refactor(llm): 将学习率字段类型从 Integer 改为 BigDecimal

- 修改了 FineTuningTaskPageReqVO、FineTuningTaskRespVO 和 FineTuningTaskSaveReqVO 中的 learningRate 字段类型
- 优化了学习率的表示精度，提高了数据准确性

yudao-module-llm/yudao-module-llm-biz/src/main/java/cn/iocoder/yudao/module/llm/controller/admin/finetuningtask/vo/FineTuningTaskPageReqVO.java

@@ -1,6 +1,8 @@
 package cn.iocoder.yudao.module.llm.controller.admin.finetuningtask.vo;
 
 import lombok.*;
+
+import java.math.BigDecimal;
 import java.util.*;
 import io.swagger.v3.oas.annotations.media.Schema;
 import cn.iocoder.yudao.framework.common.pojo.PageParam;
@@ -43,7 +45,7 @@ public class FineTuningTaskPageReqVO extends PageParam {
     private Long dataset;
 
     @Schema(description = "学习率")
-    private Integer learningRate;
+    private BigDecimal learningRate;
 
     @Schema(description = "训练轮数")
     private Integer epoch;
@@ -94,4 +96,4 @@ public class FineTuningTaskPageReqVO extends PageParam {
     @Schema(description ="基础模型服务Id")
     private Long baseModelId;
 
-}
+}

yudao-module-llm/yudao-module-llm-biz/src/main/java/cn/iocoder/yudao/module/llm/controller/admin/finetuningtask/vo/FineTuningTaskRespVO.java

@@ -4,6 +4,8 @@ import cn.iocoder.yudao.module.llm.service.http.vo.AigcFineTuningDetailRespVO;
 import com.alibaba.fastjson.JSONObject;
 import io.swagger.v3.oas.annotations.media.Schema;
 import lombok.*;
+
+import java.math.BigDecimal;
 import java.util.*;
 import org.springframework.format.annotation.DateTimeFormat;
 import java.time.LocalDateTime;
@@ -58,7 +60,7 @@ public class FineTuningTaskRespVO {
 
     @Schema(description = "学习率")
     @ExcelProperty("学习率")
-    private Integer learningRate;
+    private BigDecimal learningRate;
 
     @Schema(description = "训练轮数")
     @ExcelProperty("训练轮数")

yudao-module-llm/yudao-module-llm-biz/src/main/java/cn/iocoder/yudao/module/llm/controller/admin/finetuningtask/vo/FineTuningTaskSaveReqVO.java

@@ -2,6 +2,8 @@ package cn.iocoder.yudao.module.llm.controller.admin.finetuningtask.vo;
 
 import io.swagger.v3.oas.annotations.media.Schema;
 import lombok.*;
+
+import java.math.BigDecimal;
 import java.util.*;
 import javax.validation.constraints.*;
 
@@ -41,7 +43,7 @@ public class FineTuningTaskSaveReqVO {
     private Long dataset;
 
     @Schema(description = "学习率")
-    private Integer learningRate;
+    private BigDecimal learningRate;
 
     @Schema(description = "训练轮数")
     private Integer epoch;
@@ -89,4 +91,4 @@ public class FineTuningTaskSaveReqVO {
     @Schema(description = "基础模型服务Id")
     private Long baseModelId;
 
-}
+}

yudao-module-llm/yudao-module-llm-biz/src/main/java/cn/iocoder/yudao/module/llm/service/http/TrainHttpService.java

@@ -154,6 +154,7 @@ public class TrainHttpService {
         // TODO: 在上个方法中已经将数据集的文件id赋予，调试时需要写死再放开
 //        String fileId = "6237ed4d-a046-479c-80d6-8579a0283994";
 //        req.setFileId(fileId);
+        log.info(" finetuningCreate:{}", JSON.toJSONString(req));
         String res = HttpUtils.post(llmBackendProperties.getFinetuningCreate(), headers, JSON.toJSONString(req));
         log.info(" finetuningCreate:{}", res);
         AigcRespVO aigcRespVO = JSON.parseObject(res, AigcRespVO.class);