Update app.py

app.py

@@ -15,17 +15,7 @@ st.title("Chat with CSV using open source LLM Inference Point 🦙🦜")
 # Display a markdown message with additional information
 st.markdown("<h3 style='text-align: center; color: white;'>Built by <a href='https://github.com/AIAnytime'>AI Anytime with ❤️ </a></h3>", unsafe_allow_html=True)
 
-# Allow users to upload a CSV file
-uploaded_file = st.sidebar.file_uploader("Upload your Data", type="csv")
-
-if uploaded_file :
-# Initialize the CSVLoader to load the uploaded CSV file
-   #use tempfile because CSVLoader only accepts a file_path
-    with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
-        tmp_file.write(uploaded_file.getvalue())
-        tmp_file_path = tmp_file.name
-
-    db = DB_FAISS_PATH = "vectorstore/db_faiss"
+loader = CSVLoader(file_path="data/2019.csv", encoding="utf-8", csv_args={"delimiter": ","})
 # Initialize the CSVLoader to load the uploaded CSV file
     loader = CSVLoader(file_path="data/2019.csv", encoding="utf-8", csv_args={'delimiter': ','})
     data = loader.load()
@@ -115,8 +105,8 @@ qa = ConversationalRetrievalChain.from_llm(llm, retriever=docsearch.as_retriever
 
 # Insert a chat message container.
 with st.chat_message("user"):
-    st.write("Hello 👋")
-    st.line_chart(np.random.randn(30, 3))
+   st.write("Hello 👋")
+   st.line_chart(np.random.randn(30, 3))
 
 # Display a chat input widget.
 st.chat_input("Say something")