Java/seer-teach-cloud-21
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Merge remote-tracking branch 'origin/master' into dev-chenjiajian

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嘉多宝宝 2025-12-30 09:39:07 +08:00
commit 92ad9f88a0
28 changed files with 1410 additions and 546 deletions
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2
seer-admin/src/main/java/com/seer/teach/admin/SeerAdminApplication.java
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@ -15,7 +15,7 @@ import org.springframework.transaction.annotation.EnableTransactionManagement;
@Slf4j @Slf4j
@EnableFeignClients(basePackages = "com.seer.teach.*.api") @EnableFeignClients(basePackages = "com.seer.teach.*.api")
@SpringBootApplication(scanBasePackages = "com.seer",exclude = QuartzAutoConfiguration.class) @SpringBootApplication(scanBasePackages = "com.seer",exclude = {QuartzAutoConfiguration.class})
@EnableTransactionManagement @EnableTransactionManagement
@EnableAspectJAutoProxy @EnableAspectJAutoProxy
@EnableAsync @EnableAsync

6
seer-admin/src/main/resources/application.yml
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@ -11,13 +11,8 @@ spring:
main: main:
allow-bean-definition-overriding: true allow-bean-definition-overriding: true
allow-circular-references: true allow-circular-references: true
mvc:
profiles: profiles:
active: dev active: dev
mvc:
pathmatch:
matching-strategy: ant_path_matcher
flyway: flyway:
enabled: true enabled: true
locations: classpath:db/mysql locations: classpath:db/mysql
@ -39,6 +34,7 @@ spring:
server-addr: 192.168.0.39:8848 # 配置中心地址 server-addr: 192.168.0.39:8848 # 配置中心地址
file-extension: yaml # 配置文件后缀（yaml/properties） file-extension: yaml # 配置文件后缀（yaml/properties）
namespace: ${spring.profiles.active} namespace: ${spring.profiles.active}
#日志 #日志
logging: logging:
config: classpath:logback-${spring.profiles.active}.xml config: classpath:logback-${spring.profiles.active}.xml

5
seer-common/common-enums/src/main/java/com/seer/teach/common/enums/ResultCodeEnum.java
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@ -316,7 +316,10 @@ public enum ResultCodeEnum {
// 富文本模板相关错误码 // 富文本模板相关错误码
RICH_TEXT_TEMPLATE_PREVIEW_FAILED(1100418, "预览失败"), RICH_TEXT_TEMPLATE_PREVIEW_FAILED(1100418, "预览失败"),
RICH_TEXT_TEMPLATE_CONVERT_FAILED(1100419, "转换失败"); RICH_TEXT_TEMPLATE_CONVERT_FAILED(1100419, "转换失败"),
AI_MODEL_NOT_FOUND(12000, "未找到模型");
private int code; private int code;
private String msg; private String msg;

5
seer-common/common/src/main/java/com/seer/teach/common/constants/CommonConstant.java
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@ -70,4 +70,9 @@ public interface CommonConstant {
* 任务锁前缀 * 任务锁前缀
*/ */
String TASK_CANCEL_PREFIX = "ai_task_cancel:"; String TASK_CANCEL_PREFIX = "ai_task_cancel:";
/**
* 启用
*/
Integer ENABLE = 1;
} }

59
seer-dependencies/pom.xml
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@ -15,8 +15,8 @@
<spring-cloud-openfeign.version>4.3.0</spring-cloud-openfeign.version> <spring-cloud-openfeign.version>4.3.0</spring-cloud-openfeign.version>
<spring-cloud-alibaba.version>2025.0.0.0</spring-cloud-alibaba.version> <spring-cloud-alibaba.version>2025.0.0.0</spring-cloud-alibaba.version>
<spring-ai.version>2.0.0-SNAPSHOT</spring-ai.version> <spring-ai.version>1.1.2</spring-ai.version>
<spring-ai-alibaba.version>1.0.0-M6.1</spring-ai-alibaba.version> <spring-ai-alibaba.version>1.1.0.0-RC2</spring-ai-alibaba.version>
<!-- 认证 --> <!-- 认证 -->
@ -68,7 +68,7 @@
<guava.version>33.5.0-jre</guava.version> <guava.version>33.5.0-jre</guava.version>
<!-- 异步处理 --> <!-- 异步处理 -->
<spring-retry.version>1.2.5.RELEASE</spring-retry.version> <spring-retry.version>2.0.8</spring-retry.version>
<!-- 接口文档 --> <!-- 接口文档 -->
<springdoc-openapi.version>2.8.14</springdoc-openapi.version> <springdoc-openapi.version>2.8.14</springdoc-openapi.version>
@ -186,6 +186,13 @@
<scope>import</scope> <scope>import</scope>
</dependency> </dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>${spring-ai.version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
<!-- Lombok --> <!-- Lombok -->
<dependency> <dependency>
@ -646,6 +653,52 @@
</exclusions> </exclusions>
</dependency> </dependency>
<dependency>
<groupId>com.alibaba.cloud.ai</groupId>
<artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
<version>${spring-ai-alibaba.version}</version>
</dependency>
<dependency>
<groupId>com.alibaba.cloud.ai</groupId>
<artifactId>spring-ai-alibaba-dashscope</artifactId>
<version>${spring-ai-alibaba.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-model-deepseek</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-deepseek</artifactId>
<version>${spring-ai.version}</version>
<scope>compile</scope>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai</artifactId>
<version>${spring-ai.version}</version>
<scope>compile</scope>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-model-ollama</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<groupId>com.alibaba.cloud.ai</groupId>
<artifactId>spring-ai-alibaba-agent-framework</artifactId>
<version>${spring-ai-alibaba.version}</version>
</dependency>
<!-- 测试依赖 --> <!-- 测试依赖 -->
<dependency> <dependency>
<groupId>org.springframework.boot</groupId> <groupId>org.springframework.boot</groupId>

2
seer-gateway/pom.xml
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@ -21,7 +21,7 @@
<dependency> <dependency>
<groupId>org.springframework.cloud</groupId> <groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-gateway</artifactId> <artifactId>spring-cloud-starter-gateway-server-webflux</artifactId>
</dependency> </dependency>
<dependency> <dependency>

39
seer-gateway/src/main/resources/application.yml
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@ -32,6 +32,45 @@ spring:
server-addr: 192.168.0.39:8848 # 配置中心地址 server-addr: 192.168.0.39:8848 # 配置中心地址
file-extension: yaml # 配置文件后缀（yaml/properties） file-extension: yaml # 配置文件后缀（yaml/properties）
namespace: ${spring.profiles.active} namespace: ${spring.profiles.active}
gateway:
discovery:
locator:
enabled: true # 开启通过服务发现创建路由
lower-case-service-id: true # 服务名小写
routes:
- id: seer-admin # 路由的编号
uri: lb://seer-admin
predicates:
- Path=/seer/admin/**
- id: seer-teacher
uri: lb://seer-teacher
predicates:
- Path=/seer/teacher/**
- id: seer-iot
uri: lb://seer-iot
predicates:
- Path=/seer/iot/**
- id: seer-mall
uri: lb://seer-mall
predicates:
- Path=/seer/mall/**
- id: seer-pay
uri: lb://seer-pay
predicates:
- Path=/seer/pay/**
- id: seer-user
uri: lb://seer-user
predicates:
- Path=/seer/user/**
- id: seer-mp
uri: lb://seer-mp
predicates:
- Path=/seer/mp/**
- id: seer-open-api
uri: lb://seer-open-api
predicates:
- Path=/seer/open/rest/**
config: config:
import: import:
- optional:nacos:${spring.application.name}-${spring.profiles.active}.yaml - optional:nacos:${spring.application.name}-${spring.profiles.active}.yaml

4
seer-gateway/src/main/resources/logback-dev.xml
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@ -78,12 +78,12 @@
<logger name="org.springframework.data.redis" level="error"/> <logger name="org.springframework.data.redis" level="error"/>
<logger name="com.alibaba.nacos.shaded.io.grpc" level="error"/> <logger name="com.alibaba.nacos.shaded.io.grpc" level="error"/>
<logger name="com.alibaba.nacos.client.naming" level="WARN"/> <logger name="com.alibaba.nacos.client.naming" level="WARN"/>
<logger name="org.springframework.cloud.gateway.route" level="error"/> <logger name="org.springframework.cloud.gateway.route" level="debug"/>
<logger name="org.springframework.core.env" level="error"/> <logger name="org.springframework.core.env" level="error"/>
<logger name="java.util.concurrent" level="error"/> <logger name="java.util.concurrent" level="error"/>
<!--将整个项目的日志设置为debug级别--> <!--将整个项目的日志设置为debug级别-->
<root level="info"> <root level="debug">
<appender-ref ref="FILE_ERROR"/> <appender-ref ref="FILE_ERROR"/>
<appender-ref ref="FILE_WARN"/> <appender-ref ref="FILE_WARN"/>
<appender-ref ref="FILE_INFO"/> <appender-ref ref="FILE_INFO"/>

101
seer-teacher/pom.xml
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@ -19,105 +19,6 @@
<module>seer-teacher-service-bootstrap</module> <module>seer-teacher-service-bootstrap</module>
<module>seer-teacher-api</module> <module>seer-teacher-api</module>
<module>seer-teacher-service-admin</module> <module>seer-teacher-service-admin</module>
<module>seer-teacher-ai</module>
</modules> </modules>
<dependencies>
<!--繁体转简体-->
<dependency>
<groupId>com.github.houbb</groupId>
<artifactId>opencc4j</artifactId>
<version>1.6.0</version>
</dependency>
<!--MinIO依赖-->
<dependency>
<groupId>io.minio</groupId>
<artifactId>minio</artifactId>
<version>8.5.1</version>
</dependency>
<!--protobaffer-->
<dependency>
<groupId>com.google.protobuf</groupId>
<artifactId>protobuf-java</artifactId>
<version>4.30.2</version>
</dependency>
<!-- 加密库 -->
<dependency>
<groupId>commons-io</groupId>
<artifactId>commons-io</artifactId>
</dependency>
<dependency>
<groupId>commons-codec</groupId>
<artifactId>commons-codec</artifactId>
</dependency>
<!--MybatisPlus-->
<dependency>
<groupId>com.baomidou</groupId>
<artifactId>mybatis-plus-spring-boot3-starter</artifactId>
</dependency>
<!-- 代码自动生成器依赖-->
<dependency>
<groupId>com.baomidou</groupId>
<artifactId>mybatis-plus-generator</artifactId>
</dependency>
<!--代码生成器需要的引擎-->
<dependency>
<groupId>org.apache.velocity</groupId>
<artifactId>velocity-engine-core</artifactId>
</dependency>
<!--AOP编程jar包-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-aop</artifactId>
</dependency>
<!-- fastjson2 -->
<dependency>
<groupId>com.alibaba.fastjson2</groupId>
<artifactId>fastjson2</artifactId>
</dependency>
<!--参数校验-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-validation</artifactId>
</dependency>
<dependency>
<groupId>javax.validation</groupId>
<artifactId>validation-api</artifactId>
</dependency>
<!-- Sa-Token 权限认证，在线文档：https://sa-token.cc -->
<dependency>
<groupId>cn.dev33</groupId>
<artifactId>sa-token-spring-boot3-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.retry</groupId>
<artifactId>spring-retry</artifactId>
</dependency>
<!-- IP地址检索 -->
<dependency>
<groupId>org.lionsoul</groupId>
<artifactId>ip2region</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
</project> </project>

