Update app.py

app.py

@@ -1,6 +1,5 @@
 import streamlit as st
 import pandas as pd
-import io
 import os
 from dotenv import load_dotenv
 from llama_index.core import Settings, VectorStoreIndex, SimpleDirectoryReader
@@ -16,9 +15,9 @@ 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()
 os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
 
 # Global settings for LlamaIndex
@@ -45,14 +44,8 @@ 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)
+                # Use CSVLoader with the uploaded file
+                loader = CSVLoader(file_path=uploaded_file)
                 docs = loader.load_and_split()
 
                 # Preview the first document
@@ -91,24 +84,15 @@ if uploaded_file:
 
             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(
-                    input_files=[temp_file_path],
+                    input_files=[uploaded_file.name],
                     file_extractor={".csv": csv_reader},
                 )
                 docs = reader.load_data()
@@ -137,9 +121,5 @@ if uploaded_file:
                     st.write(f"Answer: {response.response}")
             except Exception as e:
                 st.error(f"Error processing with LlamaIndex: {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)
     except Exception as e:
         st.error(f"Error reading uploaded file: {e}")