Model switch fix

tools/generate_image.py

@@ -32,7 +32,7 @@ async def ensure_model_state(model_name: str, model_preset: Dict[str, Any]):
             preset = model_preset.get("preset", "xl")
             await asyncio.to_thread(
                 requests.post,
-                f"{config.SD_URL}/api/predict/checkpoint_change", 
+                f"{config.SD_URL}/api/checkpoint_change", 
                 json={"data": [target_ckpt, preset]}, 
                 timeout=30
             )
@@ -45,7 +45,7 @@ async def ensure_model_state(model_name: str, model_preset: Dict[str, Any]):
             preset = model_preset.get("preset", "xl")
             await asyncio.to_thread(
                 requests.post,
-                f"{config.SD_URL}/api/predict/modules_change", 
+                f"{config.SD_URL}/api/modules_change", 
                 json={"data": [target_modules, preset]}, 
                 timeout=30
             )
@@ -81,16 +81,47 @@ async def handle(args: Dict[str, Any]) -> List[Dict[str, Any]]:
     except Exception as e:
         raise ToolError(f"Failed to connect to Stable Diffusion server: {str(e)}")
 
-    # Build the label-to-index map
+    # Build the label-to-index map and a sparse payload
     label_map = {}
     label_counts = {}
     
-    payload = [p["parameter_default"] for p in params_info]
+    # Find the maximum param index to determine payload size
+    max_param_idx = 0
+    for p in params_info:
+        name = p.get("parameter_name", "")
+        if name.startswith("param_"):
+            try:
+                idx = int(name.replace("param_", ""))
+                max_param_idx = max(max_param_idx, idx)
+            except ValueError:
+                pass
 
-    for idx, p in enumerate(params_info):
-        label = p["label"]
+    # Initialize payload with Nones (size is max_idx + 1)
+    payload = [None] * (max_param_idx + 1)
+    
+    for idx_in_list, p in enumerate(params_info):
+        name = p.get("parameter_name", "")
+        label = p.get("label")
+        default = p.get("parameter_default")
+        
+        # Determine the absolute index in the payload
+        if name == "id_task":
+            abs_idx = 0
+        elif name.startswith("param_"):
+            try:
+                abs_idx = int(name.replace("param_", ""))
+            except ValueError:
+                continue
+        else:
+            # Fallback for unexpected names, though unlikely
+            continue
+
+        # Set the default value at the absolute index
+        payload[abs_idx] = default
+        
+        # Handle label mapping for AI overrides
         if not label or label.startswith("parameter_"):
-            label = p["parameter_name"]
+            label = name
             
         if label in label_counts:
             label_counts[label] += 1
@@ -99,7 +130,7 @@ async def handle(args: Dict[str, Any]) -> List[Dict[str, Any]]:
             label_counts[label] = 0
             mapped_label = label
             
-        label_map[mapped_label] = idx
+        label_map[mapped_label] = abs_idx
 
     # 3. LOAD CONFIGS
     models_cfg = load_toml(config.MODEL_PRESETS_PATH)
@@ -163,8 +194,8 @@ async def handle(args: Dict[str, Any]) -> List[Dict[str, Any]]:
     if "Seed" in label_map:
         payload[label_map["Seed"]] = -1
 
-    for _ in range(7):
-        payload.insert(39, None)
+    # The "Magic Number" splice is no longer needed as gaps are 
+    # automatically filled by the sparse-to-dense mapping.
 
     # 6. EXECUTE GENERATION
     try: