Update app.py

app.py

@@ -37,11 +37,6 @@ if uploaded_file:
         st.write("Preview of uploaded data:")
         st.dataframe(data)
 
-        # Create a temporary file for the uploaded CSV
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".csv", mode="w") as temp_file:
-            data.to_csv(temp_file.name, index=False)
-            temp_file_path = temp_file.name
-
         # Tabs
         tab1, tab2 = st.tabs(["Chat w CSV using LangChain", "Chat w CSV using LlamaIndex"])
 
@@ -49,6 +44,12 @@ if uploaded_file:
         with tab1:
             st.subheader("LangChain Query")
             try:
+                # Save the uploaded file to a temporary file for LangChain
+                with tempfile.NamedTemporaryFile(delete=False, suffix=".csv", mode="w") as temp_file:
+                    # Write the DataFrame to the temp file
+                    data.to_csv(temp_file.name, index=False)
+                    temp_file_path = temp_file.name
+
                 # Use CSVLoader with the temporary file path
                 loader = CSVLoader(file_path=temp_file_path)
                 docs = loader.load_and_split()
@@ -78,7 +79,7 @@ if uploaded_file:
                 prompt = ChatPromptTemplate.from_messages(
                     [("system", system_prompt), ("human", "{input}")]
                 )
-                question_answer_chain = create_stuff_documents_chain(ChatOpenAI(), prompt)
+                question_answer_chain = create_stuff_documents_chain(ChatOpenAI(model="gpt-4o"), prompt)
                 langchain_rag_chain = create_retrieval_chain(retriever, question_answer_chain)
 
                 # Query input for LangChain
@@ -86,13 +87,23 @@ if uploaded_file:
                 if query:
                     answer = langchain_rag_chain.invoke({"input": query})
                     st.write(f"Answer: {answer['answer']}")
+
             except Exception as e:
                 st.error(f"Error processing with LangChain: {e}")
+            finally:
+                # Clean up the temporary file
+                if 'temp_file_path' in locals() and os.path.exists(temp_file_path):
+                    os.remove(temp_file_path)
 
         # LlamaIndex Tab
         with tab2:
             st.subheader("LlamaIndex Query")
             try:
+                # Save uploaded file content to a temporary CSV file for LlamaIndex
+                with tempfile.NamedTemporaryFile(delete=False, suffix=".csv", mode="w") as temp_file:
+                    data.to_csv(temp_file.name, index=False)
+                    temp_file_path = temp_file.name
+
                 # Use PagedCSVReader for LlamaIndex
                 csv_reader = PagedCSVReader()
                 reader = SimpleDirectoryReader(