Revolutionary: ChatGPT on ESP32 with Audio Output

Table of Contents

1. Introduction
2. Setting up the Project
3. Using the i2s Audio Amplifier with ESP32
4. Converting Text to Speech with ESP32
5. Adding the Chat GPT Feature
6. Code Explanation
7. Testing and Results
8. Conclusion
9. Future Project Ideas
10. Sponsorship Message

Introduction

In this video tutorial, we will be adding a new feature to our ESP32 project using Chat GPT. This new feature will allow us to listen to the responses coming from Chat GPT. We will demonstrate how to connect a speaker to the ESP32 board and convert text to speech using the i2s audio amplifier. We will also provide a step-by-step guide on how to use the Arduino JSON library to fetch and deserialize the responses from the Chat GPT server. By the end of this tutorial, You will be able to integrate the Chat GPT feature into your own projects and listen to the audio feedback.

Setting up the Project

To get started, we will need an ESP32 board, an i2s audio amplifier module, and a 4 ohm speaker. These components can be easily ordered from our Website. Once you have all the components, you can proceed with the following steps:

1. Connect the ESP32 board, i2s audio amplifier module, and the speaker according to the provided connection Diagram.
2. Install the necessary libraries, including the Arduino JSON library and the audio.h library.
3. Configure the Wi-Fi credentials in the code to enable internet connectivity.
4. Upload the code to the ESP32 board using the Arduino IDE.
5. Open the serial monitor to Interact with the project.

Using the i2s Audio Amplifier with ESP32

Before we dive into the Chat GPT feature, let's first learn how to convert any text into speech using the i2s audio amplifier with the ESP32 board. We have provided a sample sketch that demonstrates this functionality. The code is similar to the one used in our internet radio project. By making a slight modification in the code, we can achieve text-to-speech conversion. The modified code uses the function audio.connectToSpeech to provide the input text in STRING format and specify the language for speech conversion. The code leverages Google Text-to-Speech (TTS) service to convert the text into audio. Once the code is uploaded and executed, you will be able to hear the audio feedback for the provided text.

Adding the Chat GPT Feature

To add the Chat GPT feature, we need to make some changes to our existing code. We will introduce two new libraries: Arduino JSON and audio.h. These libraries enable us to handle the JSON-formatted responses from the Chat GPT server and extract the required text. In addition to these changes, we will define certain parameters such as the name, password, Chat GPT token, temperature, and max tokens. These parameters will be used in the request made to the Chat GPT server. After receiving the response, we will deserialize the JSON data and extract the answer. The answer will then be printed on the serial monitor and spoken out using the text-to-speech conversion feature.

Code Explanation

Let's go through the code in more Detail to understand how it works. First, we import the necessary libraries and define the required parameters. The setup part includes connecting to Wi-Fi and configuring the audio settings through the i2s amplifier. In the loop function, We Prompt the user to ask a question and wait until a question is provided through the serial monitor. Once a question is received, an HTTP POST request is made to the Chat GPT server with the question, temperature, and max tokens. The response from the server, in JSON format, is stored in the payload variable. We use the Arduino JSON library to extract the answer from the JSON response. After processing the answer, it is printed on the serial monitor and spoken out using the audio.connectToSpeech function.

Testing and Results

After uploading the modified code to the ESP32 board, open the serial monitor. The code will establish a Wi-Fi connection and wait for a question. Enter a question, and you will see the answer printed on the serial monitor. The speaker connected to the board will also produce the audio feedback for the answer. The code supports different token lengths, allowing you to adjust the response length as per your requirements.

Conclusion

In conclusion, we have successfully added the Chat GPT feature to our ESP32 project. By connecting a speaker and configuring the i2s audio amplifier, we were able to listen to the audio responses generated by Chat GPT. We also understood how to use the Arduino JSON library to fetch and deserialize JSON data. This feature opens up new possibilities for projects that require interactive conversations with the Chat GPT model.

Future Project Ideas

Based on the success of this project, We Are excited about exploring further possibilities with Chat GPT on the ESP32. Here are some future project ideas:

1. Standalone Chat GPT: Create an independent project where questions can be directly provided to the ESP32 without the need for a laptop, computer, or mobile phone.
2. Voice-controlled Chat GPT: Integrate a microphone to enable voice input for questions, making the interaction more natural and convenient.
3. Multi-language Support: Adapt the code to support multiple languages by leveraging the language options provided by Google Text-to-Speech.

We value your suggestions and would love to hear your ideas for the next part of the Chat GPT series. Let us know your thoughts and recommendations in the comments section of the video.

Sponsorship Message

This video is sponsored by LTM, a leading product design platform called LTM 365. LTM 365 offers a comprehensive solution for PCB design, MCAD data management, and teamwork. With LTM 365, you can easily share your PCB designs for review, collaborate with mechanical teams, benefit from centralized cloud storage, manage components, and access real-time supply chain data. The platform enables multiple people to work on a single project and simplifies the process of sending designs to manufacturing units. Try out the free trial version of LTM 365 by clicking on the link provided in the video description.

FAQ

Q: Can I use a different speaker with higher impedance for this project?

A: Yes, you can use a speaker with a higher impedance. However, make sure to adjust the amplifier settings accordingly to ensure optimal performance.

Q: How can I change the language for text-to-speech conversion?

A: In the code, specify the desired language for the audio.connectToSpeech function. The Google Text-to-Speech service supports multiple languages.

Q: Can I increase the token length to receive longer responses?

A: Yes, you can increase the token length by modifying the max_tokens parameter in the code. However, be aware that longer responses may require more processing time and resources.

Q: Does this project require an internet connection to function?

A: Yes, an internet connection is necessary to connect to the Chat GPT server and fetch the responses. Ensure that your ESP32 board is connected to Wi-Fi.

Q: Are there any restrictions or usage limits for the Chat GPT feature?

A: The Chat GPT feature may have certain restrictions and usage limits imposed by the Chat GPT server. Refer to the server documentation or terms of service for more information.

Q: Can I use this code for commercial purposes?

A: The code provided is for educational purposes. If you intend to use it for commercial purposes, ensure compliance with any Relevant licenses or restrictions.

Q: How can I extend the functionality of this project?

A: You can extend this project by adding voice input capabilities, integrating it with other smart devices, or incorporating natural language processing algorithms to improve the conversational experience.

Q: What should I do if I encounter any issues with the project?

A: If you encounter any issues or have specific questions about the project, feel free to ask in the comments section of the video. We will do our best to assist you.