How to use ChatGPT and Java to develop an intelligent investment advice tool
Introduction:
In recent years, with the rapid development of artificial intelligence technology, more and more Traditional industries have begun to join the trend of intelligence. The investment field is no exception. Many investors hope to use intelligent tools to improve the accuracy and efficiency of investment analysis. This article will introduce how to use ChatGPT and Java to develop an intelligent investment advice tool, and provide specific code examples.
1. Introduction to ChatGPT:
ChatGPT is a text generation model developed by OpenAI, which can give corresponding answers or suggestions based on the input text. It uses a large amount of training data to generate text through a neural network model. We can use ChatGPT to implement intelligent conversation functions.
2. Setting up a Java development environment:
Before we start, we need to set up a Java development environment. First, make sure you have installed the Java Development Kit (JDK) and configured the relevant environment variables. Next, we need to choose an integrated development environment (IDE) to write and debug Java code. It is recommended to use Eclipse or IntelliJ IDEA. After installing the development environment, we can start writing code.
3. Introduce the ChatGPT library:
In order to use the ChatGPT function, we need to introduce the corresponding library. In Java, we can use the Gpt-3.5-turbo library officially provided by OpenAI. You can add the following dependencies in the project's pom.xml file:
<dependency> <groupId>ai.openai.gpt-3.5-turbo</groupId> <artifactId>jackson-databind</artifactId> <version>2.10.5.1</version> </dependency>
In addition, you also need to register an account on the OpenAI official website and obtain API credentials in order to call the ChatGPT API interface in the code.
4. Implement intelligent investment recommendation tools:
Connect to ChatGPT
First, we need to write a method to connect to ChatGPT. In this method, we need to set up the API credentials and create an instance of the ChatCompletion class. The code sample is as follows:
import ai.openai.gpt.ChatCompletion; public class InvestmentAdvisor { private ChatCompletion chatCompletion; public InvestmentAdvisor(String apiKey) { chatCompletion = new ChatCompletion(apiKey); } }
Provide investment questions
Next, we need to write a method to provide investment questions and get input from the user. The code example is as follows:
import java.util.Scanner; public class InvestmentAdvisor { // ... public String getUserInput() { Scanner scanner = new Scanner(System.in); System.out.println("请输入您的投资问题:"); return scanner.nextLine(); } }
Get smart suggestions
Then, we pass the user’s investment questions to ChatGPT and get smart suggestions. The code example is as follows:
import ai.openai.gpt.CompletionRequest; public class InvestmentAdvisor { // ... public String getInvestmentAdvice(String userInput) { CompletionRequest completionRequest = new CompletionRequest.Builder() .setPrompt(userInput) .setMaxTokens(50) .setTemperature(0.7) .build(); String response = chatCompletion.complete(completionRequest); // 剥离多余的部分,只保留智能回答 int index = response.indexOf("回答:"); if (index != -1) { response = response.substring(index + 3); } return response.trim(); } }
Full code example
Finally, we combine the above code together and add a main method to make the actual call and run. The complete code example is as follows:
import ai.openai.gpt.ChatCompletion; import ai.openai.gpt.CompletionRequest; import java.util.Scanner; public class InvestmentAdvisor { private ChatCompletion chatCompletion; public InvestmentAdvisor(String apiKey) { chatCompletion = new ChatCompletion(apiKey); } public String getUserInput() { Scanner scanner = new Scanner(System.in); System.out.println("请输入您的投资问题:"); return scanner.nextLine(); } public String getInvestmentAdvice(String userInput) { CompletionRequest completionRequest = new CompletionRequest.Builder() .setPrompt(userInput) .setMaxTokens(50) .setTemperature(0.7) .build(); String response = chatCompletion.complete(completionRequest); int index = response.indexOf("回答:"); if (index != -1) { response = response.substring(index + 3); } return response.trim(); } public static void main(String[] args) { String apiKey = "YOUR_API_KEY"; InvestmentAdvisor advisor = new InvestmentAdvisor(apiKey); String userInput = advisor.getUserInput(); String advice = advisor.getInvestmentAdvice(userInput); System.out.println("智能建议:" + advice); } }
5. Summary:
Through the above steps, we have successfully implemented an intelligent investment advice tool developed using ChatGPT and Java. Users can talk to the program, ask investment questions, and receive intelligent advice. This intelligent tool can help investors make decisions more accurately and efficiently, and is of great value in improving the effectiveness of investment research.
6. References:
Note: This article only provides a basic example, and actual applications need to be carried out according to specific needs. Expand and optimize. Please use the functions of ChatGPT in accordance with the relevant regulations of OpenAI, and pay attention to protecting user privacy and data security.
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