- 规范sentry数据收集标签

- 添加切割时间点结束时间必须大于开始时间的检查

.runtime.env

@@ -1,4 +1,4 @@
-MODAL_ENVIRONMENT=dev
+MODAL_ENVIRONMENT=test
 modal_app_name=bowong-ai-video
 S3_mount_dir=/mntS3
 S3_bucket_name=modal-media-cache

src/BowongModalFunctions/models/ffmpeg_worker_model.py

@@ -1,5 +1,5 @@
 from typing import Union, Any
-from pydantic import BaseModel, Field, computed_field, field_validator
+from pydantic import BaseModel, Field, computed_field, field_validator, model_validator
 from pydantic.json_schema import JsonSchemaValue
 from ..utils.TimeUtils import TimeDelta
 
@@ -43,6 +43,12 @@ class FFMpegSliceSegment(BaseModel):
         else:
             raise TypeError(v)
 
+    @model_validator(mode='after')
+    def validate_end_after_start(self) -> 'FFMpegSliceSegment':
+        if self.end <= self.start:
+            raise ValueError("end time must be greater than start time")
+        return self
+
     @classmethod
     def __get_pydantic_json_schema__(cls, core_schema: Any, handler: Any) -> JsonSchemaValue:
         # Override the schema to represent it as a string

src/BowongModalFunctions/models/media_model.py

@@ -201,7 +201,14 @@ class MediaSources(BaseModel):
     @classmethod
     def parse_inputs(cls, v: Union[str, MediaSource]) -> List[MediaSource]:
         if not v:
-            raise ValidationError("inputs为空")
+            raise ValidationError([
+                {
+                    'loc': ('inputs',),
+                    'msg': "inputs为空",
+                    'type': 'value_error',
+                    'input': v
+                }
+            ], MediaSources)
         result = []
         for item in v:
             if isinstance(item, str):
@@ -209,7 +216,14 @@ class MediaSources(BaseModel):
             elif isinstance(item, MediaSource):
                 result.append(item)
             else:
-                raise ValidationError("inputs元素类型错误: 必须是字符串")
+                raise ValidationError([
+                    {
+                        'loc': ('inputs',),
+                        'msg': "inputs元素类型错误: 必须是字符串",
+                        'type': 'value_error',
+                        'input': v
+                    }
+                ], MediaSources)
         return result
 
     model_config = {

src/BowongModalFunctions/utils/SentryUtils.py

@@ -32,7 +32,7 @@ class SentryUtils:
                                                             op=op,
                                                             name=name)
                 else:
-                    transaction = sentry_sdk.start_transaction(op='modal.function', name='Modal Function直接调用')
+                    transaction = sentry_sdk.start_transaction(op=op, name=name)
                 with transaction:
                     with transaction.start_child(op=op, name=name) as span:
                         cpu_freq, cpu_count, mem = SentryUtils.capture_hardware_info()
@@ -43,23 +43,18 @@ class SentryUtils:
                             'x_trace.id': sentry_trace_id,
                             'x_trace.baggage': sentry_baggage,
                             'cpu.count': cpu_count,
-                            'cpu.frequency': cpu_freq.current / 1000,
+                            'cpu.frequency': f"{cpu_freq.current / 1000:.2f}",
                             'cpu.frequency.format': f"{cpu_freq.current / 1000:.2f} GHz",
                             'memory.available': total_mb,
                             'memory.available.format': f"{total_mb} Mb",
-                            'cloud_resource': {
+                            'modal.cloud.region': os.environ.get('MODAL_REGION', 'unknown'),
-                                "cloud.provider": 'Modal',
+                            'modal.cloud.provider': os.environ.get('MODAL_CLOUD_PROVIDER', 'unknown'),
-                                "type": "cloud_resource"
+                            'modal.task.id': os.environ.get('MODAL_TASK_ID', 'unknown'),
-                            },
+                            'modal.identity.token': os.environ.get('MODAL_IDENTITY_TOKEN', 'unknown'),
-                            'modal': {
+                            'modal.image.id': os.environ.get('MODAL_IMAGE_ID', 'unknown'),
-                                'modal.region': os.environ.get('MODAL_REGION', 'unknown'),
-                                'modal.provider': os.environ.get('MODAL_CLOUD_PROVIDER', 'unknown'),
-                                'modal.task.id': os.environ.get('MODAL_TASK_ID', 'unknown'),
-                                'modal.identity.token': os.environ.get('MODAL_IDENTITY_TOKEN', 'unknown'),
-                                'modal.image.id': os.environ.get('MODAL_IMAGE_ID', 'unknown'),
-                            }
                         })
                         result = func(*args, **kwargs)
+                        span.set_status('ok')
                 return result
 
             return wrapper

src/cluster/ffmpeg_app.py

@@ -156,7 +156,7 @@ with ffmpeg_worker_image.imports():
         List[str], Optional[SentryTransactionInfo]]:
         fn_id = current_function_call_id()
 
-        @SentryUtils.sentry_tracker(name="视频切割任务", op="ffmpeg.slice", fn_id=fn_id,
+        @SentryUtils.sentry_tracker(name="视频文件切割任务", op="ffmpeg.slice.media", fn_id=fn_id,
                                     sentry_trace_id=sentry_trace.x_trace_id if sentry_trace else None,
                                     sentry_baggage=sentry_trace.x_baggage if sentry_trace else None)
         @SentryUtils.webhook_handler(webhook=webhook, func_id=fn_id)
@@ -164,15 +164,15 @@ with ffmpeg_worker_image.imports():
                                        fn_id: str) -> List[FFMPEGResult]:
             cache_filepath = f"{s3_mount}/{media_source.cache_filepath}"
             logger.info(f"从{media_source.urn}切割")
-            for marker in media_markers:
+            for i, marker in enumerate(media_markers):
-                logger.info(f"{marker.start.toFormatStr()} --> {marker.end.toFormatStr()}")
+                logger.info(f"[{i}] {marker.start.toFormatStr()} --> {marker.end.toFormatStr()}")
             segments = await VideoUtils.ffmpeg_slice_media(media_path=cache_filepath,
                                                            media_markers=media_markers,
                                                            output_path=f"{output_path_prefix}/{config.modal_environment}/slice/outputs/{fn_id}/output.mp4")
             return [FFMPEGResult(urn=local_copy_to_s3([segment[0]])[0], metadata=segment[1],
                                  content_length=os.path.getsize(segment[0])) for segment in segments]
 
-        @SentryUtils.sentry_tracker(name="视频切割任务", op="ffmpeg.slice", fn_id=fn_id,
+        @SentryUtils.sentry_tracker(name="直播视频切割任务", op="ffmpeg.slice.stream", fn_id=fn_id,
                                     sentry_trace_id=sentry_trace.x_trace_id if sentry_trace else None,
                                     sentry_baggage=sentry_trace.x_baggage if sentry_trace else None)
         @SentryUtils.webhook_handler(webhook=webhook, func_id=fn_id)