atifsial123 commited on
Commit
a21cc8f
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1 Parent(s): 01df9cf

Update app.py

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Files changed (1) hide show
  1. app.py +24 -16
app.py CHANGED
@@ -18,23 +18,28 @@ import gradio as gr
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  from transformers import AutoModel, AutoTokenizer
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  import torch
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  from sklearn.model_selection import train_test_split
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- from google.colab import files
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- # Upload the dataset if running in Google Colab
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- def upload_dataset():
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- uploaded = files.upload() # This will prompt the file upload
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- file_name = list(uploaded.keys())[0]
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- file_path = f'/content/{file_name}'
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- return file_path
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- # Load your dataset
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- def load_dataset():
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- file_path = '/content/Valid-part-2.xlsx' # Default path if the file is uploaded manually to Colab
 
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  # Check if the file exists
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- if not os.path.exists(file_path):
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- print(f"File not found at '{file_path}', prompting file upload...")
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- file_path = upload_dataset() # Upload if not found
 
 
 
 
 
 
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  try:
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  df = pd.read_excel(file_path)
@@ -78,8 +83,8 @@ def predict(input_text):
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  return outputs.last_hidden_state
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  # Build the Gradio interface
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- def build_interface():
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- df = load_dataset() # Load your dataset
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  if df is None:
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  return None
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@@ -95,7 +100,9 @@ def build_interface():
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  # Run the Gradio interface
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  if __name__ == "__main__":
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- iface = build_interface()
 
 
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  if iface:
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  iface.launch()
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  else:
@@ -103,3 +110,4 @@ if __name__ == "__main__":
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  from transformers import AutoModel, AutoTokenizer
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  import torch
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  from sklearn.model_selection import train_test_split
 
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+ # Function to convert a list to a DataFrame
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+ def list_to_dataframe(data_list):
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+ # Convert the list to a DataFrame (assuming it's a list of dicts or tuples)
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+ df = pd.DataFrame(data_list)
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+ return df
 
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+ # Load your dataset from a file
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+ def load_dataset(file_path=None):
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+ if file_path is None:
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+ file_path = '/content/Valid-part-2.xlsx' # Default path if the file is uploaded manually to Colab
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  # Check if the file exists
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+ if file_path and not os.path.exists(file_path):
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+ print(f"File not found at '{file_path}', using default list data...")
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+ # Fallback to a default list if file is not found
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+ default_data = [
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+ {'text': 'Example sentence 1', 'label': 'label1'},
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+ {'text': 'Example sentence 2', 'label': 'label2'},
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+ # Add more example data as needed
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+ ]
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+ return list_to_dataframe(default_data)
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  try:
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  df = pd.read_excel(file_path)
 
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  return outputs.last_hidden_state
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  # Build the Gradio interface
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+ def build_interface(file_path=None):
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+ df = load_dataset(file_path) # Load your dataset
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  if df is None:
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  return None
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  # Run the Gradio interface
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  if __name__ == "__main__":
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+ # You can specify a file_path here if you have a specific file to use
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+ file_path = None # Change this to your specific file path if needed
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+ iface = build_interface(file_path=file_path)
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  if iface:
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  iface.launch()
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  else:
 
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+