Update app.py

app.py

@@ -4,7 +4,6 @@ import io
 import os
 from dotenv import load_dotenv
 from llama_index.core import Settings, VectorStoreIndex, SimpleDirectoryReader
-from llama_index.core.readers.base import BaseReader
 from llama_index.readers.file.paged_csv.base import PagedCSVReader
 from llama_index.embeddings.openai import OpenAIEmbedding
 from llama_index.llms.openai import OpenAI
@@ -17,6 +16,7 @@ from langchain.chains.combine_documents import create_stuff_documents_chain
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_openai import OpenAIEmbeddings, ChatOpenAI
 import faiss
+import tempfile
 
 # Load environment variables
 load_dotenv()
@@ -34,7 +34,7 @@ st.title("Chat with CSV Files - LangChain vs LlamaIndex")
 uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"])
 if uploaded_file:
     try:
-        # Load and preview CSV data using pandas
+        # Read and preview CSV data using pandas
         data = pd.read_csv(uploaded_file)
         st.write("Preview of uploaded data:")
         st.dataframe(data)
@@ -46,8 +46,13 @@ if uploaded_file:
         with tab1:
             st.subheader("LangChain Query")
             try:
-                # Use CSVLoader directly with file-like object
-                loader = CSVLoader(file_path=io.BytesIO(uploaded_file.getvalue()))
+                # Save the uploaded file to a temporary file for LangChain
+                with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as temp_file:
+                    temp_file.write(uploaded_file.getvalue())
+                    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()
 
                 # Preview the first document
@@ -83,8 +88,13 @@ 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: