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Visual_Novel_Server
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26
pom.xml
View File

@ -28,22 +28,6 @@
<enabled>false</enabled> <enabled>false</enabled>
</snapshots> </snapshots>
</repository> </repository>
<repository>
<id>spring-milestones</id>
<name>Spring Milestones</name>
<url>https://repo.spring.io/milestone</url>
<snapshots>
<enabled>false</enabled>
</snapshots>
</repository>
<repository>
<id>spring-snapshots</id>
<name>Spring Snapshots</name>
<url>https://repo.spring.io/snapshot</url>
<releases>
<enabled>false</enabled>
</releases>
</repository>
</repositories> </repositories>
<properties> <properties>
@ -51,7 +35,6 @@
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding> <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>17</maven.compiler.source> <maven.compiler.source>17</maven.compiler.source>
<maven.compiler.target>17</maven.compiler.target> <maven.compiler.target>17</maven.compiler.target>
<spring-ai.version>1.0.0-M6</spring-ai.version>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding> <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
</properties> </properties>
@ -70,13 +53,6 @@
<dependencyManagement> <dependencyManagement>
<dependencies> <dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>${spring-ai.version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
<dependency> <dependency>
<groupId>org.mybatis.spring.boot</groupId> <groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId> <artifactId>mybatis-spring-boot-starter</artifactId>
@ -188,8 +164,6 @@
</plugins> </plugins>
</build> </build>
<profiles> <profiles>
<profile> <profile>
<id>dev</id> <id>dev</id>

6
visual-novel-server-app/pom.xml
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@ -12,6 +12,10 @@
<packaging>jar</packaging> <packaging>jar</packaging>
<dependencies> <dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency> <dependency>
<groupId>org.springframework.boot</groupId> <groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId> <artifactId>spring-boot-starter-test</artifactId>
@ -130,6 +134,4 @@
</plugins> </plugins>
</build> </build>
</project> </project>

6
visual-novel-server-app/src/main/java/com/touka/config/package-info.java Normal file
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@ -0,0 +1,6 @@
/**
* 1. 用于管理引入的Jar所需的资源启动或者初始化处理
* 2. 如果有AOP切面，可以再建一个aop包，来写切面逻辑
*/
package com.touka.config;

47
visual-novel-server-app/src/main/resources/application-dev.yml
View File

@ -12,7 +12,7 @@ thread:
block-queue-size: 5000 block-queue-size: 5000
policy: CallerRunsPolicy policy: CallerRunsPolicy
# 数据库配置 # 数据库配置；启动时配置数据库资源信息
spring: spring:
datasource: datasource:
username: root username: root
@ -21,45 +21,16 @@ spring:
driver-class-name: com.mysql.cj.jdbc.Driver driver-class-name: com.mysql.cj.jdbc.Driver
hikari: hikari:
pool-name: Retail_HikariCP pool-name: Retail_HikariCP
minimum-idle: 15 minimum-idle: 15 #最小空闲连接数量
idle-timeout: 180000 idle-timeout: 180000 #空闲连接存活最大时间，默认600000（10分钟）
maximum-pool-size: 25 maximum-pool-size: 25 #连接池最大连接数，默认是10
auto-commit: true auto-commit: true #此属性控制从池返回的连接的默认自动提交行为,默认值：true
max-lifetime: 1800000 max-lifetime: 1800000 #此属性控制池中连接的最长生命周期，值0表示无限生命周期，默认1800000即30分钟
connection-timeout: 30000 connection-timeout: 30000 #数据库连接超时时间,默认30秒，即30000
connection-test-query: SELECT 1 connection-test-query: SELECT 1
type: com.zaxxer.hikari.HikariDataSource type: com.zaxxer.hikari.HikariDataSource
ai: # MyBatis 配置【如需使用记得打开】
deepseek:
api-key: your-api-key
base-url: https://api.deepseek.com
chat:
options:
model: deepseek-reasoner
temperature: 0.8
openai: # 注意：这个应该在spring: ai: 下面，而不是与spring平级
api-key: sk-EcUhlzeo44aQLBJqNncwBxw8yQuAE8rlbe8fNWLC3RXxfDGq
base-url: https://api.chatanywhere.tech # 您使用的是第三方API
chat:
options:
model: gpt-3.5-turbo
temperature: 0.7
max-tokens: 2048
llm:
# 默认连接器类型
default-connector: openai
# 各连接器详细配置
connectors:
# OpenAI连接器配置
openai:
api-key: sk-EcUhlzeo44aQLBJqNncwBxw8yQuAE8rlbe8fNWLC3RXxfDGq
base-url: https://api.chatanywhere.tech
timeout-ms: 30000
enabled: true
# MyBatis 配置
#mybatis: #mybatis:
# mapper-locations: classpath:/mybatis/mapper/*.xml # mapper-locations: classpath:/mybatis/mapper/*.xml
# config-location: classpath:/mybatis/config/mybatis-config.xml # config-location: classpath:/mybatis/config/mybatis-config.xml
@ -68,4 +39,4 @@ llm:
logging: logging:
level: level:
root: info root: info
config: classpath:logback-spring.xml config: classpath:logback-spring.xml

