Fix concurrent local activity replay nondeterminism

During first execution, local activity resolve_activity jobs arrive in
completion order (wall-clock). During replay, they arrive in sequence
number order. When multiple coroutines issue local activities
concurrently, this ordering difference causes coroutines to resume in a
different order, assigning different sequence numbers to subsequent
commands and triggering NondeterminismError.

Fix by sorting local activity resolutions by sequence number before
processing. This ensures coroutines always resume in scheduling order
regardless of execution mode.

Author: paulcacheux

temporalio/worker/_workflow_instance.py

@@ -461,8 +461,30 @@ def activate(
             for index, job_set in enumerate(job_sets):
                 if not job_set:
                     continue
+                # Separate local-activity resolutions from other jobs.
+                # Local activity results may arrive in non-deterministic
+                # order (completion order varies between first-execution
+                # and replay). Sort them by sequence number so coroutines
+                # always resume in scheduling order, ensuring deterministic
+                # interleaving regardless of execution mode.
+                local_activity_jobs = []
+                other_jobs = []
                 for job in job_set:
-                    # Let errors bubble out of these to the caller to fail the task
+                    if (
+                        job.HasField("resolve_activity")
+                        and job.resolve_activity.is_local
+                    ):
+                        local_activity_jobs.append(job)
+                    else:
+                        other_jobs.append(job)
+
+                # Apply non-local-activity jobs first
+                for job in other_jobs:
+                    self._apply(job)
+
+                # Apply local activity resolutions sorted by seq number.
+                local_activity_jobs.sort(key=lambda j: j.resolve_activity.seq)
+                for job in local_activity_jobs:
                     self._apply(job)
 
                 # Run one iteration of the loop. We do not allow conditions to