summarize immediately

app.py

@@ -236,10 +236,16 @@ def process_pdf_and_chat(pdf_file, message, history, system_message, max_tokens,
         return history + [(message, "Please upload a PDF file first.")]
     
     try:
-        # Create a temporary file path for the uploaded PDF
-        with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as tmp_file:
-            tmp_file.write(pdf_file.read())
-            tmp_pdf_path = tmp_file.name
+        # Handle file path - in newer Gradio versions, pdf_file is already a path
+        if isinstance(pdf_file, str):
+            tmp_pdf_path = pdf_file
+            cleanup_needed = False
+        else:
+            # For older versions where pdf_file is a file object
+            with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as tmp_file:
+                tmp_file.write(pdf_file.read())
+                tmp_pdf_path = tmp_file.name
+                cleanup_needed = True
         
         # Check if user wants to search for additional information
         search_keywords = ['search', 'find more', 'additional info', 'more information', 'research']
@@ -294,8 +300,9 @@ def process_pdf_and_chat(pdf_file, message, history, system_message, max_tokens,
             else:
                 response = "Unable to process the PDF. Please check the file format."
         
-        # Clean up temporary file
-        os.unlink(tmp_pdf_path)
+        # Clean up temporary file only if we created it
+        if cleanup_needed:
+            os.unlink(tmp_pdf_path)
         
         return history + [(message, response)]
     
@@ -336,10 +343,16 @@ def process_pdf_and_chat_messages(pdf_file, message, history, system_message, ma
         return "Please upload a PDF file first."
     
     try:
-        # Create a temporary file path for the uploaded PDF
-        with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as tmp_file:
-            tmp_file.write(pdf_file.read())
-            tmp_pdf_path = tmp_file.name
+        # Handle file path - in newer Gradio versions, pdf_file is already a path
+        if isinstance(pdf_file, str):
+            tmp_pdf_path = pdf_file
+            cleanup_needed = False
+        else:
+            # For older versions where pdf_file is a file object
+            with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as tmp_file:
+                tmp_file.write(pdf_file.read())
+                tmp_pdf_path = tmp_file.name
+                cleanup_needed = True
         
         # Check if user wants to search for additional information
         search_keywords = ['search', 'find more', 'additional info', 'more information', 'research']
@@ -394,8 +407,9 @@ def process_pdf_and_chat_messages(pdf_file, message, history, system_message, ma
             else:
                 response = "Unable to process the PDF. Please check the file format."
         
-        # Clean up temporary file
-        os.unlink(tmp_pdf_path)
+        # Clean up temporary file only if we created it
+        if cleanup_needed:
+            os.unlink(tmp_pdf_path)
         
         return response
     
@@ -463,10 +477,22 @@ with gr.Blocks() as demo:
             response = respond_messages(message, history[:-1], system_message, max_tokens, temperature, top_p, enable_search)
         return history[:-1] + [{"role": "user", "content": message}, {"role": "assistant", "content": response}]
     
+    def auto_summarize_pdf(pdf_file):
+        """Automatically summarize PDF when uploaded"""
+        if pdf_file is None:
+            return []
+        
+        # Trigger automatic summarization
+        response = process_pdf_and_chat_messages(pdf_file, "Please provide a summary of this document", [], "You are a helpful assistant for summarizing documents.", 512, 0.7, 0.95, False)
+        return [{"role": "assistant", "content": response}]
+    
     msg.submit(user_input, [msg, chatbot], [msg, chatbot], queue=False).then(
         bot_response, [chatbot, pdf_upload, enable_search, system_message, max_tokens, temperature, top_p], chatbot
     )
     clear.click(lambda: None, None, chatbot, queue=False)
+    
+    # Auto-summarize when PDF is uploaded
+    pdf_upload.upload(auto_summarize_pdf, [pdf_upload], [chatbot])
 
 if __name__ == "__main__":
     demo.launch(share=True)