phase 3
This commit is contained in:
@@ -13,22 +13,6 @@ class AssetStatus(models.TextChoices):
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ERROR = "error", "Error"
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class JobStatus(models.TextChoices):
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PENDING = "pending", "Pending"
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PROCESSING = "processing", "Processing"
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COMPLETED = "completed", "Completed"
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FAILED = "failed", "Failed"
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CANCELLED = "cancelled", "Cancelled"
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class ChunkJobStatus(models.TextChoices):
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PENDING = "pending", "Pending"
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CHUNKING = "chunking", "Chunking"
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PROCESSING = "processing", "Processing"
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COLLECTING = "collecting", "Collecting"
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COMPLETED = "completed", "Completed"
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FAILED = "failed", "Failed"
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CANCELLED = "cancelled", "Cancelled"
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class DetectJobStatus(models.TextChoices):
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PENDING = "pending", "Pending"
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RUNNING = "running", "Running"
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PAUSED = "paused", "Paused"
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@@ -111,81 +95,17 @@ class TranscodePreset(models.Model):
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return self.name
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class TranscodeJob(models.Model):
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"""A transcoding or trimming job in the queue."""
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id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
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source_asset_id = models.UUIDField()
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preset_id = models.UUIDField(null=True, blank=True)
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preset_snapshot = models.JSONField(default=dict, blank=True)
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trim_start = models.FloatField(null=True, blank=True, default=None)
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trim_end = models.FloatField(null=True, blank=True, default=None)
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output_filename = models.CharField(max_length=500)
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output_path = models.CharField(max_length=1000, null=True, blank=True)
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output_asset_id = models.UUIDField(null=True, blank=True)
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status = models.CharField(max_length=20, choices=JobStatus.choices, default=JobStatus.PENDING)
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progress = models.FloatField(default=0.0)
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current_frame = models.IntegerField(null=True, blank=True, default=None)
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current_time = models.FloatField(null=True, blank=True, default=None)
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speed = models.CharField(max_length=255, null=True, blank=True)
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error_message = models.TextField(blank=True, default='')
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celery_task_id = models.CharField(max_length=255, null=True, blank=True)
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execution_arn = models.CharField(max_length=255, null=True, blank=True)
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priority = models.IntegerField(default=0)
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created_at = models.DateTimeField(auto_now_add=True)
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started_at = models.DateTimeField(null=True, blank=True)
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completed_at = models.DateTimeField(null=True, blank=True)
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class Meta:
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ordering = ["-created_at"]
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def __str__(self):
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return str(self.id)
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class ChunkJob(models.Model):
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"""A chunk pipeline job — splits a media file into chunks and processes them"""
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id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
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source_asset_id = models.UUIDField()
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chunk_duration = models.FloatField(default=10.0)
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num_workers = models.IntegerField(default=4)
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max_retries = models.IntegerField(default=3)
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processor_type = models.CharField(max_length=255)
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status = models.CharField(max_length=20, choices=ChunkJobStatus.choices, default=ChunkJobStatus.PENDING)
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progress = models.FloatField(default=0.0)
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total_chunks = models.IntegerField(default=0)
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processed_chunks = models.IntegerField(default=0)
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failed_chunks = models.IntegerField(default=0)
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retry_count = models.IntegerField(default=0)
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error_message = models.TextField(blank=True, default='')
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throughput_mbps = models.FloatField(null=True, blank=True, default=None)
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elapsed_seconds = models.FloatField(null=True, blank=True, default=None)
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celery_task_id = models.CharField(max_length=255, null=True, blank=True)
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priority = models.IntegerField(default=0)
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created_at = models.DateTimeField(auto_now_add=True)
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started_at = models.DateTimeField(null=True, blank=True)
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completed_at = models.DateTimeField(null=True, blank=True)
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class Meta:
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ordering = ["-created_at"]
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def __str__(self):
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return str(self.id)
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class DetectJob(models.Model):
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"""A detection pipeline job."""
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class Job(models.Model):
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"""A pipeline job."""
