diff --git a/src/backend/langflow/components/llms/CTransformers.py b/src/backend/langflow/components/llms/CTransformers.py
index 881953639..46b1c021e 100644
--- a/src/backend/langflow/components/llms/CTransformers.py
+++ b/src/backend/langflow/components/llms/CTransformers.py
@@ -11,46 +11,16 @@ class CTransformersComponent(CustomComponent):
     def build_config(self):
         return {
             "model": {"display_name": "Model", "required": True},
-            "model_file": {"display_name": "Model File", "required": False},
-            "model_type": {"display_name": "Model Type", "required": False},
+            "model_file": {"display_name": "Model File", "required": False,"field_type":"file", "file_types":[".bin"]},
+            "model_type": {"display_name": "Model Type", "required": True},
             "config": {"display_name": "Config", "advanced": True, "required": False,"field_type":"dict","value":'{"top_k":40,"top_p":0.95,"temperature":0.8,"repetition_penalty":1.1,"last_n_tokens":64,"seed":-1,"max_new_tokens":256,"stop":"","stream":"False","reset":"True","batch_size":8,"threads":-1,"context_length":-1,"gpu_layers":0}'}
         }
 
     def build(
         self,
         model: str,
-        model_file: Optional[str] = None,
-        model_type: Optional[str] = None,
+        model_file: str,
+        model_type: str,
         config: Optional[Dict] = None
     ) -> CTransformers:
-        # Default config values
-        default_config = {
-            "top_k": 40,
-            "top_p": 0.95,
-            "temperature": 0.8,
-            "repetition_penalty": 1.1,
-            "last_n_tokens": 64,
-            "seed": -1,
-            "max_new_tokens": 256,
-            "stop": None,
-            "stream": False,
-            "reset": True,
-            "batch_size": 8,
-            "threads": -1,
-            "context_length": -1,
-            "gpu_layers": 0
-        }
-
-        # If there is a custom config, update the default config with it
-        if config:
-            default_config.update(config)
-
-        # Assuming the import below is correct and CTransformers is a class within the langchain library
-        # that inherits from BaseLanguageModel. The following import statement is required:
-        # from langchain.llms.integration_module import CTransformers
-
-        return CTransformers(model=model, model_file=model_file, model_type=model_type, config=default_config)
-
-# Note: The actual CTransformers class needs to be imported from the correct module inside the langchain library.
-# The `integration_module` in the import statement is just a placeholder and should be replaced with
-# the actual module where the CTransformers class is located.
+        return CTransformers(model=model, model_file=model_file, model_type=model_type, config=config)