56
seer-teacher/seer-teacher-ai/pom.xml Normal file
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@ -0,0 +1,56 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>com.seer.teach</groupId>
<artifactId>seer-teacher</artifactId>
<version>1.0.0-SNAPSHOT</version>
</parent>
<artifactId>seer-teacher-ai</artifactId>
<dependencies>
<dependency>
<groupId>${project.groupId}</groupId>
<artifactId>seer-teacher-service</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.retry</groupId>
<artifactId>spring-retry</artifactId>
</dependency>
<dependency>
<groupId>com.alibaba.cloud.ai</groupId>
<artifactId>spring-ai-alibaba-dashscope</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai</artifactId>
<scope>compile</scope>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-deepseek</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-model-ollama</artifactId>
</dependency>
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-observation</artifactId>
<version>1.15.7</version>
<scope>compile</scope>
</dependency>
</dependencies>
</project>

12
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/AiModelClientFactory.java Normal file
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@ -0,0 +1,12 @@
package com.seer.teach.ai.client;
import com.seer.teach.ai.client.model.AiModelClient;
/**
*
*/
public interface AiModelClientFactory {
AiModelClient getClient(String platform);
}

43
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/AiModelClientFactoryImpl.java Normal file
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@ -0,0 +1,43 @@
package com.seer.teach.ai.client;
import cn.hutool.core.collection.CollectionUtil;
import com.seer.teach.ai.client.model.AiModelClient;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Service;
import java.util.List;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
/**
* 平台模型管理器接口
* 定义了平台特定的模型管理功能
*
* @since 2025-12-25
*/
@Slf4j
@Service
public class AiModelClientFactoryImpl implements AiModelClientFactory {
private final Map<String, AiModelClient> serviceMap = new ConcurrentHashMap<>();
public AiModelClientFactoryImpl(List<AiModelClient> platformServices){
if(CollectionUtil.isEmpty(platformServices)){
return;
}
for (AiModelClient platform : platformServices) {
register(platform);
}
}
public void register(AiModelClient platformManager) {
String platformName = platformManager.getPlatformName();
serviceMap.put(platformName, platformManager);
}
@Override
public AiModelClient getClient(String platform) {
return serviceMap.get(platform);
}
}

45
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/model/AbstractAiModelClient.java Normal file
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@ -0,0 +1,45 @@
package com.seer.teach.ai.client.model;
import io.micrometer.observation.ObservationRegistry;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.model.tool.DefaultToolExecutionEligibilityPredicate;
import org.springframework.ai.model.tool.ToolCallingManager;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.retry.support.RetryTemplate;
import org.springframework.web.client.ResponseErrorHandler;
import org.springframework.web.client.RestClient;
import org.springframework.web.reactive.function.client.WebClient;
/**
* 平台模型管理器抽象基类
* 提供通用的模型管理功能实现，减少代码重复
*
* @author Captain
* @since 2025-12-26
*/
@Slf4j
public abstract class AbstractAiModelClient implements AiModelClient {
@Autowired(required = false)
protected ResponseErrorHandler responseErrorHandler;
@Autowired(required = false)
@Qualifier("aiRestClient")
protected RestClient.Builder restClientBuilder;
@Autowired(required = false)
@Qualifier("aiWebClient")
protected WebClient.Builder webClientBuilder;
@Autowired
protected RetryTemplate retryTemplate;
@Autowired
protected ToolCallingManager toolCallingManager;
protected ObservationRegistry observationRegistry = ObservationRegistry.create();
protected final DefaultToolExecutionEligibilityPredicate toolExecutionEligibilityPredicate = new DefaultToolExecutionEligibilityPredicate();
}

66
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/model/AiModelClient.java Normal file
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@ -0,0 +1,66 @@
package com.seer.teach.ai.client.model;
import com.seer.teach.ai.client.model.config.ModelConfig;
import org.springframework.ai.audio.tts.TextToSpeechModel;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.image.ImageModel;
import org.springframework.stereotype.Service;
import java.util.Map;
import java.util.Optional;
/**
*
* @author Captain
* @since 2025-12-25
*/
@Service
public interface AiModelClient {
String getPlatformName();
/**
* 获取聊天模型
*
* @param modelConfig 模型配置
* @return 大语言模型实例的Optional包装
*/
default Optional<ChatModel> createChatModel(ModelConfig modelConfig){
return Optional.empty();
}
default Optional<ChatOptions> createChatOptions(Map<String, Object> options){
return Optional.empty();
}
/**
* 获取图像模型
*/
default Optional<ImageModel> createImageModel(ModelConfig modelConfig){
return Optional.empty();
}
/**
* 获取文本转语音模型（Text To Speech Model）
* 用于将文本转换为语音输出，支持多种平台
*
* @param modelConfig 模型配置
* @return 文本转语音模型实例的Optional包装
*/
default Optional<TextToSpeechModel> createTextToSpeechModel(ModelConfig modelConfig) {
return Optional.empty();
}
/**
* 获取嵌入模型（Embedding Model）
* 用于将文本转换为向量表示，支持多种平台
*
* @param modelConfig 模型配置
* @return 嵌入模型实例的Optional包装
*/
default Optional<EmbeddingModel> createEmbeddingModel(ModelConfig modelConfig) {
return Optional.empty();
}
}

99
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/model/config/DashScopeClientConfig.java Normal file
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@ -0,0 +1,99 @@
package com.seer.teach.ai.client.model.config;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.datatype.jsr310.JavaTimeModule;
import lombok.extern.slf4j.Slf4j;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.http.HttpRequest;
import org.springframework.http.client.ClientHttpRequestExecution;
import org.springframework.http.client.ClientHttpRequestInterceptor;
import org.springframework.http.client.ClientHttpResponse;
import org.springframework.http.codec.json.Jackson2JsonDecoder;
import org.springframework.http.codec.json.Jackson2JsonEncoder;
import org.springframework.http.converter.json.Jackson2ObjectMapperBuilder;
import org.springframework.http.converter.json.MappingJackson2HttpMessageConverter;
import org.springframework.web.client.RestClient;
import org.springframework.web.reactive.function.client.ExchangeFilterFunction;
import org.springframework.web.reactive.function.client.WebClient;
import reactor.core.publisher.Mono;
import java.io.IOException;
import java.nio.charset.StandardCharsets;
/**
* DashScope API 配置类
* 用于配置restClient以正确处理聊天完成请求
*/
@Slf4j
@Configuration
public class DashScopeClientConfig {
/**
* 创建用于DashScope API的RestClient
*/
@Bean
public RestClient aiRestClient() {
ObjectMapper objectMapper = Jackson2ObjectMapperBuilder.json()
.modules(new JavaTimeModule())
.build();
MappingJackson2HttpMessageConverter converter = new MappingJackson2HttpMessageConverter(objectMapper);
return RestClient.builder()
.requestInterceptor(new LoggingInterceptor())
.messageConverters(converters -> converters.add(converter))
.build();
}
/**
* 创建用于DashScope API的WebClient并启用日志
*/
@Bean
public WebClient aiWebClient() {
ObjectMapper objectMapper = Jackson2ObjectMapperBuilder.json()
.modules(new JavaTimeModule())
.build();
return WebClient.builder()
.codecs(configurer -> configurer.defaultCodecs().jackson2JsonDecoder(new Jackson2JsonDecoder(objectMapper)))
.codecs(configurer -> configurer.defaultCodecs().jackson2JsonEncoder(new Jackson2JsonEncoder(objectMapper)))
.filter(ExchangeFilterFunction.ofRequestProcessor(clientRequest -> {
log.info("Request: {} {}", clientRequest.method(), clientRequest.url());
clientRequest.headers().forEach((name, values) ->
values.forEach(value -> log.info("{}={}", name, value)));
return Mono.just(clientRequest);
}))
.filter(ExchangeFilterFunction.ofResponseProcessor(clientResponse -> {
log.info("Response Status: {}", clientResponse.statusCode());
clientResponse.headers().asHttpHeaders().forEach((name, values) ->
values.forEach(value -> log.info("{}={}", name, value)));
return Mono.just(clientResponse);
}))
.build();
}
public static class LoggingInterceptor implements ClientHttpRequestInterceptor {
@Override
public ClientHttpResponse intercept(
HttpRequest request,
byte[] body,
ClientHttpRequestExecution execution) throws IOException {
// 记录请求信息
log.info("HTTP请求方法: {}", request.getMethod());
log.info("HTTP请求URL: {}", request.getURI());
log.info("HTTP请求头: {}", request.getHeaders());
if (body.length > 0) {
log.info("HTTP请求体: {}", new String(body, StandardCharsets.UTF_8));
}
// 执行请求
ClientHttpResponse response = execution.execute(request, body);
return response;
}
}
}

13
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/model/config/ModelConfig.java Normal file
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@ -0,0 +1,13 @@
package com.seer.teach.ai.client.model.config;
import lombok.Builder;
import lombok.Data;
@Builder
@Data
public class ModelConfig {
private String model;
private String apiKey;
private String url;
}

177
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/model/dashscope/DashScopeModelClient.java Normal file
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@ -0,0 +1,177 @@
package com.seer.teach.ai.client.model.dashscope;
import com.alibaba.cloud.ai.dashscope.api.DashScopeApi;
import com.alibaba.cloud.ai.dashscope.api.DashScopeAudioSpeechApi;
import com.alibaba.cloud.ai.dashscope.api.DashScopeImageApi;
import com.alibaba.cloud.ai.dashscope.audio.DashScopeAudioSpeechModel;
import com.alibaba.cloud.ai.dashscope.audio.DashScopeAudioSpeechOptions;
import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel;
import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions;
import com.alibaba.cloud.ai.dashscope.embedding.DashScopeEmbeddingModel;
import com.alibaba.cloud.ai.dashscope.image.DashScopeImageModel;
import com.alibaba.cloud.ai.dashscope.image.DashScopeImageOptions;
import com.seer.teach.ai.client.model.AbstractAiModelClient;
import com.seer.teach.ai.client.model.config.ModelConfig;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.audio.tts.TextToSpeechModel;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.image.ImageModel;
import org.springframework.stereotype.Component;
import java.util.Map;
import java.util.Optional;
/**
* DashScope平台模型管理器
* 专门负责DashScope平台的AI模型管理
* 使用配置属性进行更灵活的模型初始化
*
* @author Captain
* @since 2025-12-25
*/
@Slf4j
@Component
public class DashScopeModelClient extends AbstractAiModelClient {
@Override
public String getPlatformName() {
return "aliyun_bailian";
}
@Override
public Optional<ChatModel> createChatModel(ModelConfig modelConfig) {
DashScopeChatOptions chatOptions = DashScopeChatOptions.builder()
.withModel(modelConfig.getModel())
.build();
DashScopeApi dashScopeApi = createDashScopeApi(modelConfig.getApiKey(), modelConfig.getUrl());
return Optional.of(DashScopeChatModel.builder()
.dashScopeApi(dashScopeApi)
.retryTemplate(retryTemplate)
.toolCallingManager(toolCallingManager)
.defaultOptions(chatOptions)
.observationRegistry(observationRegistry)
.toolExecutionEligibilityPredicate(toolExecutionEligibilityPredicate)
.build());
}
@Override
public Optional<ChatOptions> createChatOptions(Map<String, Object> options) {
DashScopeChatOptions.DashScopeChatOptionsBuilder builder = DashScopeChatOptions.builder();
for (Map.Entry<String, Object> entry : options.entrySet()) {
String key = entry.getKey();
Object value = entry.getValue();
if (value == null) {
continue;
}
switch (key) {
case "temperature":
builder.withTemperature(((Number) value).doubleValue());
break;
case "maxTokens":
builder.withMaxToken(((Number) value).intValue());
break;
case "enableSearch":
builder.withEnableSearch((Boolean) value);
break;
case "seed":
builder.withSeed(((Number) value).intValue());
break;
case "topP":
builder.withTopP(((Number) value).doubleValue());
break;
case "topK":
builder.withTopK(((Number) value).intValue());
break;
case "enableThinking":
builder.withEnableThinking((Boolean) value);
break;
case "repetitionPenalty":
builder.withRepetitionPenalty(((Number) value).doubleValue());
default:
break;
}
}
DashScopeChatOptions chatOptions = builder.build();
return Optional.of(chatOptions);
}
@Override
public Optional<ImageModel> createImageModel(ModelConfig modelConfig) {
DashScopeImageOptions imageOptions = DashScopeImageOptions.builder()
.withModel(modelConfig.getModel())
.build();
DashScopeImageApi imageApi = DashScopeImageApi.builder()
.apiKey(modelConfig.getApiKey())
.baseUrl(modelConfig.getUrl())
.restClientBuilder(restClientBuilder)
.responseErrorHandler(responseErrorHandler)
.build();
return Optional.of(new DashScopeImageModel(imageApi, imageOptions, retryTemplate));
}
@Override
public Optional<TextToSpeechModel> createTextToSpeechModel(ModelConfig modelConfig) {
try {
DashScopeAudioSpeechApi audioSpeechApi = new DashScopeAudioSpeechApi(modelConfig.getApiKey(), modelConfig.getUrl());
DashScopeAudioSpeechOptions options = DashScopeAudioSpeechOptions.builder()
.model(modelConfig.getModel())
.voice("longyingxiao")
.build();
DashScopeAudioSpeechModel speechSynthesisModel = new DashScopeAudioSpeechModel(audioSpeechApi, options, retryTemplate);
return Optional.of(speechSynthesisModel);
} catch (Exception e) {
log.error("创建DashScope语音合成模型失败", e);
return Optional.empty();
}
}
@Override
public Optional<EmbeddingModel> createEmbeddingModel(ModelConfig modelConfig) {
try {
DashScopeApi dashScopeApi = createDashScopeApi(modelConfig.getApiKey(), modelConfig.getUrl());
DashScopeEmbeddingModel embeddingModel = new DashScopeEmbeddingModel(dashScopeApi);
return Optional.of(embeddingModel);
} catch (Exception e) {
log.error("创建DashScope嵌入模型失败", e);
return Optional.empty();
}
}
/**
* 创建DashScope API实例
*/
private DashScopeApi createDashScopeApi(String apiKey, String completionsPath) {
DashScopeApi.Builder builder = DashScopeApi.builder()
.apiKey(apiKey)
.baseUrl("https://dashscope.aliyuncs.com");
// 如果有可用的客户端构建器，添加它们
if (webClientBuilder != null) {
builder.webClientBuilder(webClientBuilder);
}
if (restClientBuilder != null) {
builder.restClientBuilder(restClientBuilder);
}
if (responseErrorHandler != null) {
builder.responseErrorHandler(responseErrorHandler);
}
return builder.build();
}
private DashScopeImageApi createDashScopeImageApi(String apiKey, String baseUrl) {
return DashScopeImageApi.builder()
.apiKey(apiKey)
.baseUrl(baseUrl)
.restClientBuilder(restClientBuilder)
.responseErrorHandler(responseErrorHandler)
.build();
}
}