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id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
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source_asset_id = models.UUIDField()
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video_path = models.CharField(max_length=1000)
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profile_name = models.CharField(max_length=255)
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parent_job_id = models.UUIDField(null=True, blank=True)
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parent_id = models.UUIDField(null=True, blank=True)
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run_type = models.CharField(max_length=20, choices=RunType.choices, default=RunType.INITIAL)
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replay_from_stage = models.CharField(max_length=255, null=True, blank=True)
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config_overrides = models.JSONField(default=dict, blank=True)
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status = models.CharField(max_length=20, choices=DetectJobStatus.choices, default=DetectJobStatus.PENDING)
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status = models.CharField(max_length=20, choices=JobStatus.choices, default=JobStatus.PENDING)
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current_stage = models.CharField(max_length=255, null=True, blank=True)
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progress = models.FloatField(default=0.0)
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error_message = models.TextField(blank=True, default='')
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@@ -206,26 +126,17 @@ class DetectJob(models.Model):
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return str(self.id)
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class StageCheckpoint(models.Model):
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"""A checkpoint saved after a pipeline stage completes."""
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class Timeline(models.Model):
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"""The frame sequence from a source video."""
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id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
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job_id = models.UUIDField()
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stage = models.CharField(max_length=255)
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stage_index = models.IntegerField()
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source_asset_id = models.UUIDField(null=True, blank=True)
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source_video = models.CharField(max_length=255)
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profile_name = models.CharField(max_length=255)
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fps = models.FloatField(default=2.0)
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frames_prefix = models.CharField(max_length=255)
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frames_manifest = models.JSONField(default=dict, blank=True)
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frames_meta = models.JSONField(default=list, blank=True)
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filtered_frame_sequences = models.JSONField(default=list, blank=True)
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boxes_by_frame = models.JSONField(default=dict, blank=True)
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text_candidates = models.JSONField(default=list, blank=True)
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unresolved_candidates = models.JSONField(default=list, blank=True)
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detections = models.JSONField(default=list, blank=True)
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stats = models.JSONField(default=dict, blank=True)
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config_snapshot = models.JSONField(default=dict, blank=True)
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config_overrides = models.JSONField(default=dict, blank=True)
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video_path = models.CharField(max_length=1000)
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profile_name = models.CharField(max_length=255)
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created_at = models.DateTimeField(auto_now_add=True)
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class Meta:
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@@ -235,15 +146,36 @@ class StageCheckpoint(models.Model):
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return str(self.id)
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class KnownBrand(models.Model):
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class Checkpoint(models.Model):
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"""A snapshot of pipeline state on a timeline."""
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id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
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timeline_id = models.UUIDField()
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parent_id = models.UUIDField(null=True, blank=True)
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stage_outputs = models.JSONField(default=dict, blank=True)
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config_overrides = models.JSONField(default=dict, blank=True)
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stats = models.JSONField(default=dict, blank=True)
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is_scenario = models.BooleanField(default=False)
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scenario_label = models.CharField(max_length=255)
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created_at = models.DateTimeField(auto_now_add=True)
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class Meta:
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ordering = ["-created_at"]
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def __str__(self):
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return str(self.id)
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class Brand(models.Model):
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"""A brand discovered or registered in the system."""
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id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
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canonical_name = models.CharField(max_length=255)
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aliases = models.JSONField(default=list, blank=True)
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first_source = models.CharField(max_length=20, choices=BrandSource.choices, default=BrandSource.OCR)
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total_occurrences = models.IntegerField(default=0)
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source = models.CharField(max_length=20, choices=BrandSource.choices, default=BrandSource.OCR)
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confirmed = models.BooleanField(default=False)
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airings = models.JSONField(default=list, blank=True)
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total_airings = models.IntegerField(default=0)
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created_at = models.DateTimeField(auto_now_add=True)
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updated_at = models.DateTimeField(auto_now=True)
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@@ -253,24 +185,3 @@ class KnownBrand(models.Model):
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def __str__(self):
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return str(self.id)
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class SourceBrandSighting(models.Model):
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"""A brand seen in a specific source (video/asset)."""
