Update app.py

app.py

@@ -36,8 +36,8 @@ def load_dataset():
 
 # Preprocess the data
 def preprocess_data(df):
-    # Add your preprocessing steps here
-    # For example: cleaning, tokenization, etc.
+    # Example preprocessing: You can add more steps as needed
+    # For now, we're just returning the dataframe as is
     return df
 
 # Train your model
@@ -49,8 +49,8 @@ def train_model(df):
     tokenizer = AutoTokenizer.from_pretrained("Alibaba-NLP/gte-multilingual-base")
     model = AutoModel.from_pretrained("Alibaba-NLP/gte-multilingual-base")
 
-    # Add your training code here
-    # This may involve tokenizing the data and feeding it into the model
+    # Normally, you would fine-tune the model here with your training data
+    # Since this is an example, we're returning the model as is
     return model
 
 # Define the Gradio interface function
@@ -91,3 +91,4 @@ if __name__ == "__main__":
     else:
         print("Failed to build the Gradio interface. Please check the dataset and model.")
 
+