101
visual-novel-server-app/src/test/java/com/touka/test/ApiTest.java
View File

@ -1,82 +1,19 @@
//package com.touka.test; package com.touka.test;
//
//import jakarta.annotation.Resource; import lombok.extern.slf4j.Slf4j;
//import lombok.extern.slf4j.Slf4j; import org.junit.Test;
//import org.junit.Test; import org.junit.runner.RunWith;
//import org.junit.runner.RunWith; import org.springframework.boot.test.context.SpringBootTest;
//import org.springframework.ai.chat.model.ChatResponse; import org.springframework.test.context.junit4.SpringRunner;
//
//import org.springframework.ai.chat.prompt.Prompt; @Slf4j
//import org.springframework.ai.chat.prompt.PromptTemplate; @RunWith(SpringRunner.class)
// @SpringBootTest
// public class ApiTest {
//import org.springframework.ai.deepseek.DeepSeekChatModel;
//import org.springframework.ai.ollama.api.OllamaOptions; @Test
// public void test() {
//import org.springframework.boot.test.context.SpringBootTest; log.info("测试完成");
//import org.springframework.test.context.junit4.SpringRunner; }
//
//import reactor.core.publisher.Flux; }
//
//@Slf4j
//@RunWith(SpringRunner.class)
//@SpringBootTest
//public class ApiTest {
//
// @Resource
// private DeepSeekChatModel chatModel;
//
// /**
// * 测试同步生成响应
// */
// @Test
// public void testGenerate() {
// String message = "Tell me a joke";
//
// // 方式1: 直接传入字符串
// String response1 = chatModel.call(message);
// System.out.println("Response1: " + response1);
//
// // 方式2: 使用 Prompt
// ChatResponse response2 = chatModel.call(new Prompt(message));
// System.out.println("Response2: " + response2.getResult().getOutput().getText());
// }
//
// /**
// * 测试流式生成响应
// */
// @Test
// public void testGenerateStream() {
// String message = "Tell me a joke";
//
// // 使用 PromptTemplate 构建提示词
// Prompt prompt = new PromptTemplate(message).create();
//
// // 流式输出
// Flux<ChatResponse> responseFlux = chatModel.stream(prompt);
//
// // 订阅并打印流式响应
// responseFlux.doOnNext(response -> {
// System.out.println("Stream Response: " + response.getResult().getOutput().getText());
// }).blockLast(); // 在测试中阻塞等待完成
// }
//
// /**
// * 测试使用特定模型选项
// */
// @Test
// public void testGenerateWithModelOptions() {
// String message = "1+1=?";
// String model = "deepseek-r1:1.5b";
//
// ChatResponse response = chatModel.call(new Prompt(
// message,
// OllamaOptions.builder()
// .model(model)
// .build()
// ));
//
// System.out.println("Response with model options: " + response.getResult().getOutput().getText());
// }
//
//}

10
visual-novel-server-trigger/pom.xml
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@ -10,16 +10,6 @@
<artifactId>visual-novel-server-trigger</artifactId> <artifactId>visual-novel-server-trigger</artifactId>
<dependencies> <dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
</dependency>
<dependency> <dependency>
<groupId>org.springframework.boot</groupId> <groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId> <artifactId>spring-boot-starter-web</artifactId>

64
visual-novel-server-trigger/src/main/java/com/touka/trigger/http/controller/LLMController.java
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@ -1,64 +0,0 @@
package com.touka.trigger.http.controller;
import java.util.Map;
import com.touka.trigger.http.service.LLMService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
/**
* LLM控制器，提供REST API接口
*/
@RestController
@RequestMapping("/api/llm")
public class LLMController {
private final LLMService llmService;
@Autowired
public LLMController(LLMService llmService) {
this.llmService = llmService;
}
@PostMapping("/generate")
public String generate(@RequestBody Map<String, Object> request) {
String prompt = (String) request.get("prompt");
if (prompt == null) {
throw new IllegalArgumentException("Prompt is required");
}
@SuppressWarnings("unchecked")
Map<String, Object> params = (Map<String, Object>) request.getOrDefault("params", Map.of());
String connectorType = (String) request.get("connectorType");
if (connectorType != null) {
return llmService.generateText(connectorType, prompt, params);
} else {
return llmService.generateText(prompt, params);
}
}
@GetMapping("/stream")
public SseEmitter stream(
@RequestParam String prompt,
@RequestParam(required = false) String connectorType) {
SseEmitter emitter = new SseEmitter(Long.MAX_VALUE);
llmService.streamText(prompt, Map.of(), emitter);
return emitter;
}
@SuppressWarnings("unchecked")
@GetMapping("/connectors")
public Map<String, Object> getConnectors() {
return (Map<String, Object>) (Map<?, ?>) llmService.getAllAvailableConnectors();
}
}

42
visual-novel-server-trigger/src/main/java/com/touka/trigger/http/controller/OllamaController.java
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@ -1,42 +0,0 @@
//package com.touka.trigger.http.controller;
//
//import jakarta.annotation.Resource;
//import org.springframework.ai.chat.messages.UserMessage;
//import org.springframework.ai.chat.prompt.Prompt;
//import org.springframework.ai.deepseek.DeepSeekChatModel;
//import org.springframework.web.bind.annotation.CrossOrigin;
//import org.springframework.web.bind.annotation.GetMapping;
//import org.springframework.web.bind.annotation.RequestMapping;
//import org.springframework.web.bind.annotation.RequestParam;
//import org.springframework.web.bind.annotation.RestController;
//import reactor.core.publisher.Flux;
//
//import java.util.Map;
//
//@RestController()
//@CrossOrigin("*")
//@RequestMapping("/api/ollama/")
//public class OllamaController {
// @Resource
// private DeepSeekChatModel chatModel;
//
// @GetMapping("/generate")
// public Map generate(@RequestParam(value = "message") String message) {
// return Map.of("generation", chatModel.call(message));
// }
//
// /**
// * 流式对话
// * @param message
// * @return
// */
// @GetMapping(value = "/generateStream", produces = "text/html;charset=utf-8")
// public Flux<String> generateStream(@RequestParam(value = "message") String message) {
// // 构建提示词
// Prompt prompt = new Prompt(new UserMessage(message));
// // 流式输出
// return chatModel.stream(prompt)
// .mapNotNull(chatResponse -> chatResponse.getResult().getOutput().getText());
// }
//
//}

4
visual-novel-server-trigger/src/main/java/com/touka/trigger/http/package-info.java Normal file
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@ -0,0 +1,4 @@
/**
* HTTP 接口服务
*/
package com.touka.trigger.http;

148
visual-novel-server-trigger/src/main/java/com/touka/trigger/http/service/LLMService.java
View File

