model cards optimization

src/webapp/routers/data.py

@@ -14,7 +14,6 @@
 import logging
 from sqlalchemy.exc import IntegrityError
 from ..config import databricks_vars, env_vars, gcs_vars
-from mlflow.exceptions import MlflowException
 import tempfile
 import pathlib
 
@@ -1373,33 +1372,34 @@ def get_model_cards(
             f"get_model_cards(): Workspace client initialization failed: {e}"
         )
 
-    try:
-        run_resp = w.experiments.get_run(run_id=run_id)
-
-        assert run_resp.run is not None, "Expected non-None Run object"
-        assert run_resp.run.info is not None, "Expected non-None RunInfo object"
+    host = w.config.host  # e.g. "https://12345.gcp.databricks.com"
 
-        experiment_id = run_resp.run.info.experiment_id
+    # 2. Build the MLflow REST endpoint URL and params
+    download_endpoint = f"{host}/api/2.0/mlflow/artifacts/download"
+    artifact_path = f"model_card/model-card-{model_name}.pdf"
+    params = {"run_id": run_id, "path": artifact_path}
 
-        dbfs_path = (
-            f"/databricks/mlflow-tracking/{experiment_id}/{run_id}/artifacts/"
-            f"model_card/model-card-{model_name}.pdf"
+    # 3. Let WorkspaceClient’s ApiClient perform the authenticated GET
+    try:
+        # perform_query will attach the same OAuth creds that WorkspaceClient uses
+        resp = w.api_client.perform_query(  # type: ignore[attr-defined]
+            method="GET",
+            path=download_endpoint,
+            query_params=params,
+        )  # type: ignore[attr-defined]
+        # resp here is the raw bytes of the PDF
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=f"Could not download model card via MLflow REST API: {e}",
         )
-        with tempfile.TemporaryDirectory() as tmpdir:
-            local_file = pathlib.Path(tmpdir) / f"model-card-{model_name}.pdf"
-            with w.dbfs.download(
-                f"dbfs:{dbfs_path}"
-            ) as stream:  # DBFS API download() returns a bytes stream
-                local_file.write_bytes(stream.read())
-
-            LOGGER.debug("Artifact provisioned successfully")
-            return FileResponse(
-                path=str(local_file),
-                filename=local_file.name,
-                media_type="application/pdf",
-            )
 
-    except MlflowException as e:
-        # 6. Handle errors gracefully
-        LOGGER.debug(f"Artifact download failed: {e}")
-        raise HTTPException(status_code=500, detail=f"Artifact download failed: {e}")
+    # 4. Write to a temp file and return it
+    with tempfile.TemporaryDirectory() as td:
+        out_path = pathlib.Path(td) / f"model-card-{model_name}.pdf"
+        out_path.write_bytes(resp)
+        return FileResponse(
+            path=str(out_path),
+            filename=out_path.name,
+            media_type="application/pdf",
+        )