57
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/model/local/LocalModelClient.java Normal file
View File

@ -0,0 +1,57 @@
package com.seer.teach.ai.client.model.local;
import com.seer.teach.ai.client.model.AbstractAiModelClient;
import com.seer.teach.ai.client.model.config.ModelConfig;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.ai.ollama.api.OllamaApi;
import org.springframework.ai.ollama.api.OllamaChatOptions;
import org.springframework.stereotype.Component;
import java.util.Map;
import java.util.Optional;
/**
* 本地模型管理器
* 专门负责Ollama等本地AI模型管理
*
* @author Captain
* @since 2025-12-26
*/
@Component
public class LocalModelClient extends AbstractAiModelClient {
@Override
public String getPlatformName() {
return "local";
}
@Override
public Optional<ChatModel> createChatModel(ModelConfig modelConfig) {
OllamaChatOptions chatOptions = OllamaChatOptions.builder()
.model(modelConfig.getModel())
.build();
OllamaApi ollamaApi = OllamaApi.builder()
.baseUrl(modelConfig.getUrl())
.restClientBuilder(restClientBuilder)
.webClientBuilder(webClientBuilder)
.responseErrorHandler(responseErrorHandler)
.build();
return Optional.of(OllamaChatModel.builder()
.ollamaApi(ollamaApi)
.defaultOptions(chatOptions)
.retryTemplate(retryTemplate)
.toolCallingManager(toolCallingManager)
.observationRegistry(observationRegistry)
.toolExecutionEligibilityPredicate(toolExecutionEligibilityPredicate)
.build());
}
@Override
public Optional<ChatOptions> createChatOptions(Map<String, Object> options) {
return Optional.empty();
}
}

157
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/client/model/openai/OpenAIModelClient.java Normal file
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@ -0,0 +1,157 @@
package com.seer.teach.ai.client.model.openai;
import com.seer.teach.ai.client.model.AbstractAiModelClient;
import com.seer.teach.ai.client.model.config.ModelConfig;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.audio.tts.TextToSpeechModel;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.image.ImageModel;
import org.springframework.ai.model.SimpleApiKey;
import org.springframework.ai.openai.OpenAiAudioSpeechModel;
import org.springframework.ai.openai.OpenAiChatModel;
import org.springframework.ai.openai.OpenAiChatOptions;
import org.springframework.ai.openai.OpenAiEmbeddingModel;
import org.springframework.ai.openai.OpenAiImageModel;
import org.springframework.ai.openai.OpenAiImageOptions;
import org.springframework.ai.openai.api.OpenAiApi;
import org.springframework.ai.openai.api.OpenAiAudioApi;
import org.springframework.ai.openai.api.OpenAiImageApi;
import org.springframework.stereotype.Component;
import java.util.Map;
import java.util.Objects;
import java.util.Optional;
/**
* OpenAI平台模型管理器
* 专门负责OpenAI平台的AI模型管理
*
* @author Captain
* @since 2025-12-26
*/
@Slf4j
@Component
public class OpenAIModelClient extends AbstractAiModelClient {
@Override
public String getPlatformName() {
return "openai";
}
@Override
public Optional<ChatModel> createChatModel(ModelConfig modelConfig) {
OpenAiChatOptions chatOptions = OpenAiChatOptions.builder()
.model(modelConfig.getModel())
.build();
OpenAiApi openAiApi = createOpenAiApi(modelConfig.getApiKey(), modelConfig.getUrl());
return Optional.of(new OpenAiChatModel(openAiApi, chatOptions, toolCallingManager, retryTemplate, observationRegistry));
}
@Override
public Optional<ChatOptions> createChatOptions(Map<String, Object> options) {
OpenAiChatOptions.Builder builder = OpenAiChatOptions.builder();
builder.streamUsage(true);
for (Map.Entry<String, Object> entry : options.entrySet()) {
String key = entry.getKey();
Object value = entry.getValue();
if (Objects.isNull(value)) {
continue;
}
switch (key) {
case "temperature":
builder.temperature(((Number) value).doubleValue());
break;
case "maxTokens":
builder.maxTokens(((Number) value).intValue());
break;
case "maxCompletionToken":
builder.maxCompletionTokens(((Number) value).intValue());
break;
case "topLogprobs":
builder.topLogprobs(((Number) value).intValue());
break;
case "logprobs":
builder.logprobs((Boolean) value);
break;
case "N":
case "n":
builder.N(((Number) value).intValue());
break;
case "reasoningEffort":
builder.reasoningEffort(value.toString());
break;
case "topP":
case "top_p":
builder.topP(((Number) value).doubleValue());
break;
case "frequencyPenalty":
builder.frequencyPenalty(((Number) value).doubleValue());
break;
case "presencePenalty":
builder.presencePenalty(((Number) value).doubleValue());
break;
default:
break;
}
}
return Optional.of(builder.build());
}
@Override
public Optional<ImageModel> createImageModel(ModelConfig modelConfig) {
OpenAiImageOptions imageOptions = OpenAiImageOptions.builder()
.model(modelConfig.getModel())
.build();
OpenAiImageApi imageOpenAiApi = OpenAiImageApi.builder()
.baseUrl(modelConfig.getUrl())
.apiKey(new SimpleApiKey(modelConfig.getApiKey()))
.restClientBuilder(restClientBuilder)
.responseErrorHandler(responseErrorHandler)
.build();
return Optional.of(new OpenAiImageModel(imageOpenAiApi, imageOptions, retryTemplate, observationRegistry));
}
@Override
public Optional<TextToSpeechModel> createTextToSpeechModel(ModelConfig modelConfig) {
try {
OpenAiAudioApi audioApi = OpenAiAudioApi.builder()
.baseUrl(modelConfig.getUrl())
.apiKey(new SimpleApiKey(modelConfig.getApiKey()))
.restClientBuilder(restClientBuilder)
.responseErrorHandler(responseErrorHandler)
.build();
TextToSpeechModel textToSpeechModel = new OpenAiAudioSpeechModel(audioApi);
return Optional.of(textToSpeechModel);
} catch (Exception e) {
log.error("创建OpenAI文本转语音模型失败", e);
return Optional.empty();
}
}
@Override
public Optional<EmbeddingModel> createEmbeddingModel(ModelConfig modelConfig) {
try {
OpenAiApi openAiApi = createOpenAiApi(modelConfig.getApiKey(), modelConfig.getUrl());
EmbeddingModel embeddingModel = new OpenAiEmbeddingModel(openAiApi);
return Optional.of(embeddingModel);
} catch (Exception e) {
log.error("创建OpenAI嵌入模型失败", e);
return Optional.empty();
}
}
private OpenAiApi createOpenAiApi(String apiKey, String baseUrl) {
return OpenAiApi.builder()
.baseUrl(baseUrl)
.apiKey(new SimpleApiKey(apiKey))
.restClientBuilder(restClientBuilder)
.webClientBuilder(webClientBuilder).build();
}
}