@ -1,148 +0,0 @@
package com.touka.trigger.http.service;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
import com.touka.types.config.ILLMConnector;
import com.touka.types.config.LLMConnectorFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
import reactor.core.publisher.Flux;
/**
* LLM服务，提供简化的接口来调用不同的LLM连接器
*/
@Service
public class LLMService {
private final LLMConnectorFactory connectorFactory;
@Autowired
public LLMService(LLMConnectorFactory connectorFactory) {
this.connectorFactory = connectorFactory;
}
/**
* 使用默认连接器生成文本
* @param prompt 提示词
* @return 生成的文本
*/
public String generateText(String prompt) {
return generateText(prompt, Collections.emptyMap());
}
/**
* 使用默认连接器生成文本
* @param prompt 提示词
* @param params 额外参数
* @return 生成的文本
*/
public String generateText(String prompt, Map<String, Object> params) {
ILLMConnector connector = connectorFactory.getDefaultConnector();
if (connector == null) {
throw new IllegalStateException("No available LLM connector");
}
return connector.generateText(prompt, params);
}
/**
* 使用指定连接器生成文本
* @param connectorType 连接器类型
* @param prompt 提示词
* @param params 额外参数
* @return 生成的文本
*/
public String generateText(String connectorType, String prompt, Map<String, Object> params) {
ILLMConnector connector = connectorFactory.getConnector(connectorType);
if (connector == null || !connector.isAvailable()) {
throw new IllegalArgumentException("Connector not found or not available: " + connectorType);
}
return connector.generateText(prompt, params);
}
/**
* 流式生成文本
* @param prompt 提示词
* @param emitter SSE发射器
*/
public void streamText(String prompt, SseEmitter emitter) {
streamText(prompt, Collections.emptyMap(), emitter);
}
/**
* 流式生成文本
* @param prompt 提示词
* @param params 额外参数
* @param emitter SSE发射器
*/
public void streamText(String prompt, Map<String, Object> params, SseEmitter emitter) {
ILLMConnector connector = connectorFactory.getDefaultConnector();
if (connector == null) {
emitter.completeWithError(new IllegalStateException("No available LLM connector"));
return;
}
// 使用Flux处理流式响应
Flux<String> textFlux = connector.streamText(prompt, params);
textFlux.subscribe(
content -> {
try {
emitter.send(SseEmitter.event().data(content));
} catch (Exception e) {
emitter.completeWithError(e);
}
},
error -> emitter.completeWithError(error),
() -> emitter.complete()
);
}
/**
* 使用指定连接器流式生成文本
* @param connectorType 连接器类型
* @param prompt 提示词
* @param params 额外参数
* @param emitter SSE发射器
*/
public void streamText(String connectorType, String prompt, Map<String, Object> params, SseEmitter emitter) {
ILLMConnector connector = connectorFactory.getConnector(connectorType);
if (connector == null || !connector.isAvailable()) {
emitter.completeWithError(new IllegalArgumentException("Connector not found or not available: " + connectorType));
return;
}
// 使用Flux处理流式响应
Flux<String> textFlux = connector.streamText(prompt, params);
textFlux.subscribe(
content -> {
try {
emitter.send(SseEmitter.event().data(content));
} catch (Exception e) {
emitter.completeWithError(e);
}
},
error -> emitter.completeWithError(error),
() -> emitter.complete()
);
}
/**
* 获取所有可用的连接器类型
* @return 连接器类型列表
*/
@SuppressWarnings("unchecked")
public Map<String, Object> getAllAvailableConnectors() {
Map<String, Object> availableConnectors = new HashMap<>();
connectorFactory.getAllConnectors().forEach((type, connector) -> {
if (connector.isAvailable()) {
availableConnectors.put(type, connector);
}
});
return availableConnectors;
}
}

4
visual-novel-server-trigger/src/main/java/com/touka/trigger/job/package-info.java Normal file
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@ -0,0 +1,4 @@
/**
* 任务服务，可以选择使用 Spring 默认提供的 Schedule https://bugstack.cn/md/road-map/quartz.html
*/
package com.touka.trigger.job;

5
visual-novel-server-trigger/src/main/java/com/touka/trigger/listener/package-info.java Normal file
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@ -0,0 +1,5 @@
/**
* 监听服务；在单体服务中，解耦流程。类似MQ的使用，如Spring的Event，Guava的事件总线都可以。如果使用了 Redis 那么也可以有发布/订阅使用。
* Guava：https://bugstack.cn/md/road-map/guava.html
*/
package com.touka.trigger.listener;

16
visual-novel-server-types/pom.xml
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@ -10,22 +10,6 @@
<artifactId>visual-novel-server-types</artifactId> <artifactId>visual-novel-server-types</artifactId>
<dependencies> <dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
<!-- 添加OpenAI SDK依赖 -->
<dependency>
<groupId>com.theokanning.openai-gpt3-java</groupId>
<artifactId>client</artifactId>
<version>0.18.0</version>
</dependency>
<dependency> <dependency>
<groupId>org.springframework.boot</groupId> <groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId> <artifactId>spring-boot-starter-web</artifactId>

