Update app.py

app.py

@@ -2,7 +2,6 @@ import numpy as np
 import pandas as pd
 import configparser
 import streamlit as st
-import streamlit
 import chromadb
 import langchain
 from langchain.embeddings.openai import OpenAIEmbeddings
@@ -15,8 +14,8 @@ import shutil
 import os
 import openai
 
-# You need your own API key
-api_key = st.secrets["OPENAI_API_KEY"]  # Get API key from Streamlit secrets
+# Replace with your OpenAI API key
+api_key = "your_openai_api_key_here"
 
 if not api_key:
     st.error("I can not find API key")
@@ -32,17 +31,17 @@ else:
             shutil.copyfileobj(uploaded_file, tmpfile)
             file_path = tmpfile.name
 
-        # PyPDFLoader
+        # Load and split PDF using PyPDFLoader
         loader = PyPDFLoader(file_path)
         pages = loader.load_and_split()
 
-        # Model and vectorstore
+        # Initialize model and vectorstore
+        llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
         embeddings = OpenAIEmbeddings()
         vectorstore = Chroma.from_documents(pages, embedding=embeddings, persist_directory=".")
         vectorstore.persist()
-        llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
 
-        # Q&A chain
+        # Create Q&A chain
         pdf_qa = ConversationalRetrievalChain.from_llm(llm, vectorstore.as_retriever(), return_source_documents=True)
 
         # Get question from user
@@ -53,4 +52,5 @@ else:
             st.write("Answer:", answer)
 
         # Delete tempfile
-        os.remove(file_path)  # Clean up the temporary file
+        if file_path:
+            os.unlink(file_path)