100
seer-teacher/seer-teacher-ai/src/main/java/com/seer/teach/ai/service/AiChatModelService.java Normal file
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@ -0,0 +1,100 @@
package com.seer.teach.ai.service;
import cn.hutool.core.bean.BeanUtil;
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.seer.teach.ai.client.AiModelClientFactory;
import com.seer.teach.ai.client.model.AiModelClient;
import com.seer.teach.ai.client.model.config.ModelConfig;
import com.seer.teach.common.enums.ResultCodeEnum;
import com.seer.teach.common.exception.CommonException;
import com.seer.teach.common.utils.AssertUtils;
import com.seer.teach.teacher.module.entity.AiApiKeyEntity;
import com.seer.teach.teacher.module.entity.AiModelEntity;
import com.seer.teach.teacher.module.entity.AiScenarioConfigEntity;
import com.seer.teach.teacher.service.IAiApiKeyService;
import com.seer.teach.teacher.service.IAiModelService;
import com.seer.teach.teacher.service.IAiScenarioConfigService;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.stereotype.Service;
import reactor.core.publisher.Flux;
import java.util.List;
import java.util.Objects;
import java.util.Optional;
@Slf4j
@Service
@RequiredArgsConstructor
public class AiChatModelService {
private final IAiScenarioConfigService aiScenarioConfigService;
private final IAiApiKeyService aiApiKeyService;
private final IAiModelService aiModelService;
private final AiModelClientFactory aiModelClientFactory;
public ChatResponse chatMessage(String scenarioCode, Object prompt){
AiScenarioConfigEntity scenarioConfig = aiScenarioConfigService.getOneByScenarioCode(scenarioCode);
log.info("scenarioConfig:{}", scenarioConfig);
AssertUtils.notNull(scenarioConfig, ResultCodeEnum.SCENARIO_NOT_FOUND);
AiModelClient client = aiModelClientFactory.getClient(scenarioConfig.getPlatform());
ModelConfig modelConfig = getModelConfig(scenarioConfig);
ChatModel chatModel = client.createChatModel(modelConfig).orElseThrow(() -> new CommonException(ResultCodeEnum.AI_MODEL_NOT_FOUND));
Optional<ChatOptions> options = client.createChatOptions(BeanUtil.beanToMap(scenarioConfig));
return chatModel.call(new Prompt(prompt.toString(), options.orElse(null)));
}
public Flux<ChatResponse> chatStream(String scenarioCode, Object params){
AiScenarioConfigEntity scenarioConfig = aiScenarioConfigService.getOneByScenarioCode(scenarioCode);
log.info("chatStream scenarioConfig:{}", scenarioConfig);
AssertUtils.notNull(scenarioConfig, ResultCodeEnum.SCENARIO_NOT_FOUND);
AiModelClient client = aiModelClientFactory.getClient(scenarioConfig.getPlatform());
ModelConfig modelConfig = getModelConfig(scenarioConfig);
ChatModel chatModel = client.createChatModel(modelConfig).orElseThrow(() -> new CommonException(ResultCodeEnum.AI_MODEL_NOT_FOUND));
Optional<ChatOptions> options = client.createChatOptions(BeanUtil.beanToMap(scenarioConfig));
Prompt prompt = new Prompt(params.toString(), options.orElse(null));
return chatModel.stream(prompt);
}
private ModelConfig getModelConfig(AiScenarioConfigEntity scenarioConfig) {
AiModelEntity module = aiModelService.getById(scenarioConfig.getModuleId());
AiApiKeyEntity apiKey = getApiKey(scenarioConfig);
return ModelConfig.builder()
.url(module.getUrl()).apiKey(apiKey.getApiKey()).model(module.getModelIdentifier()).build();
}
private AiApiKeyEntity getApiKey(AiScenarioConfigEntity aiScenarioConfig) {
List<AiApiKeyEntity> aiApiKeyList = aiApiKeyService.list(new LambdaQueryWrapper<>(AiApiKeyEntity.class).eq(AiApiKeyEntity::getPlatform, aiScenarioConfig.getPlatform()));
AiApiKeyEntity apiKey = null;
Optional<AiApiKeyEntity> any = aiApiKeyList.stream().filter(aiApiKey -> Objects.nonNull(aiScenarioConfig.getApiKeyId()) && aiScenarioConfig.getApiKeyId().intValue() == aiApiKey.getId()).findAny();
if (any.isPresent()) {
apiKey = any.get();
}
if (Objects.isNull(apiKey)) {
Optional<AiApiKeyEntity> apiKeyOptional = aiApiKeyList.stream().filter(aiApiKey -> Objects.nonNull(aiApiKey.getIsDefault()) && aiApiKey.getIsDefault() == 1).findAny();
if (apiKeyOptional.isPresent()) {
apiKey = apiKeyOptional.get();
}
}
return apiKey;
}
}

6
seer-teacher/seer-teacher-common/pom.xml
View File

@ -30,5 +30,11 @@
<artifactId>spring-webflux</artifactId> <artifactId>spring-webflux</artifactId>
</dependency> </dependency>
<dependency>
<groupId>org.springframework</groupId>
<artifactId>spring-webmvc</artifactId>
</dependency>
</dependencies> </dependencies>
</project> </project>

6
seer-teacher/seer-teacher-service-admin/pom.xml
View File

@ -38,6 +38,12 @@
<version>${project.version}</version> <version>${project.version}</version>
</dependency> </dependency>
<dependency>
<groupId>${project.groupId}</groupId>
<artifactId>seer-teacher-ai</artifactId>
<version>${project.version}</version>
</dependency>
<dependency> <dependency>
<groupId>com.squareup.okhttp3</groupId> <groupId>com.squareup.okhttp3</groupId>
<artifactId>okhttp</artifactId> <artifactId>okhttp</artifactId>

11
seer-teacher/seer-teacher-service-admin/src/main/java/com/seer/teach/admin/service/impl/AbstractGenerationService.java
View File

@ -2,11 +2,14 @@ package com.seer.teach.admin.service.impl;
import com.fasterxml.jackson.databind.JsonNode; import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper; import com.fasterxml.jackson.databind.ObjectMapper;
import com.seer.teach.ai.service.AiChatModelService;
import com.seer.teach.common.constants.CommonConstant; import com.seer.teach.common.constants.CommonConstant;
import com.seer.teach.common.entity.BaseEntity; import com.seer.teach.common.entity.BaseEntity;
import com.seer.teach.teacher.service.AiModelCallService; import com.seer.teach.teacher.service.AiModelCallService;
import com.seer.teach.teacher.service.platform.LlmResponse; import com.seer.teach.teacher.service.platform.LlmResponse;
import lombok.extern.slf4j.Slf4j; import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.model.Generation;
import org.springframework.beans.factory.annotation.Autowired; import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.StringRedisTemplate; import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.transaction.support.TransactionTemplate; import org.springframework.transaction.support.TransactionTemplate;
@ -16,6 +19,7 @@ import java.util.ArrayList;
import java.util.Collections; import java.util.Collections;
import java.util.List; import java.util.List;
import java.util.Map; import java.util.Map;
import java.util.Objects;
import java.util.function.Function; import java.util.function.Function;
/** /**
@ -41,6 +45,9 @@ public abstract class AbstractGenerationService<T, R, E extends BaseEntity> {
@Autowired @Autowired
protected TransactionTemplate transactionTemplate; protected TransactionTemplate transactionTemplate;
@Autowired
protected AiChatModelService chatModelService;
/** /**
* 检查当前线程是否被中断 * 检查当前线程是否被中断
* *
@ -78,6 +85,10 @@ public abstract class AbstractGenerationService<T, R, E extends BaseEntity> {
*/ */
protected LlmResponse callLLM(String scenarioCode, String prompt, Map<String, Object> params, Integer userId) { protected LlmResponse callLLM(String scenarioCode, String prompt, Map<String, Object> params, Integer userId) {
log.info("调用大模型，场景编码: {}, 提示词长度: {}", scenarioCode, prompt.length()); log.info("调用大模型，场景编码: {}, 提示词长度: {}", scenarioCode, prompt.length());
//ChatResponse chatResponse = chatModelService.chatMessage(scenarioCode, prompt);
LlmResponse response = new LlmResponse();
//Generation result = chatResponse.getResult();
return aiModelCallService.callModel(scenarioCode, prompt, params, userId); return aiModelCallService.callModel(scenarioCode, prompt, params, userId);
} }

797
seer-teacher/seer-teacher-service-admin/src/main/java/com/seer/teach/admin/util/PromptBuilder.java
View File

