feat: added support for remote server policy execution (#33)

Author: mark-neuracore

examples/4_rollout_neuracore_policy.py

@@ -661,26 +661,27 @@ def update_visualization(
         default=None,
         help="IP address of Meta Quest device (optional, defaults to None for auto-discovery)",
     )
-    parser.add_argument(
+    policy_group = parser.add_mutually_exclusive_group(required=True)
+    policy_group.add_argument(
         "--train-run-name",
         type=str,
         default=None,
-        help="Name of the training run to load policy from (for cloud training). Mutually exclusive with --model-path.",
+        help="Name of the training run to load policy from (for cloud training).",
     )
-    parser.add_argument(
+    policy_group.add_argument(
         "--model-path",
         type=str,
         default=None,
-        help="Path to local model file to load policy from. Mutually exclusive with --train-run-name.",
+        help="Path to local model file to load policy from.",
+    )
+    policy_group.add_argument(
+        "--remote-endpoint-name",
+        type=str,
+        default=None,
+        help="Name of remote Neuracore policy endpoint.",
     )
     args = parser.parse_args()
 
-    # Validate that exactly one of train-run-name or model-path is provided
-    if (args.train_run_name is None) == (args.model_path is None):
-        parser.error(
-            "Exactly one of --train-run-name or --model-path must be provided (not both, not neither)"
-        )
-
     print("=" * 60)
     print("PIPER ROBOT TEST WITH NEURACORE POLICY")
     print("=" * 60)
@@ -722,7 +723,19 @@ def update_visualization(
     for data_type, names in model_output_order.items():
         print(f"  {data_type.name}: {names}")
 
-    if args.train_run_name is not None:
+    if args.remote_endpoint_name is not None:
+        print(
+            f"\n🤖 Connecting to remote policy endpoint: {args.remote_endpoint_name}..."
+        )
+        try:
+            policy = nc.policy_remote_server(args.remote_endpoint_name)
+        except nc.EndpointError:
+            print(
+                f"❌ Endpoint '{args.remote_endpoint_name}' not available. "
+                "Please start it from the Neuracore dashboard."
+            )
+            sys.exit(1)
+    elif args.train_run_name is not None:
         print(f"\n🤖 Loading policy from training run: {args.train_run_name}...")
         policy = nc.policy(
             train_run_name=args.train_run_name,

examples/5_rollout_neuracore_policy_minimal.py

@@ -178,17 +178,24 @@ def execute_horizon(
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Minimal Piper Policy Test")
-    parser.add_argument(
+    policy_group = parser.add_mutually_exclusive_group(required=True)
+    policy_group.add_argument(
         "--train-run-name",
         type=str,
         default=None,
-        help="Name of the training run to load policy from (for cloud training). Mutually exclusive with --model-path.",
+        help="Name of the training run to load policy from (for cloud training).",
     )
-    parser.add_argument(
+    policy_group.add_argument(
         "--model-path",
         type=str,
         default=None,
-        help="Path to local model file to load policy from. Mutually exclusive with --train-run-name.",
+        help="Path to local model file to load policy from.",
+    )
+    policy_group.add_argument(
+        "--remote-endpoint-name",
+        type=str,
+        default=None,
+        help="Name of remote Neuracore policy endpoint.",
     )
     parser.add_argument(
         "--frequency",
@@ -204,12 +211,6 @@ def execute_horizon(
     )
     args = parser.parse_args()
 
-    # Validate that exactly one of train-run-name or model-path is provided
-    if (args.train_run_name is None) == (args.model_path is None):
-        parser.error(
-            "Exactly one of --train-run-name or --model-path must be provided (not both, not neither)"
-        )
-
     print("=" * 60)
     print("PIPER POLICY ROLLOUT")
     print("=" * 60)
@@ -244,7 +245,19 @@ def execute_horizon(
     for data_type, names in model_output_order.items():
         print(f"  {data_type.name}: {names}")
 
-    if args.train_run_name is not None:
+    if args.remote_endpoint_name is not None:
+        print(
+            f"\n🤖 Connecting to remote policy endpoint: {args.remote_endpoint_name}..."
+        )
+        try:
+            policy = nc.policy_remote_server(args.remote_endpoint_name)
+        except nc.EndpointError:
+            print(
+                f"❌ Endpoint '{args.remote_endpoint_name}' not available. "
+                "Please start it from the Neuracore dashboard."
+            )
+            sys.exit(1)
+    elif args.train_run_name is not None:
         print(f"\n🤖 Loading policy from training run: {args.train_run_name}...")
         policy = nc.policy(
             train_run_name=args.train_run_name,

examples/6_visualize_policy_from_dataset.py

@@ -40,18 +40,24 @@
     description="Visualize policy predictions from dataset"
 )
 parser.add_argument("--dataset-name", type=str, required=True, help="Dataset name")
-parser.add_argument(
+policy_group = parser.add_mutually_exclusive_group(required=True)
+policy_group.add_argument(
     "--train-run-name", type=str, default=None, help="Training run name"
 )
-parser.add_argument("--model-path", type=str, default=None, help="Model file path")
+policy_group.add_argument(
+    "--model-path", type=str, default=None, help="Model file path"
+)
+policy_group.add_argument(
+    "--remote-endpoint-name",
+    type=str,
+    default=None,
+    help="Name of remote Neuracore policy endpoint to use instead of a local policy.",
+)
 parser.add_argument(
     "--frequency", type=int, default=100, help="Frequency of visualization"
 )
 args = parser.parse_args()
 
-if (args.train_run_name is None) == (args.model_path is None):
-    parser.error("Exactly one of --train-run-name or --model-path must be provided")
-
 # Connect to Neuracore
 print("🔧 Initializing Neuracore...")
 nc.login()
@@ -68,7 +74,17 @@
     DataType.PARALLEL_GRIPPER_TARGET_OPEN_AMOUNTS: [GRIPPER_LOGGING_NAME],
 }
 
-if args.train_run_name:
+if args.remote_endpoint_name:
+    print(f"🤖 Connecting to remote policy endpoint: {args.remote_endpoint_name}...")
+    try:
+        policy = nc.policy_remote_server(args.remote_endpoint_name)
+    except nc.EndpointError:
+        print(
+            f"❌ Endpoint '{args.remote_endpoint_name}' not available. "
+            "Please start it from the Neuracore dashboard."
+        )
+        sys.exit(1)
+elif args.train_run_name:
     print(f"🤖 Loading policy from training run: {args.train_run_name}...")
     policy = nc.policy(
         train_run_name=args.train_run_name,