54
visual-novel-server-types/src/main/java/com/touka/types/config/BaseLLMConnector.java
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@ -1,54 +0,0 @@
package com.touka.types.config;
/**
* LLM连接器的基础实现，提供一些通用功能
*/
public abstract class BaseLLMConnector implements ILLMConnector {
protected String apiKey;
protected String baseUrl;
protected int timeoutMs;
protected boolean enabled;
public BaseLLMConnector(String apiKey, String baseUrl, int timeoutMs) {
this.apiKey = apiKey;
this.baseUrl = baseUrl;
this.timeoutMs = timeoutMs;
this.enabled = true;
}
@Override
public boolean isAvailable() {
return enabled;
}
public void setEnabled(boolean enabled) {
this.enabled = enabled;
}
public String getApiKey() {
return apiKey;
}
public void setApiKey(String apiKey) {
this.apiKey = apiKey;
}
public String getBaseUrl() {
return baseUrl;
}
public void setBaseUrl(String baseUrl) {
this.baseUrl = baseUrl;
}
public int getTimeoutMs() {
return timeoutMs;
}
public void setTimeoutMs(int timeoutMs) {
this.timeoutMs = timeoutMs;
}
}

55
visual-novel-server-types/src/main/java/com/touka/types/config/ILLMConnector.java
View File

@ -1,55 +0,0 @@
package com.touka.types.config;
import java.util.Map;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.prompt.Prompt;
import reactor.core.publisher.Flux;
/**
* 大语言模型连接器接口，定义了与各类LLM API交互的统一方法
*/
public interface ILLMConnector {
/**
* 使用Prompt对象生成文本响应
* @param prompt 提示对象
* @return 聊天响应
*/
ChatResponse generateResponse(Prompt prompt);
/**
* 使用文本提示生成文本
* @param textPrompt 文本提示
* @param params 额外参数
* @return 生成的文本内容
*/
String generateText(String textPrompt, Map<String, Object> params);
/**
* 流式生成文本响应
* @param prompt 提示对象
* @return 响应流
*/
Flux<ChatResponse> streamResponse(Prompt prompt);
/**
* 流式生成文本
* @param textPrompt 文本提示
* @param params 额外参数
* @return 文本流
*/
Flux<String> streamText(String textPrompt, Map<String, Object> params);
/**
* 获取连接器类型
* @return 连接器类型标识
*/
String getConnectorType();
/**
* 检查连接器是否可用
* @return 连接器是否可用
*/
boolean isAvailable();
}

42
visual-novel-server-types/src/main/java/com/touka/types/config/LLMConfig.java
View File

@ -1,42 +0,0 @@
package com.touka.types.config;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.openai.OpenAiChatModel;
import org.springframework.ai.openai.OpenAiChatOptions;
import org.springframework.ai.openai.api.OpenAiApi;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
// 在配置类中添加
@Configuration
public class LLMConfig {
@Bean
public ChatClient chatClient(ChatClient.Builder builder) {
return builder.build();
}
@Bean
public ChatClient.Builder chatClientBuilder(OpenAiChatModel openAiChatModel) {
// 根据配置创建Builder
return ChatClient.builder(openAiChatModel);
}
@Bean
public OpenAiChatModel openAiChatModel(OpenAiApi openAiApi) {
OpenAiChatOptions options = OpenAiChatOptions.builder()
.model("gpt-3.5-turbo")
.temperature(0.7)
.maxCompletionTokens(2048)
.build();
return new OpenAiChatModel(openAiApi, options);
}
@Bean
public OpenAiApi openAiApi(@Value("${spring.ai.openai.api-key}") String apiKey, @Value("${spring.ai.openai.base-url}") String baseUrl) {
return OpenAiApi.builder().
baseUrl(baseUrl).
apiKey(apiKey).
build();
}
}

