feat: setup dataset enrichment app codebase and scripts

backend/api/models.py

@@ -0,0 +1,63 @@
+"""Training and model-version routes (REQ-060…065)."""
+
+import os
+from typing import Optional, Union
+
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+
+from backend import hardware, training
+from backend.api.common import project_or_404
+
+router = APIRouter(tags=["models"])
+
+
+class TrainRequest(BaseModel):
+    epochs: int = 50
+    batch: Optional[int] = None
+    imgsz: Optional[int] = None
+    device: Optional[Union[int, str]] = None
+    batch_ids: Optional[list] = None
+
+
+@router.get("/api/hardware")
+def read_hardware() -> dict:
+    return hardware.defaults()
+
+
+@router.post("/api/projects/{project_id}/train")
+def start_training(project_id: int, request: TrainRequest) -> dict:
+    project_or_404(project_id)
+    try:
+        return training.start(
+            project_id, request.epochs,
+            {"batch": request.batch, "imgsz": request.imgsz, "device": request.device},
+            batch_ids=request.batch_ids,
+        )
+    except training.TrainingError as exc:
+        raise HTTPException(400, str(exc))
+
+
+@router.get("/api/projects/{project_id}/models")
+def list_models(project_id: int) -> dict:
+    project = project_or_404(project_id)
+    return {"models": training.listing(project_id),
+            "base_model_kind": project["base_model_kind"]}
+
+
+@router.get("/api/models/{model_id}/weights")
+def download_weights(model_id: int):
+    version = training.get_version(model_id)
+    if version is None or not os.path.isfile(version["weights_path"]):
+        raise HTTPException(404, "No weights for that version")
+    return FileResponse(version["weights_path"], media_type="application/octet-stream",
+                        filename=f"v{version['version']}-best.pt")
+
+
+@router.post("/api/models/{model_id}/promote")
+def promote_model(model_id: int) -> dict:
+    try:
+        return training.promote(model_id)
+    except training.TrainingError as exc:
+        raise HTTPException(400, str(exc))