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id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
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source_asset_id = models.UUIDField()
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brand_id = models.UUIDField()
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brand_name = models.CharField(max_length=255)
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first_seen_timestamp = models.FloatField(default=0.0)
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last_seen_timestamp = models.FloatField(default=0.0)
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occurrences = models.IntegerField(default=0)
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detection_source = models.CharField(max_length=20, choices=BrandSource.choices, default=BrandSource.OCR)
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avg_confidence = models.FloatField(default=0.0)
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created_at = models.DateTimeField(auto_now_add=True)
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class Meta:
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ordering = ["-created_at"]
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def __str__(self):
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return str(self.id)
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156
core/db/models.py
Normal file
156
core/db/models.py
Normal file
@@ -0,0 +1,156 @@
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"""
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SQLModel Table Models - GENERATED FILE
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Do not edit directly. Regenerate using modelgen.
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"""
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from datetime import datetime
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from enum import Enum
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from typing import Any, Dict, List, Optional
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from uuid import UUID, uuid4
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from sqlmodel import SQLModel, Field, Column
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from sqlalchemy import JSON
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class AssetStatus(str, Enum):
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PENDING = "pending"
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READY = "ready"
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ERROR = "error"
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class JobStatus(str, Enum):
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PENDING = "pending"
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RUNNING = "running"
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PAUSED = "paused"
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COMPLETED = "completed"
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FAILED = "failed"
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CANCELLED = "cancelled"
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class RunType(str, Enum):
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INITIAL = "initial"
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REPLAY = "replay"
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RETRY = "retry"
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class BrandSource(str, Enum):
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OCR = "ocr"
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VLM = "local_vlm"
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CLOUD = "cloud_llm"
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MANUAL = "manual"
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class SourceType(str, Enum):
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CHUNK_JOB = "chunk_job"
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UPLOAD = "upload"
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DEVICE = "device"
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STREAM = "stream"
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class MediaAsset(SQLModel, table=True):
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"""A video/audio file registered in the system."""
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__tablename__ = "media_assets"
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id: UUID = Field(default_factory=uuid4, primary_key=True)
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filename: str
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file_path: str
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status: AssetStatus = "pending"
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error_message: Optional[str] = None
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file_size: Optional[int] = None
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duration: Optional[float] = None
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video_codec: Optional[str] = None
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audio_codec: Optional[str] = None
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width: Optional[int] = None
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height: Optional[int] = None
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framerate: Optional[float] = None
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bitrate: Optional[int] = None
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properties: Dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON, nullable=False, server_default='{}'))
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comments: str = ""
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tags: List[str] = Field(default_factory=list, sa_column=Column(JSON, nullable=False, server_default='[]'))
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created_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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updated_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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class TranscodePreset(SQLModel, table=True):
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"""A reusable transcoding configuration (like Handbrake presets)."""
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__tablename__ = "transcode_presets"
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id: UUID = Field(default_factory=uuid4, primary_key=True)
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name: str
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description: str = ""
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is_builtin: bool = False
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container: str = "mp4"
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video_codec: str = "libx264"
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video_bitrate: Optional[str] = None
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video_crf: Optional[int] = None
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video_preset: Optional[str] = None
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resolution: Optional[str] = None
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framerate: Optional[float] = None
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audio_codec: str = "aac"
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audio_bitrate: Optional[str] = None
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audio_channels: Optional[int] = None
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audio_samplerate: Optional[int] = None
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extra_args: List[str] = Field(default_factory=list, sa_column=Column(JSON, nullable=False, server_default='[]'))
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created_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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updated_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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class Job(SQLModel, table=True):
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"""A pipeline job."""
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__tablename__ = "jobs"
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id: UUID = Field(default_factory=uuid4, primary_key=True)
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source_asset_id: UUID = Field(index=True)
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video_path: str
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profile_name: str = "soccer_broadcast"
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parent_id: Optional[UUID] = None
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run_type: RunType = "initial"
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config_overrides: Dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON, nullable=False, server_default='{}'))
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status: JobStatus = "pending"
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current_stage: Optional[str] = None
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progress: float = 0.0
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error_message: Optional[str] = None
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total_detections: int = 0
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brands_found: int = 0
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cloud_llm_calls: int = 0
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estimated_cost_usd: float = 0.0
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celery_task_id: Optional[str] = None
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priority: int = 0
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created_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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started_at: Optional[datetime] = None
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completed_at: Optional[datetime] = None
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class Timeline(SQLModel, table=True):
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"""The frame sequence from a source video."""
