Update app.py

app.py

@@ -1091,6 +1091,85 @@ async def reset_session(session_id: str):
         "removed_systems": removed_systems
     }
 
+#verifikasi model loading
+@app.get("/verify-models")
+async def verify_all_models():
+    """Verify all 11 models can be loaded"""
+    verification_results = {}
+    total_models = len(MODELS)
+    successful_loads = 0
+    
+    for model_id, model_config in MODELS.items():
+        try:
+            print(f"🔍 Verifying {model_config['name']}...")
+            
+            if model_id not in app.state.pipelines:
+                pipeline_kwargs = {
+                    "task": model_config["task"],
+                    "model": model_config["model_path"],
+                    "device": -1,
+                    "torch_dtype": torch.float32,
+                    "model_kwargs": {
+                        "torchscript": False,
+                        "low_cpu_mem_usage": True
+                    }
+                }
+                
+                app.state.pipelines[model_id] = pipeline(**pipeline_kwargs)
+                gc.collect()
+            
+            # Test with simple input
+            if model_config["task"] == "text-generation":
+                test_result = app.state.pipelines[model_id](
+                    "Hello", 
+                    max_length=10, 
+                    do_sample=False,
+                    pad_token_id=app.state.pipelines[model_id].tokenizer.eos_token_id
+                )
+                verification_results[model_id] = {
+                    "status": "✅ SUCCESS",
+                    "name": model_config["name"],
+                    "task": model_config["task"],
+                    "test_output_length": len(test_result[0]['generated_text'])
+                }
+            elif model_config["task"] == "text-classification":
+                test_result = app.state.pipelines[model_id]("Hello test", truncation=True)
+                verification_results[model_id] = {
+                    "status": "✅ SUCCESS", 
+                    "name": model_config["name"],
+                    "task": model_config["task"],
+                    "test_score": test_result[0]['score']
+                }
+            elif model_config["task"] == "text2text-generation":
+                test_result = app.state.pipelines[model_id]("translate: Hello", max_length=10)
+                verification_results[model_id] = {
+                    "status": "✅ SUCCESS",
+                    "name": model_config["name"], 
+                    "task": model_config["task"],
+                    "test_output": test_result[0]['generated_text']
+                }
+            
+            successful_loads += 1
+            print(f"✅ {model_config['name']} verified successfully")
+            
+        except Exception as e:
+            verification_results[model_id] = {
+                "status": "❌ FAILED",
+                "name": model_config["name"],
+                "task": model_config["task"],
+                "error": str(e)
+            }
+            print(f"❌ {model_config['name']} failed: {e}")
+    
+    return {
+        "total_models": total_models,
+        "successful_loads": successful_loads,
+        "success_rate": f"{(successful_loads/total_models)*100:.1f}%",
+        "results": verification_results,
+        "memory_usage": f"{torch.cuda.memory_allocated() / 1024**2:.1f}MB" if torch.cuda.is_available() else "CPU Mode",
+        "loaded_pipelines": len(app.state.pipelines)
+    }
+
 # API info endpoint
 @app.get("/api")
 async def api_info():