feat(isolation): DynamicVRAM compatibility for process isolation

DynamicVRAM's on-demand model loading/offloading conflicted with  process isolation in three ways: RPC tensor transport stalls from mid-call GPU offload, race conditions between model lifecycle and active RPC operations, and false positive memory leak detection from changed finalizer patterns.

- Marshal CUDA tensors to CPU before RPC transport for dynamic models
- Add operation state tracking + quiescence waits at workflow boundaries
- Distinguish proxy reference release from actual leaks in cleanup_models_gc
- Fix init order: DynamicVRAM must initialize before isolation proxies
- Add RPC timeouts to prevent indefinite hangs on model unavailability
- Prevent proxy-of-proxy chains from DynamicVRAM model reload cycles
- Add torch.device/torch.dtype serializers for new DynamicVRAM RPC paths
- Guard isolation overhead so non-isolated workflows are unaffected
- Migrate env var to PYISOLATE_CHILD

comfy_execution/jobs.py

@@ -20,7 +20,7 @@ class JobStatus:
 
 
 # Media types that can be previewed in the frontend
-PREVIEWABLE_MEDIA_TYPES = frozenset({'images', 'video', 'audio', '3d'})
+PREVIEWABLE_MEDIA_TYPES = frozenset({'images', 'video', 'audio', '3d', 'text'})
 
 # 3D file extensions for preview fallback (no dedicated media_type exists)
 THREE_D_EXTENSIONS = frozenset({'.obj', '.fbx', '.gltf', '.glb', '.usdz'})
@@ -75,6 +75,23 @@ def normalize_outputs(outputs: dict) -> dict:
         normalized[node_id] = normalized_node
     return normalized
 
+# Text preview truncation limit (1024 characters) to prevent preview_output bloat
+TEXT_PREVIEW_MAX_LENGTH = 1024
+
+
+def _create_text_preview(value: str) -> dict:
+    """Create a text preview dict with optional truncation.
+
+    Returns:
+        dict with 'content' and optionally 'truncated' flag
+    """
+    if len(value) <= TEXT_PREVIEW_MAX_LENGTH:
+        return {'content': value}
+    return {
+        'content': value[:TEXT_PREVIEW_MAX_LENGTH],
+        'truncated': True
+    }
+
 
 def _extract_job_metadata(extra_data: dict) -> tuple[Optional[int], Optional[str]]:
     """Extract create_time and workflow_id from extra_data.
@@ -221,23 +238,43 @@ def get_outputs_summary(outputs: dict) -> tuple[int, Optional[dict]]:
                 continue
 
             for item in items:
-                normalized = normalize_output_item(item)
-                if normalized is None:
-                    continue
+                if not isinstance(item, dict):
+                    # Handle text outputs (non-dict items like strings or tuples)
+                    normalized = normalize_output_item(item)
+                    if normalized is None:
+                        # Not a 3D file string — check for text preview
+                        if media_type == 'text':
+                            count += 1
+                            if preview_output is None:
+                                if isinstance(item, tuple):
+                                    text_value = item[0] if item else ''
+                                else:
+                                    text_value = str(item)
+                                text_preview = _create_text_preview(text_value)
+                                enriched = {
+                                    **text_preview,
+                                    'nodeId': node_id,
+                                    'mediaType': media_type
+                                }
+                                if fallback_preview is None:
+                                    fallback_preview = enriched
+                        continue
+                    # normalize_output_item returned a dict (e.g. 3D file)
+                    item = normalized
 
                 count += 1
 
                 if preview_output is not None:
                     continue
 
-                if isinstance(normalized, dict) and is_previewable(media_type, normalized):
+                if is_previewable(media_type, item):
                     enriched = {
-                        **normalized,
+                        **item,
                         'nodeId': node_id,
                     }
-                    if 'mediaType' not in normalized:
+                    if 'mediaType' not in item:
                         enriched['mediaType'] = media_type
-                    if normalized.get('type') == 'output':
+                    if item.get('type') == 'output':
                         preview_output = enriched
                     elif fallback_preview is None:
                         fallback_preview = enriched