a label to display the results.

Configure the button to trigger the chat completion action of the Chat GPT model. Specify the model to be used (GPT3 Turbo or GPT4) and provide the messages as input. The messages should include a system message and a user message.

By customizing the system message, you can guide the model to generate desired responses. The system message sets the Context for the chat interaction. Experiment with different system messages to obtain varied responses.

Test the app to see the chat interaction in action. You should receive responses from the Chat GPT model Based on the input messages and the defined system message.

Using the GPT3 Turbo Model

The GPT3 Turbo model is a powerful variant of the Chat GPT models. It offers robust natural language processing capabilities and can generate coherent and context-aware responses. By utilizing the GPT3 Turbo model in your custom connector, you can enhance the conversational capabilities of your app.

Pros:

• Advanced natural language processing capabilities
• Context-aware responses

Cons:

• May require fine-tuning for specific use cases

Using the GPT4 Model (Preview Only)

If you have access to the GPT4 model through the preview feature, you can leverage its cutting-edge AI capabilities within your custom connector. The GPT4 model offers improved language understanding and generation abilities, pushing the boundaries of AI conversational interfaces.

Pros:

• State-of-the-art language generation
• Enhanced AI capabilities

Cons:

• Restricted to preview users only

Customizing System Messages

System messages play a crucial role in guiding the Chat GPT model's responses. By customizing system messages, you can Shape the conversation and Elicit specific outputs from the model. Experiment with different system messages to achieve the desired conversational style or response pattern.

Conclusion

In this article, we have shown you how to build a custom connector for the Chat GPT endpoint in the Independent Publisher Connector for OpenAI. By following the steps outlined here, you can create your own connector and leverage the power of the Chat GPT 3.5 Turbo model or the GPT4 model. Utilize the chat completion action in your apps to generate dynamic and interactive AI-powered chat responses. Have fun experimenting and exploring the possibilities of AI-driven conversations!

Highlights

• Create a custom connector for the Chat GPT endpoint
• Access the Chat GPT 3.5 Turbo model or the GPT4 model
• Set up the connector and test its functionality
• Use the Chat GPT endpoint in an app to generate dynamic chat responses
• Customize system messages to guide the model's responses

FAQs

Q: Can I use the GPT3 Turbo model without building a custom connector? A: No, the GPT3 Turbo model can only be accessed through a custom connector in the Independent Publisher Connector for OpenAI.

Q: Is the GPT4 model available to all users? A: No, the GPT4 model is currently in the preview stage and accessible only to select users.

Q: How can I customize the responses from the Chat GPT model? A: You can customize the responses by providing different system messages that set the context for the conversation and by experimenting with different user messages.

Q: Can I use the Chat GPT endpoint in multiple apps? A: Yes, you can use the Chat GPT endpoint in multiple apps by integrating the custom connector into each app's data source.

Q: Does the Chat GPT model support multi-turn conversations? A: Yes, the Chat GPT model supports multi-turn conversations by providing a sequence of messages as input.

Q: Can I integrate the Chat GPT endpoint with other AI models? A: Yes, you can integrate the Chat GPT endpoint with other AI models by leveraging the capabilities of the custom connector and combining it with other APIs or models.

Q: Is the Chat GPT endpoint suitable for generating chatbot responses? A: Yes, the Chat GPT endpoint is suitable for generating chatbot responses as it can generate dynamic and interactive chat messages based on user input and system messages.