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__tablename__ = "timelines"
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id: UUID = Field(default_factory=uuid4, primary_key=True)
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source_asset_id: Optional[UUID] = Field(default=None, index=True)
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source_video: str = ""
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profile_name: str = ""
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fps: float = 2.0
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frames_prefix: str = ""
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frames_manifest: Dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON, nullable=False, server_default='{}'))
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frames_meta: List[str] = Field(default_factory=list, sa_column=Column(JSON, nullable=False, server_default='[]'))
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created_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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class Checkpoint(SQLModel, table=True):
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"""A snapshot of pipeline state on a timeline."""
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__tablename__ = "checkpoints"
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id: UUID = Field(default_factory=uuid4, primary_key=True)
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timeline_id: UUID
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parent_id: Optional[UUID] = None
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stage_outputs: Dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON, nullable=False, server_default='{}'))
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config_overrides: Dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON, nullable=False, server_default='{}'))
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stats: Dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON, nullable=False, server_default='{}'))
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is_scenario: bool = False
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scenario_label: str = ""
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created_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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class Brand(SQLModel, table=True):
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"""A brand discovered or registered in the system."""
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__tablename__ = "brands"
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id: UUID = Field(default_factory=uuid4, primary_key=True)
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canonical_name: str = Field(index=True)
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aliases: List[str] = Field(default_factory=list, sa_column=Column(JSON, nullable=False, server_default='[]'))
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source: BrandSource = "ocr"
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confirmed: bool = False
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airings: List[str] = Field(default_factory=list, sa_column=Column(JSON, nullable=False, server_default='[]'))
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total_airings: int = 0
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created_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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updated_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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@@ -94,6 +94,9 @@ class StatsUpdate:
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cloud_llm_calls: int = 0
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processing_time_seconds: float = 0.0
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estimated_cloud_cost_usd: float = 0.0
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run_id: Optional[str] = None
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parent_job_id: Optional[str] = None
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run_type: str = "initial"
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@dataclass
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@@ -63,6 +63,9 @@ class StatsUpdate(BaseModel):
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cloud_llm_calls: int = 0
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processing_time_seconds: float = 0.0
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estimated_cloud_cost_usd: float = 0.0
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run_id: Optional[str] = None
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parent_job_id: Optional[str] = None
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run_type: str = "initial"
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class FrameUpdate(BaseModel):
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"""Current frame being processed. SSE event: frame_update"""
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@@ -113,6 +116,8 @@ class RunContext(BaseModel):
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class CheckpointInfo(BaseModel):
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"""Available checkpoint for a stage."""
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stage: str
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is_scenario: bool = False
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scenario_label: str = ""
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class ReplayRequest(BaseModel):
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"""Request to replay pipeline from a specific stage."""
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@@ -5,9 +5,7 @@
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*/
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export type AssetStatus = "pending" | "ready" | "error";
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export type JobStatus = "pending" | "processing" | "completed" | "failed" | "cancelled";
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export type ChunkJobStatus = "pending" | "chunking" | "processing" | "collecting" | "completed" | "failed" | "cancelled";
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export type DetectJobStatus = "pending" | "running" | "paused" | "completed" | "failed" | "cancelled";
|
||||
export type JobStatus = "pending" | "running" | "paused" | "completed" | "failed" | "cancelled";
|
||||
export type RunType = "initial" | "replay" | "retry";
|
||||
export type BrandSource = "ocr" | "local_vlm" | "cloud_llm" | "manual";
|
||||
export type SourceType = "chunk_job" | "upload" | "device" | "stream";
|
||||
@@ -54,63 +52,15 @@ export interface TranscodePreset {
|
||||
updated_at: string | null;
|
||||
}
|
||||
|
||||
export interface TranscodeJob {
|
||||
id: string;
|
||||
source_asset_id: string;
|
||||
preset_id: string | null;
|
||||
preset_snapshot: Record<string, unknown>;
|
||||
trim_start: number | null;
|
||||
trim_end: number | null;
|
||||
output_filename: string;
|
||||
output_path: string | null;
|
||||
output_asset_id: string | null;
|
||||
status: JobStatus;
|
||||
progress: number;
|
||||
current_frame: number | null;
|
||||
current_time: number | null;
|
||||
speed: string | null;
|
||||
error_message: string | null;
|
||||
celery_task_id: string | null;
|
||||
execution_arn: string | null;
|
||||
priority: number;
|
||||
created_at: string | null;
|
||||
started_at: string | null;
|
||||
completed_at: string | null;
|
||||
}
|
||||
|
||||
export interface ChunkJob {
|
||||
id: string;
|
||||
source_asset_id: string;
|
||||
chunk_duration: number;
|
||||
num_workers: number;
|
||||
max_retries: number;
|
||||
processor_type: string;
|
||||
status: ChunkJobStatus;
|
||||
progress: number;
|
||||
total_chunks: number;
|
||||
processed_chunks: number;
|
||||
failed_chunks: number;
|
||||
retry_count: number;
|
||||
error_message: string | null;
|
||||
throughput_mbps: number | null;
|
||||
elapsed_seconds: number | null;
|
||||
celery_task_id: string | null;
|
||||
priority: number;
|
||||
created_at: string | null;
|
||||
started_at: string | null;
|
||||
completed_at: string | null;
|
||||
}
|
||||
|
||||
export interface DetectJob {
|
||||
export interface Job {
|
||||
id: string;
|
||||
source_asset_id: string;
|
||||
video_path: string;
|
||||
profile_name: string;
|
||||
parent_job_id: string | null;
|
||||
parent_id: string | null;
|
||||
run_type: RunType;
|
||||
replay_from_stage: string | null;
|
||||
config_overrides: Record<string, unknown>;
|
||||
status: DetectJobStatus;
|
||||
status: JobStatus;
|
||||
current_stage: string | null;
|
||||
progress: number;
|
||||
error_message: string | null;
|
||||
@@ -125,51 +75,42 @@ export interface DetectJob {
|
||||
completed_at: string | null;
|
||||
}
|
||||
|
||||
export interface StageCheckpoint {
|
||||
export interface Timeline {
|
||||
id: string;
|
||||
job_id: string;
|
||||
stage: string;
|
||||
stage_index: number;
|
||||
source_asset_id: string | null;
|
||||
source_video: string;
|
||||
profile_name: string;
|
||||
fps: number;
|
||||
frames_prefix: string;
|
||||
frames_manifest: Record<string, unknown>;
|
||||
frames_meta: string[];
|
||||
filtered_frame_sequences: number[];
|
||||
boxes_by_frame: Record<string, unknown>;
|
||||
text_candidates: string[];
|
||||
unresolved_candidates: string[];
|
||||
detections: string[];
|
||||
stats: Record<string, unknown>;
|
||||
config_snapshot: Record<string, unknown>;
|
||||
config_overrides: Record<string, unknown>;
|
||||
video_path: string;
