目录
- 前言
- 准备工作
- 集成达芬奇模型
- 效果展示
前言
Spring Boot是由Pivotal团队提供的全新框架,其设计目的是用来简化新Spring应用的初始搭建以及开发过程。该框架使用了特定的方式来进行配置,从而使开发人员不再需要定义样板化的配置。通过这种方式,Spring Boot致力于在蓬勃发展的快速应用编程客栈开发领域(rapid application development)成为领导者。
准备工作
1、初始化一个springboot项目
参考地址:https://www.jb51.ne开发者_C入门t/article/232551.htm
2、访问OPENAI官网获取API密钥
地址:https://platform.openai.com/account/api-keys
3、通过OPENA开源的Java SDK (OpenAI-Java)访问 API
地址:github - TheoKanning/openai-java: OpenAI GPT-3 Api Client in JavcIhFYPNVa
集成达芬奇模型
1、编写SpringBoot项目中的pom文件
<dependency> <groupId>com.theokanning.openai-gpt3-java</groupId> <artifactId>client</artifactId> <version>0.9.0</version> </dependency>
2、初始化OpenAiService类
import com.theokanning.openai.OpenAiService; import org.springframework.beans.factory.annotation.Value; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Cphponfiguration; import java.time.Duration; /** * openai 配置类 */ @Configuration public class OpenAiConfiguration { @Value("${open.ai.key}") private String openAiKey; @Value("${open.ai.request.timeout}") private long timeout; @Bean public OpenAiService openAiService(){ return new OpenAiService(openAiKey, Duration.ofSeconds(timeout)); } }
3、配置密钥、超时时间和使用的模型
#application.properties server.port=8081 #密钥 open.ai.key=xxxxxxxx #超时时间 open.ai.request.timeout=100000 #达芬奇模型 open.ai.model=text-davinci-003
3、编写访问业务类
import com.google.common.collect.Maps; import com.t编程客栈heokanning.openai.OpenAiService; import com.theokanning.openai.completion.CompletionRequest; import com.theokanning.openai.completion.CompletionResult; import lombok.extern.slf4j.Slf4j; import org.apache.commons.lang3.StringUtils; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.beans.factory.annotation.Value; import org.springframework.stereotype.Service; import java.util.Arrays; import java.util.Map; @Slf4j @Service public class OpenAiChatBiz { @Value("${open.ai.model}") private String openAiModel; @Autowired private OpenAiService openAiService; /** * 聊天 * @param prompt * @return */ public String chat(String prompt){ CompletionRequest completionRequest = CompletionRequest.builder() .prompt(prompt) .model(openAiModel)php .echo(true) .temperature(0.7) .topP(1d) .frequencyPenalty(0d) .presencePenalty(0d) .maxTokens(1000) .build(); CompletionResult completionResult = openAiService.createCompletion(completionRequest); String text = completionResult.getChoices().get(0).getText(); return text; } }
4、编写访问接口
import org.apache.commons.lang3.StringUtils; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RequestMethod; import org.springframework.web.bind.annotation.RequestParam; import org.springframework.web.bind.annotation.RestController; @RestController public class OpenAiChatApi { @Autowired private OpenAiChatBiz openAiChatBiz; @RequestMapping(path = "/chat/question",method = RequestMethod.GET) public String openAiChat(@RequestParam("question")String question){ if(StringUtils.isBlank(question)){ return "Please Input"; } return openAiChatBiz.chat(question); } }
效果展示
使用google的API Tester插件进行测试
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