用Unity构建ChatGPT AI助手:颠覆性创新!
Table of Contents
- Introduction
- Experiment Overview
- Creating the Chat GPT Assistant
- Making an HTTP call to Chat GPT API
- Parsing the Response
- Designing the Chat GPT Tester
- Handling UI Components
- Working with Scriptable Objects
- Implementing Concise Explanations
- Issues and Error Handling
- Assistant Integration with Meta Voice SDK
- Final Code Breakdown
- Conclusion
Experiment: Creating a Chat GPT Assistant
In this experiment, we will explore the creation of a chat GPT assistant using the knowledge gathered from our previous video series on chat GPT. The goal is to develop a system that can answer questions by converting the text response from the chat GPT API into an audio source, allowing us to play the responses. We'll dive into the step-by-step process of building this assistant, including making HTTP calls to the API, parsing the response, designing the UI components, and integrating with the Meta Voice SDK.
1. Introduction
In the realm of artificial intelligence, chat GPT (Generative Pre-trained Transformer) models have gained significant Attention for their ability to generate human-like text responses. In this experiment, we aim to leverage the power of chat GPT to develop a chat assistant that can provide answers to various queries. The assistant will be capable of converting the text responses into audio, enhancing the user experience.
2. Experiment Overview
Before delving into the details, let's gain a high-level understanding of the experiment's flow. We will start by making HTTP calls to the chat GPT API, passing the necessary payload in the request body. Upon receiving the response, we'll parse the information to extract the source code and explanations. To ensure a seamless user experience, concise explanations will be provided. The chat GPT tester will serve as a user interface with various components, all referenced in the inspector. We'll also utilize scriptable objects for question data and implement error handling mechanisms.
3. Creating the Chat GPT Assistant
To kickstart the experiment, we'll Create the chat GPT assistant. This assistant will be responsible for handling user interactions and orchestrating the communication between the user and the chat GPT model. We'll define a welcome message and the messages indicating that transcription is in progress, incorporating caching to provide a smoother experience. By integrating with the Meta Voice SDK, we'll enhance interactions by associating animations with audio responses.
4. Making an HTTP call to Chat GPT API
The Core functionality of our chat GPT assistant relies on making HTTP calls to the Chat GPT API. We'll construct the necessary payload and include it in the request body. Upon sending the request, we'll await the response, with an average response time of 2 to 3 seconds. The response will contain valuable information that we can utilize for further processing.
5. Parsing the Response
Once we receive the response from the Chat GPT API, we'll extract the Relevant information by parsing the JSON contract. This will allow us to access the source code and explanations required for generating the response. To ensure compatibility with the Meta Voice SDK, we'll split the explanations into multiple line items due to the constraints of 280 characters.
6. Designing the Chat GPT Tester
The Chat GPT tester acts as the user interface for our assistant. It consists of several UI components that are referenced in the inspector. By properly designing and organizing these components, we can create an intuitive and user-friendly interface. We'll visually present information, such as the response total time, to provide transparency and enhance the user's understanding of the assistant's behavior.
7. Handling UI Components
A crucial aspect of developing the chat GPT assistant is correctly handling the UI components. We'll define various actions to be executed upon user interactions, such as button clicks. These actions will involve retrieving prompt information, performing animations, handling reminders, and displaying relevant information on the UI. With well-designed UI components, the user will have a seamless and enjoyable experience interacting with the assistant.
8. Working with Scriptable Objects
To efficiently manage and pass data within the chat GPT assistant, we'll utilize scriptable objects. Scriptable objects allow us to create reusable data assets that can be referenced and modified by multiple scripts. We'll leverage this functionality to store and access question-specific information, such as Scenario titles, problem prefixes, and Prompts, without the need for extensive code modifications.
9. Implementing Concise Explanations
In designing the chat GPT assistant, it is crucial to provide concise explanations to ensure a natural conversation flow. As we will be using the Meta Voice SDK, excessively long explanations can feel unnatural. Therefore, we'll focus on generating clear and concise explanations that effectively convey information to the user. We'll continuously iterate and improve this aspect to enhance the overall user experience.
10. Issues and Error Handling
During the development process, we may encounter certain issues and errors that need to be addressed. These could include issues with voice SDK integration, prompt parsing, or UI component functionality. We'll implement error handling mechanisms to track and resolve any potential problems, ensuring the smooth operation of the chat GPT assistant.
11. Assistant Integration with Meta Voice SDK
To enrich the user experience, we'll integrate the chat GPT assistant with the Meta Voice SDK. This integration involves utilizing the TTS (Text-to-Speech) speaker component from Meta to synchronize animations with audio responses. By listening to various events from the TTS speaker, we can control character animations and create a more engaging and immersive interaction for the users.
12. Final Code Breakdown
Taking a closer look at the final code of the chat GPT assistant, we'll examine the various sections and functionalities implemented. This breakdown will provide a comprehensive understanding of how the different components and scripts work together to deliver a seamless user experience. We'll explore the code responsible for making API calls, handling UI components, and integrating with the Meta Voice SDK.
13. Conclusion
In conclusion, this experiment demonstrates the creation of a chat GPT assistant that utilizes text-to-speech technology for enhanced user interactions. By combining the power of chat GPT models, HTTP requests, and user interface design, we've developed a functional assistant capable of answering queries and providing natural responses. The integration with the Meta Voice SDK enhances the user experience, providing audio-Based interactions. With further refinement, this assistant has the potential to be utilized in various applications, revolutionizing the way we interact with AI systems.