Update app.py

app.py

@@ -1,28 +1,59 @@
-import gdown
-import torch
+# import gdown
+# import torch
+
+# # https://drive.google.com/drive/folders/17G-ejd4scK1DYko5k0ssXZjEy7P-ClI6
+
+# import streamlit as st
+# import gdown
+# import torch
+# from transformers import pipeline
+
+# # Function to download the model from Google Drive
+# def download_file_from_drive(file_id, output_path):
+#     url = f'https://drive.google.com/uc?id={file_id}'
+#     gdown.download(url, output_path, quiet=False)
+
+# # Replace 'YOUR_FILE_ID' with the actual file ID of your model
+# file_id = '1A2B3C4D5E6F7G8H9I0J'
+
 
-# https://drive.google.com/drive/folders/17G-ejd4scK1DYko5k0ssXZjEy7P-ClI6
 
 import streamlit as st
-import gdown
+import requests
 import torch
 from transformers import pipeline
 
-# Function to download the model from Google Drive
+# Function to download the model from Google Drive using requests
 def download_file_from_drive(file_id, output_path):
-    url = f'https://drive.google.com/uc?id={file_id}'
-    gdown.download(url, output_path, quiet=False)
+    url = f'https://drive.google.com/uc?export=download&id={file_id}'
+    response = requests.get(url, stream=True)
+    
+    if response.status_code == 200:
+        with open(output_path, 'wb') as f:
+            for chunk in response.iter_content(chunk_size=8192):
+                if chunk:
+                    f.write(chunk)
+    else:
+        raise Exception(f"Failed to download file: Status code {response.status_code}")
 
 # Replace 'YOUR_FILE_ID' with the actual file ID of your model
 file_id = '1A2B3C4D5E6F7G8H9I0J'
 output_path = 'model.pt'
 
 # Download the model file
-download_file_from_drive(file_id, output_path)
+try:
+    download_file_from_drive(file_id, output_path)
+except Exception as e:
+    st.error(f"Error downloading file: {e}")
+    st.stop()
 
 # Load the model
-model = torch.load(output_path)
-model.eval()
+try:
+    model = torch.load(output_path)
+    model.eval()
+except Exception as e:
+    st.error(f"Error loading model: {e}")
+    st.stop()
 
 # Initialize the summarization pipeline
 summarizer = pipeline('summarization', model=model)
@@ -37,8 +68,11 @@ text_input = st.text_area("Enter text to summarize", height=300)
 if st.button("Summarize"):
     if text_input:
         with st.spinner("Generating summary..."):
-            summary = summarizer(text_input, max_length=150, min_length=30, do_sample=False)
-            st.subheader("Summary")
-            st.write(summary[0]['summary_text'])
+            try:
+                summary = summarizer(text_input, max_length=150, min_length=30, do_sample=False)
+                st.subheader("Summary")
+                st.write(summary[0]['summary_text'])
+            except Exception as e:
+                st.error(f"Error during summarization: {e}")
     else:
         st.warning("Please enter some text to summarize.")