Fix Wan 2.2 I2V base model detection and VRAM estimation

- Add correct base model for Wan 2.2 I2V: Wan-AI/Wan2.2-I2V-A14B-Diffuser
- Add specific VRAM estimate for Wan 2.2 I2V MoE models (~14GB)
- Apply more conservative VRAM calculation for models with weights/LoRAs
- Fix indentation error in add_model_from_hf function

videogen.py

@@ -1429,6 +1429,11 @@ def add_model_from_hf(model_id_or_url, name=None, hf_token=None, debug=False):
         else:
             # Try to infer base model from LoRA name
             if "wan" in model_id.lower():
+                if "wan2.2" in model_id.lower():
+                    # Wan 2.2 models - use the new MoE base
+                    base_model = "Wan-AI/Wan2.2-I2V-A14B-Diffuser" if is_i2v else "Wan-AI/Wan2.2-T2V-14B-Diffuser"
+                else:
+                    # Wan 2.1 and earlier
                     base_model = "Wan-AI/Wan2.1-I2V-14B-Diffusers" if is_i2v else "Wan-AI/Wan2.1-T2V-14B-Diffusers"
             elif "svd" in model_id.lower() or "stable-video" in model_id.lower():
                 base_model = "stabilityai/stable-video-diffusion-img2vid-xt-1-1"
@@ -3861,10 +3866,12 @@ def select_best_model(gen_type, models, vram_gb=24, prefer_quality=True, return_
                 # Try to infer base model from LoRA name
                 lora_id = info.get("id", "").lower()
                 if "wan" in lora_id:
-                    if info.get("supports_i2v"):
-                        base_model_id = "Wan-AI/Wan2.1-I2V-14B-Diffusers"
+                    if "wan2.2" in lora_id:
+                        # Wan 2.2 models - use the new MoE base
+                        base_model_id = "Wan-AI/Wan2.2-I2V-A14B-Diffuser" if info.get("supports_i2v") else "Wan-AI/Wan2.2-T2V-14B-Diffuser"
                     else:
-                        base_model_id = "Wan-AI/Wan2.1-T2V-14B-Diffusers"
+                        # Wan 2.1 and earlier
+                        base_model_id = "Wan-AI/Wan2.1-I2V-14B-Diffusers" if info.get("supports_i2v") else "Wan-AI/Wan2.1-T2V-14B-Diffusers"
                 elif "svd" in lora_id or "stable-video" in lora_id:
                     base_model_id = "stabilityai/stable-video-diffusion-img2vid-xt-1-1"
                 elif "sdxl" in lora_id:
@@ -3887,7 +3894,10 @@ def select_best_model(gen_type, models, vram_gb=24, prefer_quality=True, return_
             # If base model not in our database, create a minimal info dict
             if not base_model_info:
                 # Estimate VRAM based on base model type
-                if "wan" in base_model_id.lower():
+                # Wan 2.2 I2V MoE model - 14B parameters with mixture of experts
+                if "wan2.2" in base_model_id.lower() and "i2v" in base_model_id.lower():
+                    base_vram_est = 14.0  # Wan 2.2 I2V MoE is ~14GB
+                elif "wan" in base_model_id.lower():
                     base_vram_est = 24.0
                 elif "svd" in base_model_id.lower():
                     base_vram_est = 16.0