Update app.py

app.py

@@ -110,9 +110,9 @@
 #             with st.chat_message("Human"):
 #                 st.write(message.content)
 
-
 import os
 import streamlit as st
+from dotenv import load_dotenv
 from langchain_core.messages import AIMessage, HumanMessage
 from langchain_community.document_loaders import WebBaseLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
@@ -122,10 +122,10 @@ from langchain_community.llms import HuggingFaceHub
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain.chains import create_history_aware_retriever, create_retrieval_chain
 from langchain.chains.combine_documents import create_stuff_documents_chain
-from dotenv import load_dotenv
 
-# Load Hugging Face token from .env
+# Load environment variable (works locally and on Hugging Face Spaces)
 load_dotenv()
+HF_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN", "").strip()
 
 # Function to get vectorstore from a website
 def get_vectorstore_from_url(url):
@@ -148,6 +148,7 @@ def get_vectorstore_from_url(url):
 def get_context_retriever_chain(vector_store):
     llm = HuggingFaceHub(
         repo_id="google/flan-t5-base",
+        huggingfacehub_api_token=HF_TOKEN,
         model_kwargs={"temperature": 0.5, "max_length": 512}
     )
 
@@ -165,6 +166,7 @@ def get_context_retriever_chain(vector_store):
 def get_conversational_rag_chain(retriever_chain):
     llm = HuggingFaceHub(
         repo_id="google/flan-t5-base",
+        huggingfacehub_api_token=HF_TOKEN,
         model_kwargs={"temperature": 0.5, "max_length": 512}
     )
 
@@ -198,7 +200,6 @@ with st.sidebar:
     st.header("🔧 Settings")
     website_url = st.text_input("🌐 Website URL")
 
-# Handle input and chatbot logic
 if not website_url:
     st.info("Please enter a website URL in the sidebar.")
 else:
@@ -214,7 +215,7 @@ else:
         st.session_state.chat_history.append(HumanMessage(content=user_input))
         st.session_state.chat_history.append(AIMessage(content=response))
 
-    # Display messages
+    # Display chat messages
     for msg in st.session_state.chat_history:
         with st.chat_message("AI" if isinstance(msg, AIMessage) else "Human"):
             st.write(msg.content)