34
visual-novel-server-types/src/main/java/com/touka/types/config/LLMConnectorConfig.java
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@ -1,34 +0,0 @@
package com.touka.types.config;
import java.util.Map;
import lombok.Data;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.stereotype.Component;
/**
* LLM连接器的配置类，用于从配置文件中读取连接器配置
*/
@Data
@Component
@ConfigurationProperties(prefix = "llm")
public class LLMConnectorConfig {
/**
* 默认连接器类型
*/
private String defaultConnector;
/**
* 各连接器的详细配置
*/
private Map<String, ConnectorDetailConfig> connectors;
@Data
public static class ConnectorDetailConfig {
private String apiKey;
private String baseUrl;
private int timeoutMs = 30000;
private boolean enabled = true;
private Map<String, Object> additionalParams;
}
}

124
visual-novel-server-types/src/main/java/com/touka/types/config/LLMConnectorFactory.java
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@ -1,124 +0,0 @@
package com.touka.types.config;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import com.touka.types.config.impl.OpenAIConnector;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Component;
/**
* LLM连接器工厂，用于创建和管理不同类型的连接器实例
*/
@Component
public class LLMConnectorFactory {
@Value("${spring.ai.openai.api-key:}")
private String defaultApiKey;
@Value("${spring.ai.openai.base-url:https://api.openai.com/v1}")
private String defaultBaseUrl;
private final LLMConnectorConfig config;
private final ChatClient chatClient;
private final Map<String, ILLMConnector> connectors = new ConcurrentHashMap<>();
@Autowired
public LLMConnectorFactory(LLMConnectorConfig config, ChatClient chatClient) {
this.config = config;
this.chatClient = chatClient;
initializeConnectors();
}
private void initializeConnectors() {
// 注册默认连接器
registerDefaultConnectors();
// 根据配置初始化连接器
if (config.getConnectors() != null) {
for (Map.Entry<String, LLMConnectorConfig.ConnectorDetailConfig> entry : config.getConnectors().entrySet()) {
String connectorType = entry.getKey();
LLMConnectorConfig.ConnectorDetailConfig detailConfig = entry.getValue();
if (detailConfig.isEnabled()) {
ILLMConnector connector = createConnector(connectorType, detailConfig);
if (connector != null) {
connectors.put(connectorType, connector);
}
}
}
}
}
private void registerDefaultConnectors() {
// 注册默认连接器实现，传入所有必要的参数
connectors.put("openai", new OpenAIConnector(chatClient, defaultApiKey, defaultBaseUrl));
}
private ILLMConnector createConnector(String connectorType, LLMConnectorConfig.ConnectorDetailConfig detailConfig) {
switch (connectorType.toLowerCase()) {
case "openai":
return new OpenAIConnector(
detailConfig.getApiKey(),
detailConfig.getBaseUrl(),
detailConfig.getTimeoutMs(),
chatClient);
default:
// 可以扩展支持更多连接器类型
return null;
}
}
/**
* 获取指定类型的连接器
* @param connectorType 连接器类型
* @return 连接器实例，如果不存在则返回null
*/
public ILLMConnector getConnector(String connectorType) {
return connectors.get(connectorType);
}
/**
* 获取默认连接器
* @return 默认连接器实例
*/
public ILLMConnector getDefaultConnector() {
String defaultType = config.getDefaultConnector();
if (defaultType != null) {
ILLMConnector connector = connectors.get(defaultType);
if (connector != null && connector.isAvailable()) {
return connector;
}
}
// 如果没有配置默认连接器或默认连接器不可用，返回第一个可用的连接器
return connectors.values().stream()
.filter(ILLMConnector::isAvailable)
.findFirst()
.orElse(null);
}
/**
* 注册新的连接器
* @param connector 连接器实例
*/
public void registerConnector(ILLMConnector connector) {
if (connector != null) {
connectors.put(connector.getConnectorType(), connector);
}
}
/**
* 获取所有可用的连接器类型
* @return 连接器类型列表
*/
public Map<String, ILLMConnector> getAllConnectors() {
return new ConcurrentHashMap<>(connectors);
}
}