|
||||
profile_name: string;
|
||||
created_at: string | null;
|
||||
}
|
||||
|
||||
export interface KnownBrand {
|
||||
export interface Checkpoint {
|
||||
id: string;
|
||||
timeline_id: string;
|
||||
parent_id: string | null;
|
||||
stage_outputs: Record<string, unknown>;
|
||||
config_overrides: Record<string, unknown>;
|
||||
stats: Record<string, unknown>;
|
||||
is_scenario: boolean;
|
||||
scenario_label: string;
|
||||
created_at: string | null;
|
||||
}
|
||||
|
||||
export interface Brand {
|
||||
id: string;
|
||||
canonical_name: string;
|
||||
aliases: string[];
|
||||
first_source: BrandSource;
|
||||
total_occurrences: number;
|
||||
source: BrandSource;
|
||||
confirmed: boolean;
|
||||
airings: string[];
|
||||
total_airings: number;
|
||||
created_at: string | null;
|
||||
updated_at: string | null;
|
||||
}
|
||||
|
||||
export interface SourceBrandSighting {
|
||||
id: string;
|
||||
source_asset_id: string;
|
||||
brand_id: string;
|
||||
brand_name: string;
|
||||
first_seen_timestamp: number;
|
||||
last_seen_timestamp: number;
|
||||
occurrences: number;
|
||||
detection_source: BrandSource;
|
||||
avg_confidence: number;
|
||||
created_at: string | null;
|
||||
}
|
||||
|
||||
export interface CreateJobRequest {
|
||||
source_asset_id: string;
|
||||
preset_id: string | null;
|
||||
|
||||
@@ -42,9 +42,9 @@ source.on<StatsUpdate>('stats_update', (e) => {
|
||||
stats.value = e
|
||||
if (!runContext.value && e.run_id) {
|
||||
runContext.value = {
|
||||
run_id: (e as any).run_id,
|
||||
parent_job_id: (e as any).parent_job_id,
|
||||
run_type: (e as any).run_type ?? 'initial',
|
||||
run_id: e.run_id!,
|
||||
parent_job_id: e.parent_job_id!,
|
||||
run_type: e.run_type ?? 'initial',
|
||||
}
|
||||
}
|
||||
})
|
||||
@@ -267,8 +267,10 @@ const editorOverlays = ref<FrameOverlay[]>([])
|
||||
// Boxes from edge detection (local or server)
|
||||
const editorBoxes = ref<FrameBBox[]>([])
|
||||
|
||||
type RegionBox = { x: number; y: number; w: number; h: number; confidence: number; label: string }
|
||||
|
||||
function onReplayResult(result: {
|
||||
regions_by_frame?: Record<string, unknown[]>
|
||||
regions_by_frame?: Record<string, RegionBox[]>
|
||||
debug?: Record<string, { edge_overlay_b64: string; lines_overlay_b64: string; horizontal_count: number; pair_count: number }>
|
||||
frameWidth?: number
|
||||
frameHeight?: number
|
||||
@@ -281,7 +283,7 @@ function onReplayResult(result: {
|
||||
// Merge incoming per-frame regions into accumulated store
|
||||
if (result.regions_by_frame) {
|
||||
for (const [seqStr, regions] of Object.entries(result.regions_by_frame)) {
|
||||
allFrameRegions.value[Number(seqStr)] = regions as any[]
|
||||
allFrameRegions.value[Number(seqStr)] = regions
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -56,6 +56,9 @@ export interface StatsUpdate {
|
||||
cloud_llm_calls: number;
|
||||
processing_time_seconds: number;
|
||||
estimated_cloud_cost_usd: number;
|
||||
run_id: string | null;
|
||||
parent_job_id: string | null;
|
||||
run_type: string;
|
||||
}
|
||||
|
||||
export interface FrameUpdate {
|
||||
|
||||
@@ -53,19 +53,7 @@ export interface PreprocessingConfigOverrides {
|
||||
contrast: boolean | null;
|
||||
}
|
||||
|
||||
export interface RegionAnalysisConfigOverrides {
|
||||
enabled: boolean | null;
|
||||
edge_canny_low: number | null;
|
||||
edge_canny_high: number | null;
|
||||
edge_hough_threshold: number | null;
|
||||
edge_hough_min_length: number | null;
|
||||
edge_hough_max_gap: number | null;
|
||||
edge_pair_max_distance: number | null;
|
||||
edge_pair_min_distance: number | null;
|
||||
}
|
||||
|
||||
export interface ConfigOverrides {
|
||||
region_analysis: RegionAnalysisConfigOverrides | null;
|
||||
detection: DetectionConfigOverrides | null;
|
||||
ocr: OCRConfigOverrides | null;
|
||||
resolver: ResolverConfigOverrides | null;
|
||||
|
||||
Reference in New Issue
Block a user