Catch MissingDatasetTypeError in making quantum graph

If a dataset type isn't known to the local repo, the quantum
graph building now fails with MissingDatasetTypeError. It
was ignored in the past. This scenario is possible in cases
such as a fresh local repo is used and the incoming image
doesn't have matching templates. We want it to fall back to
try the next pipeline. If the repo knows the template's
dataset type but no matching templates exist, it still
generate an empty quantum graph.

python/activator/middleware_interface.py

@@ -38,6 +38,7 @@
 import lsst.ctrl.mpexec
 from lsst.ctrl.mpexec import SeparablePipelineExecutor, SingleQuantumExecutor, MPGraphExecutor
 from lsst.daf.butler import Butler, CollectionType, Timespan
+from lsst.daf.butler.registry import MissingDatasetTypeError
 import lsst.dax.apdb
 import lsst.geom
 from lsst.meas.algorithms.htmIndexer import HtmIndexer
@@ -862,10 +863,14 @@ def run_pipeline(self, exposure_ids: set[int]) -> None:
                 skip_existing_in=None,
                 task_factory=factory,
             )
-            qgraph = executor.make_quantum_graph(pipeline, where=where)
+            try:
+                qgraph = executor.make_quantum_graph(pipeline, where=where)
+            except MissingDatasetTypeError as e:
+                _log.error(f"Building quantum graph for {pipeline_file} failed ", exc_info=e)
+                continue
             if len(qgraph) == 0:
                 # Diagnostic logs are the responsibility of GraphBuilder.
-                _log.error(f"Could not build quantum graph for {pipeline_file}; "
+                _log.error(f"Empty quantum graph for {pipeline_file}; "
                            "see previous logs for details.")
                 continue
             # Past this point, partial execution creates datasets.