adding gr.Info messages during the PDF processing and also improved the error handling to display messages in the UI if something goes wrong.

app.py

@@ -73,23 +73,43 @@ class SessionState:
     def is_db_ready(self):
         return self.db is not None
 
-async def process_pdf(pdf_file, state: SessionState):
+async def process_pdf(pdf_file, state: gr.State):
+    gr.Info("Processing PDF, please wait...")
     try:
+        # Check if a PDF has already been processed in this session
+        if state and state.is_db_ready():
+            return (
+                gr.update(interactive=False),
+                gr.update(interactive=True),
+                state
+            )
+            
         file_size_mb = os.path.getsize(pdf_file.name) / (1024 * 1024)
         if file_size_mb >= 75:
             gr.Error("File size exceeds the 75 MB limit. Please upload a smaller PDF.")
-            return
+            # Reset components on error
+            return (
+                gr.update(interactive=True),
+                gr.update(interactive=False),
+                gr.State() # Reset state
+            )
 
         print("Opening PDF file...")
         try:
             doc = fitz.open(pdf_file.name)
             text = ""
+            # CRITICAL FIX: Iterate over pages and get text from each page
             for page in doc:
                 text += page.get_text()
             doc.close()
         except Exception as e:
             print(f"Error processing PDF document: {str(e)}")
-            return
+            gr.Error(f"Error processing PDF document: {str(e)}")
+            return (
+                gr.update(interactive=True),
+                gr.update(interactive=False),
+                gr.State()
+            )
 
         print("PDF file opened successfully. Splitting text into chunks...")
         text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
@@ -97,17 +117,36 @@ async def process_pdf(pdf_file, state: SessionState):
         print("Text split into chunks successfully.")
 
         embeddings = GoogleGenerativeAIEmbeddings(model=EMBEDDING_MODEL, google_api_key=google_api_key)
-        state.db = await Chroma.afrom_documents(
+        
+        # Initialize a new session state object
+        new_state = SessionState()
+        
+        new_state.db = await Chroma.afrom_documents(
             documents=docs,
             embedding=embeddings,
-            persist_directory=state.vector_store_path,
-            collection_name=state.session_id
+            persist_directory=new_state.vector_store_path,
+            collection_name=new_state.session_id
         )
         print("PDF processed successfully! Database is ready.")
+        gr.Info("PDF processed! You can now ask questions about the document.")
+        
+        return (
+            gr.update(interactive=False),
+            gr.update(interactive=True),
+            new_state
+        )
+        
     except Exception as e:
-        if os.path.exists(state.vector_store_path):
+        if state and os.path.exists(state.vector_store_path):
             shutil.rmtree(state.vector_store_path)
         print(f"An error occurred: {str(e)}")
+        gr.Error(f"An error occurred: {str(e)}")
+        
+        return (
+            gr.update(interactive=True),
+            gr.update(interactive=False),
+            gr.State()
+        )
 
 async def chat_with_pdf(message, history, state: SessionState):
     print("Chat interface called. Checking if database is ready...")
@@ -143,7 +182,7 @@ async def chat_with_pdf(message, history, state: SessionState):
     yield response
 
 with gr.Blocks(title="PDF Chatbot") as demo:
-    state = gr.State()
+    state = gr.State(value=SessionState())
 
     gr.Markdown(
         """
@@ -151,35 +190,27 @@ with gr.Blocks(title="PDF Chatbot") as demo:
         Upload a PDF to start a conversation with your document.
         """
     )
+    
+    file_upload_input = gr.File(
+        file_types=[".pdf"],
+        label="Upload your PDF document",
+        interactive=True
+    )
 
-    with gr.Row():
-        file_upload_input = gr.File(
-            file_types=[".pdf"],
-            label="Upload your PDF document",
-            interactive=True
-        )
-
-    with gr.Row(visible=False) as chat_row:
-        chat_interface = gr.ChatInterface(
-            fn=chat_with_pdf,
-            additional_inputs=[state],
-            chatbot=gr.Chatbot(type="messages"),
-            textbox=gr.Textbox(placeholder="Type your question here...", scale=7),
-            examples=[["What is the main topic of the document?"], ["Summarize the key findings."], ["Who are the authors?"]],
-            title="Chat Interface",
-            theme="soft",
-            type="messages"
-        )
-
-    async def process_and_show_chat(file):
-        new_state = SessionState()
-        await process_pdf(file, new_state)
-        return gr.update(visible=True), gr.update(interactive=False), new_state
+    chat_interface = gr.ChatInterface(
+        fn=chat_with_pdf,
+        additional_inputs=[state],
+        chatbot=gr.Chatbot(type="messages"),
+        textbox=gr.Textbox(placeholder="Type your question here...", scale=7, interactive=False),
+        examples=[["What is the main topic of the document?"], ["Summarize the key findings."], ["Who are the authors?"]],
+        title="Chat Interface",
+        theme="soft"
+    )
 
     file_upload_input.upload(
-        fn=process_and_show_chat,
-        inputs=[file_upload_input],
-        outputs=[chat_row, file_upload_input, state]
+        fn=process_pdf,
+        inputs=[file_upload_input, state],
+        outputs=[file_upload_input, chat_interface.textbox, state]
     )
 
-demo.launch()
+demo.launch()