diff --git a/bitmind/synthetic_data_generation/synthetic_data_generator.py b/bitmind/synthetic_data_generation/synthetic_data_generator.py
index e2122376..45eab8e4 100644
--- a/bitmind/synthetic_data_generation/synthetic_data_generator.py
+++ b/bitmind/synthetic_data_generation/synthetic_data_generator.py
@@ -511,63 +511,4 @@ def clear_gpu(self) -> None:
             del self.model
             self.model = None
             gc.collect()
-            torch.cuda.empty_cache()
-
-    def generate_from_prompt(
-        self,
-        prompt: str,
-        task: Optional[str] = None,
-        image: Optional[Image.Image] = None,
-        generate_at_target_size: bool = False
-    ) -> Dict[str, Any]:
-        """Generate synthetic data based on a provided prompt.
-        
-        Args:
-            prompt: The text prompt to use for generation
-            task: Optional task type ('t2i', 't2v', 'i2i', 'i2v')
-            image: Optional input image for i2i or i2v generation
-            generate_at_target_size: If True, generate at TARGET_IMAGE_SIZE dimensions
-            
-        Returns:
-            Dictionary containing generated data information
-        """
-        bt.logging.info(f"Generating synthetic data from provided prompt: {prompt}")
-        
-        # Default to t2i if task is not specified
-        if task is None:
-            task = 't2i'
-        
-        # If model_name is not specified, select one based on the task
-        if self.model_name is None and self.use_random_model:
-            bt.logging.warning(f"No model configured. Using random model.")
-            if task == 't2i':
-                model_candidates = T2I_MODEL_NAMES
-            elif task == 't2v':
-                model_candidates = T2V_MODEL_NAMES
-            elif task == 'i2i':
-                model_candidates = I2I_MODEL_NAMES
-            elif task == 'i2v':
-                model_candidates = I2V_MODEL_NAMES
-            else:
-                raise ValueError(f"Unsupported task: {task}")
-            
-            self.model_name = random.choice(model_candidates)
-        
-        # Validate input image for tasks that require it
-        if task in ['i2i', 'i2v'] and image is None:
-            raise ValueError(f"Input image is required for {task} generation")
-        
-        # Run the generation with the provided prompt
-        gen_data = self._run_generation(
-            prompt=prompt, 
-            task=task, 
-            model_name=self.model_name,
-            image=image,
-            generate_at_target_size=generate_at_target_size
-        )
-        
-        # Clean up GPU memory
-        self.clear_gpu()
-        
-        return gen_data
-
+            torch.cuda.empty_cache()
\ No newline at end of file