Update app.py

app.py

@@ -6,7 +6,7 @@ from langchain_community.vectorstores import FAISS
 from langchain.memory import ConversationBufferMemory
 from langchain.chains import ConversationalRetrievalChain
 from htmlTemplates import css, bot_template, user_template
-from langchain.llms import HuggingFaceHub
+from langchain_community.llms import HuggingFaceEndpoint
 import os
 from langchain_huggingface import HuggingFaceEmbeddings
 
@@ -39,20 +39,27 @@ def get_vectorstore(text_chunks):
 
 
 def get_conversation_chain(vectorstore):
-    os.environ["HUGGINGFACEHUB_API_TOKEN"] = os.environ.get("HUGGINGFACEHUB_API_TOKEN", "")
-    llm = HuggingFaceHub(
-        repo_id="google/flan-t5-base",  # Change to another HF model if you want
+    
+    os.environ["HUGGINGFACEHUB_API_TOKEN"] = os.getenv("HUGGINGFACEHUB_API_TOKEN", "")
+
+   
+    llm = HuggingFaceEndpoint(
+        repo_id="google/flan-t5-base",  
+        huggingfacehub_api_token=os.environ["HUGGINGFACEHUB_API_TOKEN"],
         model_kwargs={"temperature": 0.5, "max_length": 512}
     )
+
     memory = ConversationBufferMemory(
-        memory_key='chat_history', return_messages=True)
+        memory_key='chat_history', return_messages=True
+    )
+
     conversation_chain = ConversationalRetrievalChain.from_llm(
         llm=llm,
         retriever=vectorstore.as_retriever(),
         memory=memory
     )
-    return conversation_chain
 
+    return conversation_chain
 
 def handle_userinput(user_question):
     if st.session_state.conversation is None: