Loader: resolve documents under assets/

load_dataset.py

@@ -39,6 +39,11 @@ class FCCInvoicesDataset:
 
     def __init__(self, local_dir: str):
         self.local_dir = Path(local_dir)
+        # Documents live under assets/; accept a checkout root or the assets dir itself.
+        if (self.local_dir / "assets").is_dir():
+            self.assets_dir = self.local_dir / "assets"
+        else:
+            self.assets_dir = self.local_dir
         self._doc_ids: list[str] | None = None
 
     # ------------------------------------------------------------------
@@ -49,26 +54,26 @@ class FCCInvoicesDataset:
         """Return all document IDs (md5 hashes)."""
         if self._doc_ids is None:
             self._doc_ids = sorted(
-                p.name for p in self.local_dir.iterdir()
+                p.name for p in self.assets_dir.iterdir()
                 if p.is_dir() and (p / "metadata.json").exists()
             )
         return self._doc_ids
 
     def load_ground_truth(self, doc_id: str) -> dict:
         """Read and parse gt.json for a document."""
-        return json.loads((self.local_dir / doc_id / "gt.json").read_text())
+        return json.loads((self.assets_dir / doc_id / "gt.json").read_text())
 
     def load_metadata(self, doc_id: str) -> dict:
         """Read and parse metadata.json (pipeline manifest) for a document."""
-        return json.loads((self.local_dir / doc_id / "metadata.json").read_text())
+        return json.loads((self.assets_dir / doc_id / "metadata.json").read_text())
 
     def pdf_path(self, doc_id: str, pipeline_name: str) -> str:
         """Return the local path to a noisy PDF."""
-        return str(self.local_dir / doc_id / pipeline_name / f"{pipeline_name}_noisy.pdf")
+        return str(self.assets_dir / doc_id / pipeline_name / f"{pipeline_name}_noisy.pdf")
 
     def original_pdf_path(self, doc_id: str) -> str:
         """Return the local path to the original clean PDF."""
-        return str(self.local_dir / doc_id / "original.pdf")
+        return str(self.assets_dir / doc_id / "original.pdf")
 
     def get_sample(self, doc_id: str, pipeline_name: str) -> dict:
         """Return a single sample dict."""