@ -31,41 +31,38 @@ public class PromptBuilder {
public static String buildPromptForQuestionGeneration(ExampleQuestionsEntity exampleQuestion, public static String buildPromptForQuestionGeneration(ExampleQuestionsEntity exampleQuestion,
KnowledgePointEntity knowledgePoint, KnowledgePointEntity knowledgePoint,
Integer count) { Integer count) {
StringBuilder prompt = new StringBuilder(); String optionsPart = ExampleQuestionTypesEnum.CHOICE.getCode().equals(exampleQuestion.getType()) ?
" - options: 选项数组（仅选择题需要，每个选项包含content和sort字段）\n\n" : "";
prompt.append("你是一个教学题目的专家，请根据以下示例题目生成").append(count).append("道类似的题目。\n\n"); return """
你是一个教学题目的专家，请根据以下示例题目生成%d道类似的题目。
prompt.append("知识点：").append(knowledgePoint.getKnowledgePointName()).append("\n"); 知识点：%s
prompt.append("知识点总结：").append(knowledgePoint.getSummary()).append("\n\n"); 知识点总结：%s
prompt.append("要求：\n");
prompt.append("1. 题目必须基于相同的教学知识点\n"); 要求：
prompt.append("2. 题目难度应与示例题目相当\n"); 1. 题目必须基于相同的教学知识点
prompt.append("3. 题型必须与示例题目一致\n"); 2. 题目难度应与示例题目相当
prompt.append("4. 答案必须明确且唯一\n"); 3. 题型必须与示例题目一致
prompt.append("5. 提供详细的解题过程或解析\n"); 4. 答案必须明确且唯一
prompt.append("6. 返回严格的JSON数组格式，每项包含以下字段：\n"); 5. 提供详细的解题过程或解析
prompt.append(" - question: 题干内容\n"); 6. 返回严格的JSON数组格式，每项包含以下字段：
prompt.append(" - answer: 答案内容\n"); - question: 题干内容
prompt.append(" - solution: 解析内容\n"); - answer: 答案内容
if (ExampleQuestionTypesEnum.CHOICE.getCode().equals(exampleQuestion.getType())) { - solution: 解析内容
prompt.append(" - options: 选项数组（仅选择题需要，每个选项包含content和sort字段）\n\n"); %s
输出格式示例：
[
{
"question": "题目内容",
"answer": "答案内容",
"solution": "解析内容",
%s
} }
prompt.append("输出格式示例：\n"); ]
prompt.append("[\n"); """.formatted(count, knowledgePoint.getKnowledgePointName(), knowledgePoint.getSummary(), optionsPart,
prompt.append(" {\n"); ExampleQuestionTypesEnum.CHOICE.getCode().equals(exampleQuestion.getType()) ?
prompt.append(" \"question\": \"题目内容\",\n"); "\"options\": [\n {\"content\": \"选项A内容\", \"sort\": 1},\n {\"content\": \"选项B内容\", \"sort\": 2}\n ]" : "");
prompt.append(" \"answer\": \"答案内容\",\n");
prompt.append(" \"solution\": \"解析内容\",\n");
if (ExampleQuestionTypesEnum.CHOICE.getCode().equals(exampleQuestion.getType())) {
prompt.append(", \"options\": [\n");
prompt.append(" {\"content\": \"选项A内容\", \"sort\": 1},\n");
prompt.append(" {\"content\": \"选项B内容\", \"sort\": 2}\n");
prompt.append(" ]\n");
}
prompt.append(" }\n");
prompt.append("]\n");
return prompt.toString();
} }
/** /**
@ -77,104 +74,108 @@ public class PromptBuilder {
* @return 提示词 * @return 提示词
*/ */
public static String buildPromptForBankQuestionGeneration(KnowledgePointEntity knowledgePoints, Integer count, GenerateTaskReq req) { public static String buildPromptForBankQuestionGeneration(KnowledgePointEntity knowledgePoints, Integer count, GenerateTaskReq req) {
StringBuilder prompt = new StringBuilder();
prompt.append("你是一位资深的'" + getGradeTypeName(req.getGradeType()) + "'教学专家，请根据以下知识点和示例题目为每一类型(1单选选择题 2多选选择题 4判断题 6填空题)的题目分别生成").append(count).append("道类似的题目。\n\n");
prompt.append("知识点名称：").append(knowledgePoints.getKnowledgePointName()).append("\n");
prompt.append("知识点总结：").append(req.getSummary()).append("\n");
prompt.append("对应的年级：").append(getGradeNameList(req.getGradeIds())).append("\n");
prompt.append("对应的学科：").append(getSubjectName(req.getSubjectId())).append("\n\n");
prompt.append("要求：\n");
prompt.append(" 1. 题目必须基于\"").append(knowledgePoints.getKnowledgePointName()).append("\"这个知识点,不能超出对应年纪和学生的理解范围\n");
prompt.append(" 2. 题目难度应在1.00和5.00范围内，小数点后面两位小数，1.00为最简单，5.00为最难，且每道题的难度不能相同\n");
prompt.append(" 3. 答案必须明确且唯一\n");
prompt.append(" 4. 提供详细的解析过程,如果是数学，物理，化学，必须列出具体的解题步骤\n");
prompt.append(" 5. 题干内容不能包含题目类型，如 （对/错）,（多选）\n");
prompt.append(" 6. 如果是选择题(单选选择题或则多选选择题)，题干内容不能包含选项，如(题目内容，选项A内容，选项B内容)\n");
prompt.append(" 7. 如果是判断题,答案(answer)只能是‘对’和‘错’，如果是选择题，答案只能是选项A,B,C,D,E... \n");
prompt.append(" 8. 每一类型题目的数量必须是" + count + "，不能省略,如要求输出10道题目，不能只输出9道题目\n");
prompt.append(" 9. 输出的格式必须是json格式，字段如下：\n");
prompt.append(" - title: 题干内容\n");
prompt.append(" - answer: 答案内容\n");
prompt.append(" - solution: 解析内容，提供详细的解析过程,如果是数学,物理或则化学的，必须列出具体的解题步骤。如果是英语，尽量使用中文\n");
prompt.append(" - type: 题型（1->单选选择题, 2->多选选择题, 4->判断题, 6->填空题）\n");
prompt.append(" - difficulty: 题目难易度系数（1-5的整数，5为最难，每道题难度不能相同）\n");
prompt.append(" - isNeedImage: 是否需要图片（0->不需要, 1->需要），如果是以图片的形式展示题目内容或者选项，则为1，否则为0\n");
prompt.append(" - options: 选择题选项数组（仅题型为单选选择题或则多选选择题需要，每个选项包含content和sort字段,选项内容不能一样）\n");
// 判断是否是一、二年级的数学题目 // 判断是否是一、二年级的数学题目
boolean isLowerElementaryMath = isLowerElementaryMath(req.getGradeIds(), req.getSubjectId()); boolean isLowerElementaryMath = isLowerElementaryMath(req.getGradeIds(), req.getSubjectId());
// 判断是否是三、四年级的英语题目 // 判断是否是三、四年级的英语题目
boolean isMiddleElementaryEnglish = isMiddleElementaryEnglish(req.getGradeIds(), req.getSubjectId()); boolean isMiddleElementaryEnglish = isMiddleElementaryEnglish(req.getGradeIds(), req.getSubjectId());
if (isNeedLatex(req.getSubjectId())) { String latexRequirement = isNeedLatex(req.getSubjectId()) ? " 10. 输出的题目内容,答案，解析，其中涉及到公式的，请使用Latex\n\n" : "";
prompt.append(" 10. 输出的题目内容,答案，解析，其中涉及到公式的，请使用Latex\n\n");
}
// 对三四年级英语题目添加特殊要求 String englishRequirement = isMiddleElementaryEnglish ? " 10. 这是三四年级的英语题目，请尽量使用中文出题，题目内容和选项中涉及的英语内容应适合该年龄段学生理解\n\n" : "";
if (isMiddleElementaryEnglish) {
prompt.append(" 10. 这是三四年级的英语题目，请尽量使用中文出题，题目内容和选项中涉及的英语内容应适合该年龄段学生理解\n\n");
}
prompt.append("输出格式示例：\n"); String lowerElementaryMathNote = isLowerElementaryMath ? "\n特别注意：这是一、二年级的题目，请尽量以图文并茂的形式展示题目内容和选项，使题目更适合低年级学生理解。\n" : "";
prompt.append("[\n");
prompt.append(" {\n");
prompt.append(" \"title\": \"题目内容\",\n");
prompt.append(" \"answer\": \"答案内容\",\n");
prompt.append(" \"solution\": \"解析内容\",\n");
prompt.append(" \"isNeedImage\": \"0\",\n");
prompt.append(" \"type\": 1,\n");
prompt.append(" \"difficulty\": 3.34,\n");
prompt.append(" \"options\": [\n");
prompt.append(" {\"content\": \"A. 选项A内容\", \"sort\": 1},\n");
prompt.append(" {\"content\": \"B. 选项B内容\", \"sort\": 2},\n");
prompt.append(" {\"content\": \"C. 选项C内容\", \"sort\": 3},\n");
prompt.append(" {\"content\": \"D. 选项D内容\", \"sort\": 4}\n");
prompt.append(" ]\n");
prompt.append(" }\n"); String middleElementaryEnglishNote = isMiddleElementaryEnglish ? "\n特别注意：这是三、四年级的英语题目，请尽量使用中文出题，让题目更容易被学生理解。\n" : "";
prompt.append("]\n");
// 特殊要求：对于小学一、二年级的数学题目，强调以图片为主 String mathRequirements = "";
if (isLowerElementaryMath) {
prompt.append("\n特别注意：这是一、二年级的题目，请尽量以图文并茂的形式展示题目内容和选项，使题目更适合低年级学生理解。\n");
}
// 特殊要求：对于三、四年级的英语题目，强调使用中文出题
if (isMiddleElementaryEnglish) {
prompt.append("\n特别注意：这是三、四年级的英语题目，请尽量使用中文出题，让题目更容易被学生理解。\n");
}
// 数学题目特殊要求：针对不同年级提供不同的解题步骤标准
if (req.getSubjectId() == 2) { // 数学学科 if (req.getSubjectId() == 2) { // 数学学科
prompt.append("\n数学题目解析(solution字段)规范要求：\n"); mathRequirements = "\n数学题目解析(solution字段)规范要求：\n";
if(Objects.nonNull(req.getGradeId())){ if(Objects.nonNull(req.getGradeId())){
// 初中三个年级的要求 // 初中三个年级的要求
if (req.getGradeId() == 7) { // 七年级(初一) if (req.getGradeId() == 7) { // 七年级(初一)
prompt.append("七年级(初一)解析标准：\n"); mathRequirements += "七年级(初一)解析标准：\n";
prompt.append("- 格式要求：从算术思维向代数思维过渡，强调基本概念、运算规则和解题格式的建立\n"); mathRequirements += "- 格式要求：从算术思维向代数思维过渡，强调基本概念、运算规则和解题格式的建立\n";
prompt.append("- 解析步骤：读与标(阅读题目，标记关键数据) -> 联与析(联想相关数学概念) -> 算或解(执行计算或按步骤解方程) -> 验与答(初步检验答案，并规范作答)\n"); mathRequirements += "- 解析步骤：读与标(阅读题目，标记关键数据) -> 联与析(联想相关数学概念) -> 算或解(执行计算或按步骤解方程) -> 验与答(初步检验答案，并规范作答)\n";
prompt.append("- 示例题型：代数方程应用题，要求严格按照\"设->列->解->验->答\"的格式进行解答\n"); mathRequirements += "- 示例题型：代数方程应用题，要求严格按照\"设->列->解->验->答\"的格式进行解答\n";
} }
if (req.getGradeId() == 8) { // 八年级(初二) if (req.getGradeId() == 8) { // 八年级(初二)
prompt.append("八年级(初二)解析标准：\n"); mathRequirements += "八年级(初二)解析标准：\n";
prompt.append("- 格式要求：逻辑推理能力要求提高，几何证明和函数概念引入，解题需展现严密的因果链条\n"); mathRequirements += "- 格式要求：逻辑推理能力要求提高，几何证明和函数概念引入，解题需展现严密的因果链条\n";
prompt.append("- 解析步骤：条件梳理(明确已知条件) -> 目标分析(明确待证明结论) -> 思路探寻(寻找定理、公式) -> 逻辑推演(清晰展示推理) -> 结论总结(给出最终结论)\n"); mathRequirements += "- 解析步骤：条件梳理(明确已知条件) -> 目标分析(明确待证明结论) -> 思路探寻(寻找定理、公式) -> 逻辑推演(清晰展示推理) -> 结论总结(给出最终结论)\n";
prompt.append("- 示例题型：几何证明题，要求严格按照\"已知->求证->证明\"的格式进行解答\n"); mathRequirements += "- 示例题型：几何证明题，要求严格按照\"已知->求证->证明\"的格式进行解答\n";
} }
if (req.getGradeId() == 9) { // 九年级(初三) if (req.getGradeId() == 9) { // 九年级(初三)
prompt.append("九年级(初三)解析标准：\n"); mathRequirements += "九年级(初三)解析标准：\n";
prompt.append("- 格式要求：知识高度综合，强调数学思想方法(分类讨论、数形结合、转化与化归、方程思想、模型思想)的应用，解法灵活多样\n"); mathRequirements += "- 格式要求：知识高度综合，强调数学思想方法(分类讨论、数形结合、转化与化归、方程思想、模型思想)的应用，解法灵活多样\n";
prompt.append("- 解析步骤：审题与建模(识别问题本质) -> 思路选择与规划(选择合适解题路径) -> 执行与讨论(计算或推理，必要时分类讨论) -> 检验与反思(检验答案合理性)\n"); mathRequirements += "- 解析步骤：审题与建模(识别问题本质) -> 思路选择与规划(选择合适解题路径) -> 执行与讨论(计算或推理，必要时分类讨论) -> 检验与反思(检验答案合理性)\n";
prompt.append("- 示例题型：二次函数综合题，要求体现数学思想方法的灵活应用\n"); mathRequirements += "- 示例题型：二次函数综合题，要求体现数学思想方法的灵活应用\n";
} }
} }
} }
return prompt.toString(); return """
你是一位资深的'%s'教学专家，请根据以下知识点和示例题目为每一类型(1单选选择题 2多选选择题 4判断题 6填空题)的题目分别生成%d道类似的题目。
知识点名称：%s
知识点总结：%s
对应的年级：%s
对应的学科：%s
要求：
1. 题目必须基于"%s"这个知识点,不能超出对应年纪和学生的理解范围
2. 题目难度应在1.00和5.00范围内，小数点后面两位小数，1.00为最简单，5.00为最难，且每道题的难度不能相同
3. 答案必须明确且唯一
4. 提供详细的解析过程,如果是数学，物理，化学，必须列出具体的解题步骤
5. 题干内容不能包含题目类型，如 （对/错）,（多选）
6. 如果是选择题(单选选择题或则多选选择题)，题干内容不能包含选项，如(题目内容，选项A内容，选项B内容)
7. 如果是判断题,答案(answer)只能是‘对’和‘错’，如果是选择题，答案只能是选项A,B,C,D,E...
8. 每一类型题目的数量必须是%d，不能省略,如要求输出10道题目，不能只输出9道题目
9. 输出的格式必须是json格式，字段如下：
- title: 题干内容
- answer: 答案内容
- solution: 解析内容，提供详细的解析过程,如果是数学,物理或则化学的，必须列出具体的解题步骤。如果是英语，尽量使用中文
- type: 题型（1->单选选择题, 2->多选选择题, 4->判断题, 6->填空题）
- difficulty: 题目难易度系数（1-5的整数，5为最难，每道题难度不能相同）
- isNeedImage: 是否需要图片（0->不需要, 1->需要），如果是以图片的形式展示题目内容或者选项，则为1，否则为0
- options: 选择题选项数组（仅题型为单选选择题或则多选选择题需要，每个选项包含content和sort字段,选项内容不能一样）
%s%s
输出格式示例：
[
{
"title": "题目内容",
"answer": "答案内容",
"solution": "解析内容",
"isNeedImage": "0",
"type": 1,
"difficulty": 3.34,
"options": [
{"content": "A. 选项A内容", "sort": 1},
{"content": "B. 选项B内容", "sort": 2},
{"content": "C. 选项C内容", "sort": 3},
{"content": "D. 选项D内容", "sort": 4}
]
}
]
%s%s%s
""".formatted(
getGradeTypeName(req.getGradeType()),
count,
knowledgePoints.getKnowledgePointName(),
req.getSummary(),
getGradeNameList(req.getGradeIds()),
getSubjectName(req.getSubjectId()),
knowledgePoints.getKnowledgePointName(),
