Update config.py

config.py

@@ -33,7 +33,8 @@ class AppConfig:
             "context_length": 128000,  # Full 128k context length
             "supports_reasoning": True,
             "supports_tool_calling": True,
-            "active_params": "5.1B"
+            "active_params": "5.1B",
+            "is_gpt_oss": True
         },
         "openai/gpt-oss-20b": {
             "name": "GPT OSS 20B", 
@@ -42,7 +43,26 @@ class AppConfig:
             "context_length": 128000,  # Full 128k context length
             "supports_reasoning": True,
             "supports_tool_calling": True,
-            "active_params": "3.6B"
+            "active_params": "3.6B",
+            "is_gpt_oss": True
+        },
+        "Qwen/Qwen3-VL-235B-A22B-Thinking": {
+            "name": "Qwen3-VL 235B A22B Thinking",
+            "description": "Vision-Language reasoning model (Qwen), strong multimodal understanding",
+            "size": "235B",
+            "context_length": 128000,
+            "supports_reasoning": True,
+            "supports_tool_calling": True,
+            "is_gpt_oss": False
+        },
+        "Qwen/Qwen3-VL-235B-A22B-Instruct": {
+            "name": "Qwen3-VL 235B A22B Instruct",
+            "description": "Vision-Language instruct-tuned model (Qwen)",
+            "size": "235B",
+            "context_length": 128000,
+            "supports_reasoning": True,
+            "supports_tool_calling": True,
+            "is_gpt_oss": False
         }
     }
     
@@ -109,7 +129,7 @@ class AppConfig:
     DEFAULT_REASONING_EFFORT = "medium"  # low, medium, high
     
     # UI Configuration
-    GRADIO_THEME = "Ocean"
+    GRADIO_THEME = "ocean"
     DEBUG_MODE = True
     
     # MCP Server recommendations
@@ -132,12 +152,28 @@ class AppConfig:
         available_models = []
         
         for model_id, model_info in cls.AVAILABLE_MODELS.items():
-            if model_info["size"] == "120B" and provider["supports_120b"]:
+            # If model declares explicit providers, honor that
+            if "providers" in model_info:
+                if provider_id in model_info["providers"]:
+                    available_models.append(model_id)
+                continue
+            # Legacy gating by size for GPT-OSS entries
+            if model_info.get("size") == "120B" and provider.get("supports_120b"):
+                available_models.append(model_id)
+            elif model_info.get("size") == "20B" and provider.get("supports_20b"):
                 available_models.append(model_id)
-            elif model_info["size"] == "20B" and provider["supports_20b"]:
+            else:
+                # Default: include other models unless explicitly incompatible
                 available_models.append(model_id)
                 
         return available_models
+
+    @classmethod
+    def is_gpt_oss_model(cls, model_id: str) -> bool:
+        info = cls.AVAILABLE_MODELS.get(model_id, {})
+        if info.get("is_gpt_oss"):
+            return True
+        return model_id.startswith("openai/gpt-oss-")
     
     @classmethod
     def get_model_endpoint(cls, model_id: str, provider_id: str) -> str: