phase 1

core/schema/models/__init__.py

@@ -35,6 +35,7 @@ from .detect import DETECT_VIEWS  # noqa: F401 — discovered by modelgen generi
 from .inference import INFERENCE_VIEWS  # noqa: F401 — GPU inference server API types
 from .ui_state import UI_STATE_VIEWS  # noqa: F401 — UI store state types
 from .stages import StageConfigField, StageIO, StageDefinition, STAGE_VIEWS  # noqa: F401
+from .detect_api import RunRequest, RunResponse, DETECT_API_VIEWS  # noqa: F401
 from .views import ChunkEvent, ChunkOutputFile, PipelineStats, WorkerEvent
 from .sources import ChunkInfo, SourceJob, SourceType
 

core/schema/models/detect_api.py

@@ -0,0 +1,31 @@
+"""
+Detection API request/response models.
+
+Source of truth for detection pipeline API shapes.
+Generated to Pydantic via modelgen.
+"""
+
+from dataclasses import dataclass
+
+
+@dataclass
+class RunRequest:
+    """Request body for launching a detection pipeline run."""
+    video_path: str           # storage key
+    profile_name: str = "soccer_broadcast"
+    source_asset_id: str = ""
+    checkpoint: bool = True
+    skip_vlm: bool = False
+    skip_cloud: bool = False
+    log_level: str = "INFO"  # INFO | DEBUG
+
+
+@dataclass
+class RunResponse:
+    """Response after starting a pipeline run."""
+    status: str
+    job_id: str
+    video_path: str
+
+
+DETECT_API_VIEWS = [RunRequest, RunResponse]

core/schema/models/job.py

@@ -56,7 +56,6 @@ class Job:
     estimated_cost_usd: float = 0.0
 
     # Worker tracking
-    celery_task_id: Optional[str] = None
     priority: int = 0
 
     # Timestamps

core/schema/models/jobs.py

@@ -1,133 +0,0 @@
-"""
-Job Schema Definitions
-
-Source of truth for job data models.
-TranscodeJob and ChunkJob share common lifecycle fields by convention.
-"""
-
-from dataclasses import dataclass, field
-from datetime import datetime
-from enum import Enum
-from typing import Any, Dict, List, Optional
-from uuid import UUID
-
-
-class JobStatus(str, Enum):
-    """Status of a transcode/trim job."""
-
-    PENDING = "pending"
-    PROCESSING = "processing"
-    COMPLETED = "completed"
-    FAILED = "failed"
-    CANCELLED = "cancelled"
-
-
-@dataclass
-class TranscodeJob:
-    """
-    A transcoding or trimming job in the queue.
-
-    Jobs can either:
-    - Transcode using a preset (full re-encode)
-    - Trim only (stream copy with -c:v copy -c:a copy)
-
-    A trim-only job has no preset and uses stream copy.
-    """
-
-    id: UUID
-
-    # Input
-    source_asset_id: UUID
-
-    # Configuration
-    preset_id: Optional[UUID] = None
-    preset_snapshot: Dict[str, Any] = field(
-        default_factory=dict
-    )  # Copy at creation time
-
-    # Trimming (optional)
-    trim_start: Optional[float] = None  # seconds
-    trim_end: Optional[float] = None  # seconds
-
-    # Output
-    output_filename: str = ""
-    output_path: Optional[str] = None
-    output_asset_id: Optional[UUID] = None
-
-    # Status & Progress
-    status: JobStatus = JobStatus.PENDING
-    progress: float = 0.0  # 0.0 to 100.0
-    current_frame: Optional[int] = None
-    current_time: Optional[float] = None  # seconds processed
-    speed: Optional[str] = None  # "2.5x"
-    error_message: Optional[str] = None
-
-    # Worker tracking
-    celery_task_id: Optional[str] = None
-    execution_arn: Optional[str] = None  # AWS Step Functions execution ARN
-    priority: int = 0  # Lower = higher priority
-
-    # Timestamps
-    created_at: Optional[datetime] = None
-    started_at: Optional[datetime] = None
-    completed_at: Optional[datetime] = None
-
-    @property
-    def is_trim_only(self) -> bool:
-        """Check if this is a trim-only job (stream copy, no transcode)."""
-        return self.preset_id is None and (
-            self.trim_start is not None or self.trim_end is not None
-        )
-
-
-class ChunkJobStatus(str, Enum):
-    """Status of a chunk pipeline job."""
-
-    PENDING = "pending"
-    CHUNKING = "chunking"
-    PROCESSING = "processing"
-    COLLECTING = "collecting"
-    COMPLETED = "completed"
-    FAILED = "failed"
-    CANCELLED = "cancelled"
-
-
-@dataclass
-class ChunkJob:
-    """
-    A chunk pipeline job — splits a media file into chunks and processes them
-    through a concurrent worker pool.
-    """
-
-    id: UUID
-
-    # Input
-    source_asset_id: UUID
-
-    # Configuration
-    chunk_duration: float = 10.0  # seconds
-    num_workers: int = 4
-    max_retries: int = 3
-    processor_type: str = "ffmpeg"  # "ffmpeg", "checksum", "simulated_decode", "composite"
-
-    # Status & Progress
-    status: ChunkJobStatus = ChunkJobStatus.PENDING
-    progress: float = 0.0  # 0.0 to 100.0
-    total_chunks: int = 0
-    processed_chunks: int = 0
-    failed_chunks: int = 0
-    retry_count: int = 0
-    error_message: Optional[str] = None
-
-    # Result stats
-    throughput_mbps: Optional[float] = None
-    elapsed_seconds: Optional[float] = None
-
-    # Worker tracking
-    celery_task_id: Optional[str] = None
-    priority: int = 0  # Lower = higher priority
-
-    # Timestamps
-    created_at: Optional[datetime] = None
-    started_at: Optional[datetime] = None
-    completed_at: Optional[datetime] = None