count,
latexRequirement,
englishRequirement,
lowerElementaryMathNote,
middleElementaryEnglishNote,
mathRequirements
);
} }
/** /**
@ -184,60 +185,70 @@ public class PromptBuilder {
* @return 提示词 * @return 提示词
*/ */
public static String buildSplitPrompt(KnowledgePointEntity knowledgePoint, KnowSummaryEntity summary, KnowledgePointSplitReq req) { public static String buildSplitPrompt(KnowledgePointEntity knowledgePoint, KnowSummaryEntity summary, KnowledgePointSplitReq req) {
StringBuilder prompt = new StringBuilder(); String specificNames = "";
prompt.append("你是一位资深的教学专家，请根据以下知识点进行拆分，将其拆分为" + req.getCount() + "个更细粒度的知识点。\n\n");
prompt.append("原始知识点名称：").append(knowledgePoint.getKnowledgePointName()).append("\n");
prompt.append("原始知识点总结：").append(summary.getSummary()).append("\n");
prompt.append("对应的年级：").append(getGradeNameList(req.getGradeIds())).append("\n");
prompt.append("对应的学科：").append(getSubjectName(knowledgePoint.getSubjectId())).append("\n");
if (CollectionUtil.isNotEmpty(req.getKnowledgePointNames())) { if (CollectionUtil.isNotEmpty(req.getKnowledgePointNames())) {
prompt.append("要求拆分为以下名称的知识点：").append("\n"); StringBuilder namesBuilder = new StringBuilder();
for (int i = 0; i < req.getKnowledgePointNames().size(); i++) { for (int i = 0; i < req.getKnowledgePointNames().size(); i++) {
prompt.append(" ").append(i + 1).append(". ").append(req.getKnowledgePointNames().get(i)).append("\n"); namesBuilder.append(" ").append(i + 1).append(". ").append(req.getKnowledgePointNames().get(i)).append("\n");
} }
specificNames = "要求拆分为以下名称的知识点：\n" + namesBuilder.toString();
} }
prompt.append("要求：\n"); String requirements = CollectionUtil.isNotEmpty(req.getKnowledgePointNames()) ?
if (CollectionUtil.isNotEmpty(req.getKnowledgePointNames())) { String.format("1. 将原始知识点拆分为上面指定的%d个名称的知识点，每个知识点需要包含以下信息：\n", req.getCount()) :
prompt.append("1. 将原始知识点拆分为上面指定的").append(req.getCount()).append("个名称的知识点，每个知识点需要包含以下信息：\n"); String.format("1. 将原始知识点拆分为%d个更具体、更细粒度的知识点，每个知识点需要包含以下信息：\n", req.getCount());
} else {
prompt.append("1. 将原始知识点拆分为").append(req.getCount()).append("个更具体、更细粒度的知识点，每个知识点需要包含以下信息：\n"); return """
你是一位资深的教学专家，请根据以下知识点进行拆分，将其拆分为%d个更细粒度的知识点。
原始知识点名称：%s
原始知识点总结：%s
对应的年级：%s
对应的学科：%s
%s
要求：
%s
- knowledgePointName: 拆分后的知识点名称
- summary: 知识点的简要总结
- exampleQuestions: 该知识点的示例题目列表
2. 每个知识点不能超出对应年纪和学生的理解范围
3. 知识点总结必须符合教学逻辑（能直接被教师用于教学视频脚本），应包括：①基本定义；②在学科体系中的地位与作用；③与前后知识的衔接关系；④学习意义与实际应用；⑤常见误区与误解。少于 300 字。
4. exampleQuestions字段要求：
- 每个题目包含type(题型)、question(题目内容)、options(选项，仅选择题需要)、answer(答案)、explanation(解析)字段
- 题型包括：包含4种题型(1单选选择题 2多选选择题 4判断题 6填空题)
- 每种题型1道题目
5. 返回严格的JSON数组格式，示例如下：
[
{
"knowledgePointName": "拆分后的知识点名称",
"summary": "知识点总结",
"exampleQuestions": [
{
"type": "1",
"question": "题目内容",
"options": [
{"content": "A. 选项A内容", "sort": 1},
{"content": "B. 选项B内容", "sort": 2},
{"content": "C. 选项C内容", "sort": 3},
{"content": "D. 选项D内容", "sort": 4}
]
"answer": "答案",
"explanation": "解析内容"
} }
prompt.append(" - knowledgePointName: 拆分后的知识点名称\n"); ]
prompt.append(" - summary: 知识点的简要总结\n"); }
prompt.append(" - exampleQuestions: 该知识点的示例题目列表\n"); ]
prompt.append("2. 每个知识点不能超出对应年纪和学生的理解范围\n"); """.formatted(
prompt.append("3. 知识点总结必须符合教学逻辑（能直接被教师用于教学视频脚本），应包括：①基本定义；②在学科体系中的地位与作用；③与前后知识的衔接关系；④学习意义与实际应用；⑤常见误区与误解。少于 300 字。\n"); req.getCount(),
prompt.append("4. exampleQuestions字段要求：\n"); knowledgePoint.getKnowledgePointName(),
prompt.append(" - 每个题目包含type(题型)、question(题目内容)、options(选项，仅选择题需要)、answer(答案)、explanation(解析)字段\n"); summary.getSummary(),
prompt.append(" - 题型包括：包含4种题型(1单选选择题 2多选选择题 4判断题 6填空题)\n"); getGradeNameList(req.getGradeIds()),
prompt.append(" - 每种题型1道题目\n\n"); getSubjectName(knowledgePoint.getSubjectId()),
specificNames,
prompt.append("5. 返回严格的JSON数组格式，示例如下：\n"); requirements
prompt.append("[\n"); );
prompt.append(" {\n");
prompt.append(" \"knowledgePointName\": \"拆分后的知识点名称\",\n");
prompt.append(" \"summary\": \"知识点总结\",\n");
prompt.append(" \"exampleQuestions\": [\n");
prompt.append(" {\n");
prompt.append(" \"type\": \"1\",\n");
prompt.append(" \"question\": \"题目内容\",\n");
prompt.append(" \"options\": [\n");
prompt.append(" {\"content\": \"A. 选项A内容\", \"sort\": 1},\n");
prompt.append(" {\"content\": \"B. 选项B内容\", \"sort\": 2},\n");
prompt.append(" {\"content\": \"C. 选项C内容\", \"sort\": 3},\n");
prompt.append(" {\"content\": \"D. 选项D内容\", \"sort\": 4}\n");
prompt.append(" ]\n");
prompt.append(" \"answer\": \"答案\",\n");
prompt.append(" \"explanation\": \"解析内容\"\n");
prompt.append(" }\n");
prompt.append(" ]\n");
prompt.append(" }\n");
prompt.append("]\n");
return prompt.toString();
} }
@ -249,53 +260,59 @@ public class PromptBuilder {
* @return 提示词 * @return 提示词
*/ */
public static String buildCheckPrompt(KnowledgePointEntity knowledgePoint, KnowSummaryEntity summary, Collection<Integer> gradeIds) { public static String buildCheckPrompt(KnowledgePointEntity knowledgePoint, KnowSummaryEntity summary, Collection<Integer> gradeIds) {
StringBuilder prompt = new StringBuilder(); return """
你是一位资深的教学专家，请根据以下知识点判断其内容是否正确和超纲。
prompt.append("你是一位资深的教学专家，请根据以下知识点判断其内容是否正确和超纲。\n\n"); 知识点名称：%s
知识点总结：%s
对应的年级：%s
对应的学科：%s
prompt.append("知识点名称：").append(knowledgePoint.getKnowledgePointName()).append("\n");
prompt.append("知识点总结：").append(summary != null ? summary.getSummary() : "").append("\n");
prompt.append("对应的年级：").append(getGradeNameList(gradeIds)).append("\n");
prompt.append("对应的学科：").append(getSubjectName(knowledgePoint.getSubjectId())).append("\n");
prompt.append("请判断以下内容：\n"); 请判断以下内容：
prompt.append("1. 该知识点内容是否正确\n"); 1. 该知识点内容是否正确
prompt.append("2. 该知识点是否超出指定年级学生的学习范围（超纲）\n"); 2. 该知识点是否超出指定年级学生的学习范围（超纲）
prompt.append("3. 如果超纲，请说明超纲原因，并给出适合的替换知识点名称和总结\n"); 3. 如果超纲，请说明超纲原因，并给出适合的替换知识点名称和总结
prompt.append("4. 请提供该知识点的示例题目\n\n"); 4. 请提供该知识点的示例题目
prompt.append("要求：\n");
prompt.append("1. 返回严格的JSON格式，包含以下字段：\n");
prompt.append(" - isCorrect: 知识点内容是否正确 (boolean)\n");
prompt.append(" - isOutOfScope: 是否超纲 (boolean)\n");
prompt.append(" - outOfScopeReason: 超纲原因 (string, 如果没有超纲则为null)\n");
prompt.append(" - suggestedKnowledgePointName: 建议的知识点名称 (string, 如果没有超纲则为null)\n");
prompt.append(" - suggestedSummary: 建议的知识点总结 (string, 如果没有超纲则为null)\n");
prompt.append(" - exampleQuestions: 示例题目列表 (array)\n");
prompt.append("2. exampleQuestions字段要求：\n");
prompt.append(" - 每个题目包含type(题型)、question(题目内容)、options(选项，仅选择题需要)、answer(答案)、explanation(解析)字段\n");
prompt.append(" - 题型包括：包含4种题型(1单选选择题 2多选选择题 4判断题 6填空题)\n");
prompt.append(" - 每种题型1道题目\n\n");
prompt.append("输出格式示例：\n"); 要求：
prompt.append("{\n"); 1. 返回严格的JSON格式，包含以下字段：
prompt.append(" \"isCorrect\": true,\n"); - isCorrect: 知识点内容是否正确 (boolean)
prompt.append(" \"isOutOfScope\": false,\n"); - isOutOfScope: 是否超纲 (boolean)
prompt.append(" \"outOfScopeReason\": null,\n"); - outOfScopeReason: 超纲原因 (string, 如果没有超纲则为null)
prompt.append(" \"suggestedKnowledgePointName\": null,\n"); - suggestedKnowledgePointName: 建议的知识点名称 (string, 如果没有超纲则为null)
prompt.append(" \"suggestedSummary\": null,\n"); - suggestedSummary: 建议的知识点总结 (string, 如果没有超纲则为null)
prompt.append(" \"exampleQuestions\": [\n"); - exampleQuestions: 示例题目列表 (array)
prompt.append(" {\n"); 2. exampleQuestions字段要求：
prompt.append(" \"type\": \"1\",\n"); - 每个题目包含type(题型)、question(题目内容)、options(选项，仅选择题需要)、answer(答案)、explanation(解析)字段
prompt.append(" \"question\": \"题目内容\",\n"); - 题型包括：包含4种题型(1单选选择题 2多选选择题 4判断题 6填空题)
prompt.append(" \"options\": [\"选项A\", \"选项B\", \"选项C\", \"选项D\"],\n"); - 每种题型1道题目
prompt.append(" \"answer\": \"答案\",\n");
prompt.append(" \"explanation\": \"解析内容\"\n");
prompt.append(" }\n");
prompt.append(" ]\n");
prompt.append("}\n");
return prompt.toString();
输出格式示例：
{
"isCorrect": true,
"isOutOfScope": false,
"outOfScopeReason": null,
"suggestedKnowledgePointName": null,
"suggestedSummary": null,
"exampleQuestions": [
{
"type": "1",
"question": "题目内容",
"options": ["选项A", "选项B", "选项C", "选项D"],
"answer": "答案",
"explanation": "解析内容"
}
]
}
""".formatted(
knowledgePoint.getKnowledgePointName(),
summary != null ? summary.getSummary() : "",
getGradeNameList(gradeIds),
getSubjectName(knowledgePoint.getSubjectId())
);
} }
/** /**
@ -306,100 +323,107 @@ public class PromptBuilder {
* @return 提示词 * @return 提示词
*/ */
public static String buildPromptForTeachTextGeneration(TeachGoalsEntity teachGoal, List<TeachMethodsEntity> methods, GenerateTaskReq req) { public static String buildPromptForTeachTextGeneration(TeachGoalsEntity teachGoal, List<TeachMethodsEntity> methods, GenerateTaskReq req) {
StringBuilder prompt = new StringBuilder(); StringBuilder methodsBuilder = new StringBuilder();
prompt.append("你是一位经验丰富的教师，请根据以下教学目标和教学重点，针对每种教学方法分别生成一份详细且有针对性的讲课稿。\n\n");
// 添加教学目标信息
prompt.append("教学目标: ").append(teachGoal.getGoal()).append("\n");
prompt.append("教学重点: ").append(teachGoal.getPoint()).append("\n\n");
if(Objects.nonNull(req.getGradeIds())){
prompt.append("对应的年级：").append(getGradeName(req.getGradeId())).append("\n");
}
if(Objects.nonNull(req.getSubjectId())){
prompt.append("对应的学科：").append(getSubjectName(req.getSubjectId())).append("\n\n");
}
// 添加教学方法信息
prompt.append("教学方法列表:\n");
for (int i = 0; i < methods.size(); i++) { for (int i = 0; i < methods.size(); i++) {
TeachMethodsEntity method = methods.get(i); TeachMethodsEntity method = methods.get(i);
prompt.append((i + 1)).append(". ").append(method.getName()); methodsBuilder.append((i + 1)).append(". ").append(method.getName());
if (method.getDescription() != null && !method.getDescription().isEmpty()) { if (method.getDescription() != null && !method.getDescription().isEmpty()) {
prompt.append(": ").append(method.getDescription()); methodsBuilder.append(": ").append(method.getDescription());
} }
prompt.append("(methodId: ").append(method.getId()).append(")\n"); methodsBuilder.append("(methodId: ").append(method.getId()).append(")\n");
} }
prompt.append("\n");
// 添加要求 return """
prompt.append("请根据以上教学目标、重点和教学方法生成详细的讲课稿，要求如下:\n"); 你是一位经验丰富的教师，请根据以下教学目标和教学重点，针对每种教学方法分别生成一份详细且有针对性的讲课稿。
prompt.append("1. 内容详实，语言生动，适合课堂讲解\n");
prompt.append("2. 结构清晰，逻辑性强\n");
prompt.append("3. 包含导入、新授、巩固练习、小结等教学环节\n");
prompt.append("4. 每种教学方法都需要生成对应的讲课稿\n");
prompt.append("5. 字数不少于800字\n");