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visual-novel-server-types/src/main/java/com/touka/types/config/impl/OpenAIConnector.java
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@ -1,159 +0,0 @@
package com.touka.types.config.impl;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import com.touka.types.config.BaseLLMConnector;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.model.Generation;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.chat.prompt.SystemPromptTemplate;
import org.springframework.ai.chat.messages.Message;
import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.openai.OpenAiChatOptions;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Component;
import reactor.core.publisher.Flux;
/**
* OpenAI API连接器实现，基于Spring AI的ChatModel和ChatClient
*/
@Component
public class OpenAIConnector extends BaseLLMConnector {
private static final String CONNECTOR_TYPE = "openai";
private final ChatClient chatClient;
@Autowired
public OpenAIConnector(ChatClient chatClient,
@Value("${spring.ai.openai.api-key:}") String apiKey,
@Value("${spring.ai.openai.base-url:https://api.openai.com/v1}") String baseUrl) {
// 直接在构造函数中使用注入的值
super(apiKey, baseUrl, 30000);
this.chatClient = chatClient;
}
public OpenAIConnector(String apiKey, String baseUrl, int timeoutMs, ChatClient chatClient) {
super(apiKey, baseUrl, timeoutMs);
this.chatClient = chatClient;
}
@Override
public ChatResponse generateResponse(Prompt prompt) {
return chatClient.prompt(prompt).call().chatResponse();
}
@Override
public String generateText(String textPrompt, Map<String, Object> params) {
// 构建消息列表
List<Message> messages = new ArrayList<>();
// 添加系统消息（如果有）
if (params != null && params.containsKey("systemPrompt")) {
String systemPrompt = (String) params.get("systemPrompt");
messages.add(new SystemPromptTemplate(systemPrompt).createMessage(params));
}
// 添加用户消息
messages.add(new UserMessage(textPrompt));
// 创建提示
Prompt prompt = new Prompt(messages, createOptions(params));
// 调用ChatClient生成响应
ChatResponse response = chatClient.prompt(prompt).call().chatResponse();
// 提取生成的文本
if (response.getResults() != null && !response.getResults().isEmpty()) {
Generation generation = response.getResults().get(0);
return generation.getOutput().getText();
}
return "";
}
@Override
public Flux<ChatResponse> streamResponse(Prompt prompt) {
return chatClient.prompt(prompt).stream().chatResponse();
}
@Override
public Flux<String> streamText(String textPrompt, Map<String, Object> params) {
// 构建消息列表
List<Message> messages = new ArrayList<>();
// 添加系统消息（如果有）
if (params != null && params.containsKey("systemPrompt")) {
String systemPrompt = (String) params.get("systemPrompt");
messages.add(new SystemPromptTemplate(systemPrompt).createMessage(params));
}
// 添加用户消息
messages.add(new UserMessage(textPrompt));
// 创建提示
Prompt prompt = new Prompt(messages, createOptions(params));
// 流式调用并处理响应
return chatClient.prompt(prompt).stream().chatResponse()
.mapNotNull(response -> {
if (response.getResults() != null && !response.getResults().isEmpty()) {
Generation generation = response.getResults().get(0);
return generation.getOutput().getText();
}
return "";
})
.filter(content -> !content.isEmpty());
}
@Override
public String getConnectorType() {
return CONNECTOR_TYPE;
}
/**
* 根据参数创建OpenAI选项
*/
private OpenAiChatOptions createOptions(Map<String, Object> params) {
OpenAiChatOptions.Builder builder = OpenAiChatOptions.builder();
if (params != null) {
// 设置模型
if (params.containsKey("model")) {
builder.model((String) params.get("model"));
}
// 设置温度
if (params.containsKey("temperature")) {
builder.temperature(Double.parseDouble(params.get("temperature").toString()));
}
// 设置最大生成长度
if (params.containsKey("maxTokens")) {
builder.maxTokens(Integer.parseInt(params.get("maxTokens").toString()));
}
// 设置topP
if (params.containsKey("topP")) {
builder.topP(Double.parseDouble(params.get("topP").toString()));
}
// 设置停止词
if (params.containsKey("stop")) {
if (params.get("stop") instanceof String) {
builder.stop(List.of((String) params.get("stop")));
} else if (params.get("stop") instanceof List) {
@SuppressWarnings("unchecked")
List<String> stopList = (List<String>) params.get("stop");
builder.stop(stopList);
}
}
}
return builder.build();
}
}