Update app.py

app.py

@@ -49,7 +49,7 @@ def get_vectorstore(text_chunks):
 # Function to set up the conversational retrieval chain
 def get_conversation_chain(vectorstore):
     try:
-        llm = ChatGroq(model="llama-3-3-70b-vision", temperature=0.5)
+        llm = ChatGroq(model="llama-3.3-70b-versatile", temperature=0.5)
         memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
         
         conversation_chain = ConversationalRetrievalChain.from_llm(
@@ -74,7 +74,7 @@ def handle_userinput(user_question):
             role = "User" if i % 2 == 0 else "Bot"
             st.write(f"*{role}:* {message.content}")
     else:
-        st.warning("Please upload and process documents first.")
+        st.warning("Please process the documents first.")
 
 # Main function to run the Streamlit app
 def main():
@@ -87,28 +87,23 @@ def main():
         st.session_state.chat_history = None
 
     st.header("Chat with PDFs :books:")
-
     user_question = st.text_input("Ask a question about your documents:")
     if user_question:
         handle_userinput(user_question)
 
     with st.sidebar:
         st.subheader("Your documents")
-        pdf_docs = st.file_uploader("Upload PDFs", accept_multiple_files=True, type=["pdf"])
-
-        if pdf_docs:
-            if st.button("Submit"):
-                with st.spinner("Processing..."):
-                    raw_text = get_pdf_text(pdf_docs)
-                    if raw_text.strip():
-                        text_chunks = get_text_chunks(raw_text)
-                        vectorstore = get_vectorstore(text_chunks)
-                        st.session_state.conversation = get_conversation_chain(vectorstore)
-                        st.success("Processing complete! You can now ask questions.")
-                    else:
-                        st.error("No valid text extracted from the PDFs.")
-        else:
-            st.info("Please upload PDF files to proceed.")
+        pdf_docs = st.file_uploader("Upload PDFs and click 'Process'", accept_multiple_files=True, type=["pdf"])
+        if st.button("Process"):
+            with st.spinner("Processing..."):
+                raw_text = get_pdf_text(pdf_docs)
+                if raw_text.strip():
+                    text_chunks = get_text_chunks(raw_text)
+                    vectorstore = get_vectorstore(text_chunks)
+                    st.session_state.conversation = get_conversation_chain(vectorstore)
+                    st.success("Processing complete! You can now ask questions.")
+                else:
+                    st.error("No valid text extracted from the PDFs.")
 
 if __name__ == '__main__':
-    main()
+    main()