prompt.append("6. 以JSON数组格式输出，每个元素包含sort(排序)、methodId(教学方法Id)和text(讲课稿内容)、isDefault(是否默认，1：是，0：否)，videoContent(讲课稿内容对应的视频内容)字段\n\n");
// 添加输出示例 教学目标: %s
prompt.append("示例输出格式:\n"); 教学重点: %s
prompt.append("[\n"); %s%s
prompt.append(" {\n"); 教学方法列表:
prompt.append(" \"sort\": 1,\n"); %s
prompt.append(" \"methodId\": 385,\n");
prompt.append(" \"isDefault\": 1,\n");
prompt.append(" \"text\": \"这里是针对第一种教学方法的讲课稿内容...\",\n");
prompt.append(" \"videoContent\": \"针对第一种教学方法的讲课稿内容对应的视频内容...\",\n");
prompt.append(" },\n");
prompt.append(" {\n");
prompt.append(" \"sort\": 2,\n");
prompt.append(" \"methodId\": 386,\n");
prompt.append(" \"isDefault\": 0,\n");
prompt.append(" \"text\": \"这里是针对第二种教学方法的讲课稿内容...\",\n");
prompt.append(" \"videoContent\": \"针对第二种教学方法的讲课稿内容对应的视频内容...\",\n");
prompt.append(" }\n");
prompt.append(" {\n");
prompt.append(" \"sort\": 3,\n");
prompt.append(" \"isDefault\": 0,\n");
prompt.append(" \"methodId\": 387,\n");
prompt.append(" \"text\": \"这里是针对第三种教学方法的讲课稿内容...\",\n");
prompt.append(" \"videoContent\": \"针对第三种教学方法的讲课稿内容对应的视频内容...\",\n");
prompt.append("]");
return prompt.toString(); 请根据以上教学目标、重点和教学方法生成详细的讲课稿，要求如下:
1. 内容详实，语言生动，适合课堂讲解
2. 结构清晰，逻辑性强
3. 包含导入、新授、巩固练习、小结等教学环节
4. 每种教学方法都需要生成对应的讲课稿
5. 字数不少于800字
6. 以JSON数组格式输出，每个元素包含sort(排序)、methodId(教学方法Id)和text(讲课稿内容)、isDefault(是否默认，1：是，0：否)，videoContent(讲课稿内容对应的视频内容)字段
示例输出格式:
[
{
"sort": 1,
"methodId": 385,
"isDefault": 1,
"text": "这里是针对第一种教学方法的讲课稿内容...",
"videoContent": "针对第一种教学方法的讲课稿内容对应的视频内容...",
},
{
"sort": 2,
"methodId": 386,
"isDefault": 0,
"text": "这里是针对第二种教学方法的讲课稿内容...",
"videoContent": "针对第二种教学方法的讲课稿内容对应的视频内容...",
}
{
"sort": 3,
"isDefault": 0,
"methodId": 387,
"text": "这里是针对第三种教学方法的讲课稿内容...",
"videoContent": "针对第三种教学方法的讲课稿内容对应的视频内容...",
}
]
""".formatted(
teachGoal.getGoal(),
teachGoal.getPoint(),
Objects.nonNull(req.getGradeIds()) ? "对应的年级：" + getGradeName(req.getGradeId()) + "\n" : "",
Objects.nonNull(req.getSubjectId()) ? "对应的学科：" + getSubjectName(req.getSubjectId()) + "\n\n" : "",
methodsBuilder.toString()
);
} }
public static String buildPromptForTeachGoalGeneration(KnowledgePointEntity knowledgePoint, Integer count, GenerateTaskReq req) { public static String buildPromptForTeachGoalGeneration(KnowledgePointEntity knowledgePoint, Integer count, GenerateTaskReq req) {
StringBuilder prompt = new StringBuilder(); return """
prompt.append("你是一位资深的'").append(getGradeTypeName(req.getGradeType())).append("'教学专家，请根据以下知识点生成").append(count).append("个教学目标（考点）。\n\n"); 你是一位资深的'%s'教学专家，请根据以下知识点生成%d个教学目标（考点）。
// 添加知识点信息 知识点名称：%s
prompt.append("知识点名称：").append(knowledgePoint.getKnowledgePointName()).append("\n"); 知识点总结：%s
prompt.append("知识点总结：").append(req.getSummary()).append("\n"); 对应的年级：%s
prompt.append("对应的年级：").append(getGradeNameList(req.getGradeIds())).append("\n"); 对应的学科：%s
prompt.append("对应的学科：").append(getSubjectName(req.getSubjectId())).append("\n\n");
prompt.append("要求：\n");
prompt.append(" 1. 教学目标必须基于\"").append(knowledgePoint.getKnowledgePointName()).append("\"这个知识点\n");
prompt.append(" 2. 教学目标应适合对应年级的学生理解和掌握\n");
prompt.append(" 3. 每个教学目标应包含具体的学习成果描述\n");
prompt.append(" 4. 提供对应的教学重点\n");
prompt.append(" 5. 可以提供推荐的视频教学链接（可选）\n");
prompt.append(" 6. 每个教学目标需要有一个排序编号\n");
prompt.append(" 7. 输出的格式必须是json格式，字段如下：\n");
prompt.append(" - goal: 教学目标内容\n");
prompt.append(" - point: 教学重点\n");
prompt.append(" - sort: 排序编号\n\n");
prompt.append("输出格式示例：\n"); 要求：
prompt.append("[\n"); 1. 教学目标必须基于"%s"这个知识点
prompt.append(" {\n"); 2. 教学目标应适合对应年级的学生理解和掌握
prompt.append(" \"goal\": \"教学目标内容\",\n"); 3. 每个教学目标应包含具体的学习成果描述
prompt.append(" \"point\": \"教学重点\",\n"); 4. 提供对应的教学重点
prompt.append(" \"sort\": 1,\n"); 5. 可以提供推荐的视频教学链接（可选）
prompt.append(" }\n"); 6. 每个教学目标需要有一个排序编号
prompt.append("]\n"); 7. 输出的格式必须是json格式，字段如下：
- goal: 教学目标内容
- point: 教学重点
- sort: 排序编号
return prompt.toString();
输出格式示例：
[
{
"goal": "教学目标内容",
"point": "教学重点",
"sort": 1,
}
]
""".formatted(
getGradeTypeName(req.getGradeType()),
count,
knowledgePoint.getKnowledgePointName(),
req.getSummary(),
getGradeNameList(req.getGradeIds()),
getSubjectName(req.getSubjectId()),
knowledgePoint.getKnowledgePointName()
);
} }
/** /**
@ -409,69 +433,74 @@ public class PromptBuilder {
* @return 提示词 * @return 提示词
*/ */
public static String buildPromptForTeachTextVideoScriptGeneration(TeachTextsEntity text) { public static String buildPromptForTeachTextVideoScriptGeneration(TeachTextsEntity text) {
StringBuilder prompt = new StringBuilder(); return """
请根据以下视频内容描述，生成一个完整的Python脚本，该脚本能够直接生成高质量的教学视频。
prompt.append("请根据以下视频内容描述，生成一个完整的Python脚本，该脚本能够直接生成高质量的教学视频。\n\n"); ## 视频内容描述:
%s
prompt.append("## 视频内容描述:\n");
prompt.append(text.getVideoContent());
prompt.append("\n\n");
prompt.append("## 核心要求:\n"); ## 核心要求:
prompt.append("1. **视频类型**: 生成的是纯视觉教学视频，不需要包含任何字幕或音频\n"); 1. **视频类型**: 生成的是纯视觉教学视频，不需要包含任何字幕或音频
prompt.append("2. **视频质量**: 必须是高质量的视觉呈现，包括清晰的图形、动画和视觉效果\n"); 2. **视频质量**: 必须是高质量的视觉呈现，包括清晰的图形、动画和视觉效果
prompt.append("3. **教学重点**: 通过视觉元素（图表、动画、代码演示、视觉示例等）清晰地传达教学内容\n\n"); 3. **教学重点**: 通过视觉元素（图表、动画、代码演示、视觉示例等）清晰地传达教学内容
prompt.append("## Python代码要求:\n");
prompt.append("### 1. 代码结构:\n"); ## Python代码要求:
prompt.append("- 必须是完整的、可直接运行的独立脚本\n");
prompt.append("- 包含所有必要的导入语句和依赖\n");
prompt.append("- 包含主程序入口，可直接执行生成视频\n\n");
prompt.append("### 2. 视觉生成要求:\n"); ### 1. 代码结构:
prompt.append("- **使用专业的视觉库**: 如Matplotlib, Plotly, Seaborn, MoviePy, OpenCV, PIL等\n"); - 必须是完整的、可直接运行的独立脚本
prompt.append("- **高质量视觉效果**:\n"); - 包含所有必要的导入语句和依赖
prompt.append(" - 清晰美观的图表和可视化\n"); - 包含主程序入口，可直接执行生成视频
prompt.append(" - 流畅的动画和过渡效果\n");
prompt.append(" - 合适的颜色搭配和视觉层次\n");
prompt.append(" - 适当的文本标注（作为图形的一部分，而非字幕）\n");
prompt.append("- **视觉叙事**: 通过视觉序列清晰地展示概念演变或步骤流程\n\n");
prompt.append("### 3. 代码质量:\n");
prompt.append("- **完整注释**:\n");
prompt.append(" - 文件头部：说明视频主题、主要视觉元素和依赖\n");
prompt.append(" - 函数/类：详细说明功能和参数\n");
prompt.append(" - 关键步骤：解释视觉生成逻辑\n");
prompt.append("- **错误处理**: 包含适当的异常处理和边界情况\n");
prompt.append("- **模块化设计**: 将不同功能封装为函数或类\n\n");
prompt.append("### 4. 依赖管理:\n"); ### 2. 视觉生成要求:
prompt.append("- 在文件开头通过注释明确列出所有第三方库\n"); - **使用专业的视觉库**: 如Matplotlib, Plotly, Seaborn, MoviePy, OpenCV, PIL等
prompt.append("- 提供pip安装命令的注释\n\n"); - **高质量视觉效果**:
- 清晰美观的图表和可视化
- 流畅的动画和过渡效果
- 合适的颜色搭配和视觉层次
- 适当的文本标注（作为图形的一部分，而非字幕）
- **视觉叙事**: 通过视觉序列清晰地展示概念演变或步骤流程
prompt.append("### 5. 特别注意事项:\n");
prompt.append("- **不要生成音频处理代码**（如声音添加、音轨处理）\n");
prompt.append("- **不要生成字幕相关代码**（如字幕叠加、文本时间轴）\n");
prompt.append("- **专注于视觉表达**：通过图形、动画、图表等视觉元素传达信息\n");
prompt.append("- **视频时长**：根据内容复杂度，生成合理时长的视频（通常在1-5分钟）\n\n");
prompt.append("## 输出格式:\n"); ### 3. 代码质量:
prompt.append("严格按以下JSON格式输出，不要包含任何解释或额外文本：\n"); - **完整注释**:
prompt.append("[\n"); - 文件头部：说明视频主题、主要视觉元素和依赖
prompt.append(" {\n"); - 函数/类：详细说明功能和参数
prompt.append(" \"pythonScript\": \"完整的Python脚本代码，可直接运行生成高质量无字幕无音频的教学视频\"\n"); - 关键步骤：解释视觉生成逻辑
prompt.append(" }\n"); - **错误处理**: 包含适当的异常处理和边界情况
prompt.append("]\n\n"); - **模块化设计**: 将不同功能封装为函数或类
prompt.append("## 示例思考方向（根据具体内容调整）:\n");
prompt.append("- 如果是编程教学：生成代码执行过程的可视化动画\n");
prompt.append("- 如果是数学教学：生成公式推导的逐步动画演示\n");
prompt.append("- 如果是数据科学：生成数据处理流程的可视化\n");
prompt.append("- 如果是算法教学：生成算法步骤的动态演示\n");
prompt.append("- 如果是概念讲解：生成概念演变的分步图示\n");
return prompt.toString(); ### 4. 依赖管理:
- 在文件开头通过注释明确列出所有第三方库
- 提供pip安装命令的注释
### 5. 特别注意事项:
- **不要生成音频处理代码**（如声音添加、音轨处理）
- **不要生成字幕相关代码**（如字幕叠加、文本时间轴）
- **专注于视觉表达**：通过图形、动画、图表等视觉元素传达信息
- **视频时长**：根据内容复杂度，生成合理时长的视频（通常在1-5分钟）
## 输出格式:
严格按以下JSON格式输出，不要包含任何解释或额外文本：
[
{
"pythonScript": "完整的Python脚本代码，可直接运行生成高质量无字幕无音频的教学视频"
}
]
## 示例思考方向（根据具体内容调整）:
- 如果是编程教学：生成代码执行过程的可视化动画
- 如果是数学教学：生成公式推导的逐步动画演示
- 如果是数据科学：生成数据处理流程的可视化
- 如果是算法教学：生成算法步骤的动态演示
- 如果是概念讲解：生成概念演变的分步图示
""".formatted(text.getVideoContent());
} }
private static boolean isNeedLatex(Integer subjectId) { private static boolean isNeedLatex(Integer subjectId) {
@ -486,91 +515,57 @@ public class PromptBuilder {
* @return 题型描述 * @return 题型描述
*/ */
private static String getQuestionTypeText(Integer type) { private static String getQuestionTypeText(Integer type) {
switch (type) { return switch (type) {
case 1: case 1 -> "选择题";
return "选择题"; case 2 -> "多选选择题";
case 2: case 3 -> "问答题";
return "多选选择题"; case 4 -> "判断题";
case 3: case 5 -> "计算题";
return "问答题"; case 6 -> "填空题";
case 4: default -> "其他题型";
return "判断题"; };
case 5:
return "计算题";
case 6:
return "填空题";
default:
return "其他题型";
}
} }
private static String getGradeTypeName(Integer gradeType) { private static String getGradeTypeName(Integer gradeType) {
switch (gradeType) { return switch (gradeType) {
case 1: case 1 -> "小学";
return "小学"; case 2 -> "初中";
case 2: case 3 -> "高中";
return "初中"; default -> throw new RuntimeException("未知的学段类型");
case 3: };
return "高中";
default:
throw new RuntimeException("未知的学段类型");
}
} }
private static String getSubjectName(Integer subjectId) { private static String getSubjectName(Integer subjectId) {
switch (subjectId) { return switch (subjectId) {
case 1: case 1 -> "语文";
return "语文"; case 2 -> "数学";
case 2: case 3 -> "英语";
return "数学"; case 4 -> "品德与生活";
case 3: case 5 -> "科学";
return "英语"; case 6 -> "历史";
case 4: case 7 -> "地理";
return "品德与生活"; case 8 -> "生物学";
case 5: case 9 -> "政治";
return "科学"; case 10 -> "物理";
case 6: case 11 -> "化学";
return "历史"; default -> throw new RuntimeException("未知的学科类型");
case 7: };
return "地理";
case 8:
return "生物学";
case 9:
return "政治";
case 10:
return "物理";
case 11:
return "化学";
default:
throw new RuntimeException("未知的学科类型");
}
} }
private static String getGradeName(Integer gradeId) { private static String getGradeName(Integer gradeId) {
switch (gradeId) { return switch (gradeId) {
case 1: case 1 -> "一年级";
return "一年级"; case 2 -> "二年级";
case 2: case 3 -> "三年级";
return "二年级"; case 4 -> "四年级";
case 3: case 5 -> "五年级";
return "三年级"; case 6 -> "六年级";
case 4: case 7 -> "初一";
return "四年级"; case 8 -> "初二";
case 5: case 9 -> "初三";
return "五年级"; case 10 -> "高中";
case 6: default -> throw new RuntimeException("未知的学科类型");
return "六年级"; };
case 7:
return "初一";
case 8:
return "初二";
case 9:
return "初三";
case 10:
return "高中";
default:
throw new RuntimeException("未知的学科类型");
}
} }
private static String getGradeNameList(Collection<Integer> gradeIds) { private static String getGradeNameList(Collection<Integer> gradeIds) {

