Handle legacy latent upscale payloads

dumas_h3_longvideos.py

@@ -4084,6 +4084,19 @@ def _latent_upscale_target_size(base_w, base_h, param):
     return int(base_w), int(base_h)
 
 
+def _latent_upscale_mode(param):
+    if not isinstance(param, dict):
+        return "off"
+    mode = str(param.get("mode") or "").strip()
+    if mode:
+        return mode
+    if "model_name" in param and str(param.get("model_name") or "").strip() not in ("", "none"):
+        return "model"
+    if "method" in param:
+        return "interp"
+    return "off"
+
+
 def _latent_spatial_grid(h, w, th, tw, ol_h, ol_w):
     if th <= 0 or tw <= 0:
         raise ValueError("tile dimensions must be positive")
@@ -6637,10 +6650,8 @@ class H3LongVideos:
             raise
         refined_out = out
         latent_upscale_param = latent_upscale_param or None
-        if (
-            isinstance(latent_upscale_param, dict)
-            and str(latent_upscale_param.get("mode", "off")) != "off"
-        ):
+        latent_upscale_mode = _latent_upscale_mode(latent_upscale_param)
+        if latent_upscale_mode != "off":
             try:
                 latent_start = time.perf_counter()
                 out_samples = out["samples"]
@@ -6659,7 +6670,7 @@ class H3LongVideos:
                 target_h = int(up_h) * 16
                 if target_w <= 0 or target_h <= 0:
                     raise RuntimeError("latent upscale target size must be positive")
-                if latent_upscale_param.get("mode") == "model" and str(latent_upscale_param.get("device", "cuda")) == "cuda" and hasattr(model, "clone_base_uuid"):
+                if latent_upscale_mode == "model" and str(latent_upscale_param.get("device", "cuda")) == "cuda" and hasattr(model, "clone_base_uuid"):
                     mm.unload_model_and_clones(model, unload_additional_models=False)
                     mm.soft_empty_cache()
                 upscale_cond, upscale_latent = _build_shot_conditioning(
@@ -6939,9 +6950,10 @@ class H3LongVideos:
         if apply_model_sampling:
             model, ms_note = apply_h3_model_sampling(model, shift_video, shift_audio)
         latent_upscale_note = ""
-        if isinstance(latent_upscale_param, dict) and str(latent_upscale_param.get("mode", "off")) != "off":
+        latent_upscale_mode = _latent_upscale_mode(latent_upscale_param)
+        if latent_upscale_mode != "off":
             target_w, target_h = _latent_upscale_target_size(w, h, latent_upscale_param)
-            mode = str(latent_upscale_param.get("mode", "off"))
+            mode = latent_upscale_mode
             detail = f" via {mode}"
             if mode == "model":
                 detail += f"/{latent_upscale_param.get('model_name', 'none')}"