chore(controller): rename for finetune info

client/starwhale/api/_impl/experiment.py

@@ -8,6 +8,7 @@
 from starwhale.consts import DecoratorInjectAttr
 from starwhale.base.context import Context
 from starwhale.api._impl.model import build as build_starwhale_model
+from starwhale.base.client.models.models import FineTune
 
 
 # TODO: support arguments
@@ -117,10 +118,12 @@ def _register_ft(
         needs=needs,
         require_dataset=require_train_datasets or require_validation_datasets,
         extra_kwargs=dict(
-            require_train_datasets=require_train_datasets,
-            require_validation_datasets=require_validation_datasets,
             auto_build_model=auto_build_model,
         ),
         built_in=True,
+        fine_tune=FineTune(
+            require_train_datasets=require_train_datasets,
+            require_validation_datasets=require_validation_datasets,
+        ),
     )(func)
     setattr(func, DecoratorInjectAttr.FineTune, True)

client/starwhale/api/_impl/job/handler.py

@@ -18,7 +18,11 @@
 from starwhale.utils.error import NoSupportError
 from starwhale.base.models.model import StepSpecClient
 from starwhale.api._impl.evaluation import PipelineHandler
-from starwhale.base.client.models.models import RuntimeResource, ParameterSignature
+from starwhale.base.client.models.models import (
+    FineTune,
+    RuntimeResource,
+    ParameterSignature,
+)
 
 
 class Handler(StepSpecClient):
@@ -100,6 +104,7 @@ def register(
         expose: int = 0,
         require_dataset: bool = False,
         built_in: bool = False,
+        fine_tune: FineTune | None = None,
     ) -> t.Callable:
         """Register a function as a handler. Enable the function execute by needs handler, run with gpu/cpu/mem resources in server side,
         and control replicas of handler run.
@@ -119,6 +124,7 @@ def register(
               If True, You must select datasets when executing on the server or cloud instance.
             built_in: [bool, optional] A special flag to distinguish user defined args in handler function from the StarWhale ones.
               This should always be False unless you know what it does.
+            fine_tune: [FineTune, optional The fine tune config for the handler. Default is None.
 
         Example:
         ```python
@@ -195,6 +201,7 @@ def decorator(func: t.Callable) -> t.Callable:
                 require_dataset=require_dataset,
                 parameters_sig=parameters_sig,
                 ext_cmd_args=ext_cmd_args,
+                fine_tune=fine_tune,
             )
 
             cls._register(_handler, func)

client/starwhale/base/client/models/models.py

@@ -725,6 +725,11 @@ class Env(SwBaseModel):
     value: Optional[str] = None
 
 
+class FineTune(SwBaseModel):
+    require_train_datasets: Optional[bool] = None
+    require_validation_datasets: Optional[bool] = None
+
+
 class ParameterSignature(SwBaseModel):
     name: str
     required: Optional[bool] = None
@@ -750,8 +755,7 @@ class StepSpec(SwBaseModel):
     job_name: Optional[str] = None
     show_name: str
     require_dataset: Optional[bool] = None
-    require_train_datasets: Optional[bool] = None
-    require_validation_datasets: Optional[bool] = None
+    fine_tune: Optional[FineTune] = None
     container_spec: Optional[ContainerSpec] = None
     ext_cmd_args: Optional[str] = None
     parameters_sig: Optional[List[ParameterSignature]] = None
@@ -914,6 +918,14 @@ class ExposedLinkVo(SwBaseModel):
     link: str
 
 
+class JobType(Enum):
+    evaluation = 'EVALUATION'
+    train = 'TRAIN'
+    fine_tune = 'FINE_TUNE'
+    serving = 'SERVING'
+    built_in = 'BUILT_IN'
+
+
 class JobStatus(Enum):
     created = 'CREATED'
     ready = 'READY'
@@ -934,6 +946,7 @@ class JobVo(SwBaseModel):
     model_version: str = Field(..., alias='modelVersion')
     model: ModelVo
     job_name: Optional[str] = Field(None, alias='jobName')
+    job_type: Optional[JobType] = Field(None, alias='jobType')
     datasets: Optional[List[str]] = None
     dataset_list: Optional[List[DatasetVo]] = Field(None, alias='datasetList')
     runtime: RuntimeVo

client/tests/sdk/test_job_handler.py

@@ -12,7 +12,11 @@
 from starwhale.base.scheduler import Step, Scheduler, TaskExecutor
 from starwhale.base.uri.project import Project
 from starwhale.base.models.model import JobHandlers, StepSpecClient
-from starwhale.base.client.models.models import RuntimeResource, ParameterSignature
+from starwhale.base.client.models.models import (
+    FineTune,
+    RuntimeResource,
+    ParameterSignature,
+)
 