1
seer-teacher/seer-teacher-service-bootstrap/src/main/java/com/seer/teach/teacher/bootstrap/SeerTeacherApplicationBootStrap.java
View File

@ -25,7 +25,6 @@ public class SeerTeacherApplicationBootStrap {
public static void main(String[] args) { public static void main(String[] args) {
SpringApplication app = new SpringApplication(SeerTeacherApplicationBootStrap.class); SpringApplication app = new SpringApplication(SeerTeacherApplicationBootStrap.class);
Environment env = app.run(args).getEnvironment(); Environment env = app.run(args).getEnvironment();
log.info("spring.mvc.pathmatch.matching-strategy={}", env.getProperty("spring.mvc.pathmatch.matching-strategy"));
String port = env.getProperty("server.port", "8087"); String port = env.getProperty("server.port", "8087");
String contextPath = env.getProperty("server.servlet.context-path", "/"); String contextPath = env.getProperty("server.servlet.context-path", "/");
log.info("----------------------------------------------------------"); log.info("----------------------------------------------------------");

2
seer-teacher/seer-teacher-service-bootstrap/src/main/resources/application.yml
View File

@ -23,6 +23,8 @@ spring:
- optional:nacos:shared-database.yaml - optional:nacos:shared-database.yaml
- optional:nacos:shared-minio.yaml - optional:nacos:shared-minio.yaml
- optional:nacos:shared-redis.yaml - optional:nacos:shared-redis.yaml
- optional:nacos:shared-sa-token.yaml
- optional:nacos:shared-minio.yaml
cloud: cloud:
nacos: nacos:
discovery: discovery:

4
seer-teacher/seer-teacher-service/src/main/java/com/seer/teach/teacher/service/IAiScenarioConfigService.java
View File

@ -8,9 +8,9 @@ import com.seer.teach.teacher.module.entity.AiScenarioConfigEntity;
* AI场景配置表 服务类 * AI场景配置表 服务类
* </p> * </p>
* *
* @author System
* @since 2025-10-27
*/ */
public interface IAiScenarioConfigService extends IService<AiScenarioConfigEntity> { public interface IAiScenarioConfigService extends IService<AiScenarioConfigEntity> {
AiScenarioConfigEntity getOneByScenarioCode(String scenarioCode);
} }

23
seer-teacher/seer-teacher-service/src/main/java/com/seer/teach/teacher/service/impl/AiScenarioConfigServiceImpl.java
View File

@ -1,9 +1,16 @@
package com.seer.teach.teacher.service.impl; package com.seer.teach.teacher.service.impl;
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl; import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.seer.teach.common.constants.CommonConstant;
import com.seer.teach.common.enums.ResultCodeEnum;
import com.seer.teach.common.utils.AssertUtils;
import com.seer.teach.teacher.module.entity.AiScenarioConfigEntity; import com.seer.teach.teacher.module.entity.AiScenarioConfigEntity;
import com.seer.teach.teacher.module.entity.AiScenarioEntity;
import com.seer.teach.teacher.module.mapper.AiScenarioConfigMapper; import com.seer.teach.teacher.module.mapper.AiScenarioConfigMapper;
import com.seer.teach.teacher.service.IAiScenarioConfigService; import com.seer.teach.teacher.service.IAiScenarioConfigService;
import com.seer.teach.teacher.service.IAiScenarioService;
import lombok.RequiredArgsConstructor;
import org.springframework.stereotype.Service; import org.springframework.stereotype.Service;
/** /**
@ -14,7 +21,23 @@ import org.springframework.stereotype.Service;
* @author System * @author System
* @since 2025-10-27 * @since 2025-10-27
*/ */
@RequiredArgsConstructor
@Service @Service
public class AiScenarioConfigServiceImpl extends ServiceImpl<AiScenarioConfigMapper, AiScenarioConfigEntity> implements IAiScenarioConfigService { public class AiScenarioConfigServiceImpl extends ServiceImpl<AiScenarioConfigMapper, AiScenarioConfigEntity> implements IAiScenarioConfigService {
private final IAiScenarioService aiScenarioService;
@Override
public AiScenarioConfigEntity getOneByScenarioCode(String scenarioCode) {
LambdaQueryWrapper<AiScenarioEntity> scenarioWrapper = new LambdaQueryWrapper<>();
scenarioWrapper.eq(AiScenarioEntity::getScenarioCode, scenarioCode);
AiScenarioEntity aiScenario = aiScenarioService.getOne(scenarioWrapper);
AssertUtils.notNull(aiScenario, ResultCodeEnum.SCENARIO_NOT_FOUND);
LambdaQueryWrapper<AiScenarioConfigEntity> configWrapper = new LambdaQueryWrapper<>();
configWrapper.eq(AiScenarioConfigEntity::getScenarioId, aiScenario.getId());
configWrapper.eq(AiScenarioConfigEntity::getEnabled, CommonConstant.ENABLE);
configWrapper.orderByAsc(AiScenarioConfigEntity::getPriority);
return super.getOne(configWrapper);
}
} }