r

app.py

@@ -4,10 +4,9 @@
 """
 import spaces
 import gradio as gr
-from deep_translator import GoogleTranslator
-from transformers import pipeline
-
-pipe = pipeline("summarization", model="facebook/bart-large-cnn")
+import subprocess
+import sys
+import os
 
 summary_type = {
     "short":{
@@ -119,5 +118,45 @@ iface = gr.Interface(
     ]
 )
 
-# Launch the Gradio interface
-iface.launch()
+def install_requirements():
+    requirements_path = 'requirements.txt'
+    
+    # Check if requirements.txt exists
+    if not os.path.exists(requirements_path):
+        print("Error: requirements.txt not found")
+        return False
+        
+    try:
+        print("Installing requirements...")
+        # Using --no-cache-dir to avoid memory issues
+        subprocess.check_call([
+            sys.executable, 
+            "-m", 
+            "pip", 
+            "install", 
+            "-r", 
+            requirements_path,
+            "--no-cache-dir"
+        ])
+        print("Successfully installed all requirements")
+        return True
+    except subprocess.CalledProcessError as e:
+        print(f"Error installing requirements: {e}")
+        return False
+    except Exception as e:
+        print(f"Unexpected error: {e}")
+        return False
+
+if __name__ == "__main__":
+    success = install_requirements()
+    if success:
+        print("All requirements installed successfully")
+        # Launch the Gradio interface
+        from deep_translator import GoogleTranslator
+        from transformers import pipeline
+
+        pipe = pipeline("summarization", model="facebook/bart-large-cnn")
+
+        iface.launch()
+    else:
+        print("Failed to install some requirements")

requirements.txt

@@ -1,4 +1,4 @@
-deep-translator
+deep-translator==1.11.4
 transformers
 tensorflow
 tf-keras