 
 class JobTestCase(unittest.TestCase):
@@ -782,9 +786,11 @@ def ft2(): ...
                     ext_cmd_args="",
                     extra_kwargs={
                         "auto_build_model": True,
-                        "require_train_datasets": True,
-                        "require_validation_datasets": True,
                     },
+                    fine_tune=FineTune(
+                        require_train_datasets=True,
+                        require_validation_datasets=True,
+                    ),
                 ),
             ],
             "mock_user_module:ft2": [
@@ -803,9 +809,11 @@ def ft2(): ...
                     ext_cmd_args="",
                     extra_kwargs={
                         "auto_build_model": True,
-                        "require_train_datasets": True,
-                        "require_validation_datasets": True,
                     },
+                    fine_tune=FineTune(
+                        require_train_datasets=True,
+                        require_validation_datasets=True,
+                    ),
                 ),
                 StepSpecClient(
                     name="mock_user_module:ft2",
@@ -828,9 +836,11 @@ def ft2(): ...
                     ext_cmd_args="",
                     extra_kwargs={
                         "auto_build_model": False,
-                        "require_train_datasets": False,
-                        "require_validation_datasets": False,
                     },
+                    fine_tune=FineTune(
+                        require_train_datasets=False,
+                        require_validation_datasets=False,
+                    ),
                 ),
             ],
         }

server/controller/src/main/java/ai/starwhale/mlops/api/protocol/job/JobVo.java

@@ -20,6 +20,7 @@
 import ai.starwhale.mlops.api.protocol.model.ModelVo;
 import ai.starwhale.mlops.api.protocol.runtime.RuntimeVo;
 import ai.starwhale.mlops.api.protocol.user.UserVo;
+import ai.starwhale.mlops.domain.job.JobType;
 import ai.starwhale.mlops.domain.job.status.JobStatus;
 import com.fasterxml.jackson.annotation.JsonProperty;
 import io.swagger.v3.oas.annotations.media.Schema;
@@ -60,6 +61,9 @@ public class JobVo implements Serializable {
     @JsonProperty("jobName")
     private String jobName;
 
+    @JsonProperty("jobType")
+    private JobType jobType;
+
     @JsonProperty("datasets")
     @Valid
     private List<String> datasets;

server/controller/src/main/java/ai/starwhale/mlops/domain/job/converter/JobConverter.java

@@ -192,6 +192,7 @@ public JobVo convert(JobEntity jobEntity) throws ConvertException {
 
         return JobVo.builder()
                 .id(idConvertor.convert(jobEntity.getId()))
+                .jobType(jobEntity.getType())
                 .uuid(jobEntity.getJobUuid())
                 .owner(UserVo.fromEntity(jobEntity.getOwner(), idConvertor))
                 .modelName(jobEntity.getModelName())

server/controller/src/main/java/ai/starwhale/mlops/domain/job/spec/StepSpec.java

@@ -84,17 +84,15 @@ public class StepSpec {
 
     @Data
     @JsonIgnoreProperties(ignoreUnknown = true)
-    public static class ExtraParams {
-        @JsonProperty("auto_build_model")
-        private Boolean autoBuildModel;
+    public static class FineTune {
         @JsonProperty("require_train_datasets")
         private Boolean requireTrainDatasets;
         @JsonProperty("require_validation_datasets")
         private Boolean requireValidationDatasets;
     }
 
-    @JsonProperty("extra_kwargs")
-    private ExtraParams extraParams;
+    @JsonProperty("fine_tune")
+    private FineTune finetune;
 
     @JsonProperty("container_spec")
     ContainerSpec containerSpec;

server/controller/src/test/java/ai/starwhale/mlops/domain/job/JobParserTest.java

@@ -57,8 +57,7 @@ public void testParseFromYamlContent() throws JsonProcessingException {
                 + "  resources: []\n"
                 + "  name: mnist.evaluator:MNISTInference.ppl\n"
                 + "  replicas: 1\n"
-                + "  extra_kwargs:\n"
-                + "    auto_build_model: true\n"
+                + "  fine_tune:\n"
                 + "    require_train_datasets: true\n"
                 + "    require_validation_datasets: false\n"
                 + "  env:\n"
@@ -81,7 +80,7 @@ public void testParseFromYamlContent() throws JsonProcessingException {
                 new Env("EVAL_DATASET", "imagenet"),
                 new Env("EVAL_MODEL", "resnet50")
             ));
-        Assertions.assertTrue(stepMetaDatas.get(2).getExtraParams().getRequireTrainDatasets());
-        Assertions.assertFalse(stepMetaDatas.get(2).getExtraParams().getRequireValidationDatasets());
+        Assertions.assertTrue(stepMetaDatas.get(2).getFinetune().getRequireTrainDatasets());
+        Assertions.assertFalse(stepMetaDatas.get(2).getFinetune().getRequireValidationDatasets());
     }
 }