use sqlalchemy pattern
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@@ -1,238 +0,0 @@
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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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PROCESSING = "processing"
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COMPLETED = "completed"
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FAILED = "failed"
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CANCELLED = "cancelled"
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class ChunkJobStatus(str, Enum):
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PENDING = "pending"
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CHUNKING = "chunking"
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PROCESSING = "processing"
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COLLECTING = "collecting"
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COMPLETED = "completed"
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FAILED = "failed"
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CANCELLED = "cancelled"
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class DetectJobStatus(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 TranscodeJob(SQLModel, table=True):
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"""A transcoding or trimming job in the queue."""
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__tablename__ = "transcode_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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preset_id: Optional[UUID] = None
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preset_snapshot: Dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON, nullable=False, server_default='{}'))
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trim_start: Optional[float] = None
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trim_end: Optional[float] = None
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output_filename: str = ""
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output_path: Optional[str] = None
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output_asset_id: Optional[UUID] = None
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status: JobStatus = "pending"
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progress: float = 0.0
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current_frame: Optional[int] = None
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current_time: Optional[float] = None
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speed: Optional[str] = None
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error_message: Optional[str] = None
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celery_task_id: Optional[str] = None
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execution_arn: 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 ChunkJob(SQLModel, table=True):
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"""A chunk pipeline job — splits a media file into chunks and processes them"""
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__tablename__ = "chunk_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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chunk_duration: float = 10.0
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num_workers: int = 4
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max_retries: int = 3
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processor_type: str = "ffmpeg"
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status: ChunkJobStatus = "pending"
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progress: float = 0.0
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total_chunks: int = 0
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processed_chunks: int = 0
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failed_chunks: int = 0
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retry_count: int = 0
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error_message: Optional[str] = None
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throughput_mbps: Optional[float] = None
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elapsed_seconds: Optional[float] = None
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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 DetectJob(SQLModel, table=True):
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"""A detection pipeline job."""
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__tablename__ = "detect_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_job_id: Optional[UUID] = Field(default=None, index=True)
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run_type: RunType = "initial"
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replay_from_stage: Optional[str] = None
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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: DetectJobStatus = "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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"""Frame sequence from a source video. Independent of stages."""
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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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"""Snapshot of pipeline state. parent_id forms a tree."""
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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 = Field(index=True)
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parent_id: Optional[UUID] = Field(default=None, index=True)
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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 KnownBrand(SQLModel, table=True):
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"""A brand discovered or registered in the system."""
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__tablename__ = "known_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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first_source: BrandSource = "ocr"
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total_occurrences: int = 0
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confirmed: bool = False
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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 SourceBrandSighting(SQLModel, table=True):
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"""A brand seen in a specific source (video/asset)."""
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__tablename__ = "source_brand_sightings"
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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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brand_id: UUID
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brand_name: str
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first_seen_timestamp: float = 0.0
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last_seen_timestamp: float = 0.0
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occurrences: int = 0
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detection_source: BrandSource = "ocr"
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avg_confidence: float = 0.0
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created_at: Optional[datetime] = Field(default_factory=datetime.utcnow)
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