Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import os
 import requests
 from bs4 import BeautifulSoup
-from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.embeddings import OpenAIEmbeddings
 from langchain.vectorstores import FAISS
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.memory import ConversationBufferMemory
@@ -75,7 +75,7 @@ book_url = "https://www.gutenberg.org/files/11/11-0.txt"
 
 # Function to fetch and process the book
 @st.cache_resource
-def process_book(book_url):
+def process_book(book_url, api_key):
     # Download the book
     response = requests.get(book_url)
     if response.status_code != 200:
@@ -96,9 +96,9 @@ def process_book(book_url):
     )
     chunks = text_splitter.split_text(cleaned_text)
     
-    # Create embeddings
-    embeddings = HuggingFaceEmbeddings(
-        model_name="sentence-transformers/all-MiniLM-L6-v2"
+    # Create embeddings using OpenAI
+    embeddings = OpenAIEmbeddings(
+        openai_api_key=openai_api_key
     )
     
     # Create vector store
@@ -164,7 +164,7 @@ else:
     # Process the book when needed
     if not st.session_state.book_processed:
         with st.spinner("Processing Alice in Wonderland... This may take a minute."):
-            vector_store = process_book(book_url)
+            vector_store = process_book(book_url, openai_api_key)
             st.session_state.agent = create_langchain_agent(vector_store)
             st.session_state.book_processed = True
             st.success("Alice in Wonderland processed successfully!")