Upload app.py

app.py

@@ -1,45 +1,35 @@
 from langchain import HuggingFaceHub
-from langchain.schema import HumanMessage,SystemMessage,AIMessage
-
+from langchain.schema import AIMessage
 from dotenv import load_dotenv
+import streamlit as st
 
+# Load environment variables
 load_dotenv()
 
-import streamlit as st
-##streamlit app 
+# Initialize HuggingFace model outside the app
+llm_huggingface = HuggingFaceHub(repo_id="google/flan-t5-large", model_kwargs={"temperature": 0.0, "max_length": 64})
+
+# Streamlit app 
 st.set_page_config(page_title="Chatbot")
 st.header('Langchain Application')
 
+# Remove the session_state initialization as it's not being used in this example
 
-
-# Initialization session
-##if 'key' not in st.session_state:
-#    st.session_state['key'] =[
-#         SystemMessage(content='You are AI ')
-#    ]
-
-
-# function to load huggingface model and get response
+# Function to load HuggingFace model and get response
 def get_huggingface_response(question):
-    llm_huggingface=HuggingFaceHub(repo_id="google/flan-t5-large",model_kwargs={"temperature":0.0})
-
-    #st.session_state['key'].append(HumanMessage(content=question))
-    #response=llm_huggingface(st.session_state['key'])
     response = llm_huggingface(question) 
-    #st.session_state['key'].append(AIMessage(content=response))
-    return(response)
-
-
+    return response
 
+# Streamlit input
+user_input = st.text_input("Input: ", key="input")
 
-##streamlit input
-input=st.text_input("Input: ",key="input")
-## call function
-response=get_huggingface_response(input)
+# Streamlit button
+submit = st.button('Generate')
 
-##streamlit button
-submit=st.button('Generate')
-## click button
+# Check if button is clicked
 if submit: 
-        st.subheader("The response is ")
-        st.write(response)
+    # Call function to get response
+    response = get_huggingface_response(user_input)
+    # Display response
+    st.subheader("The response is ")
+    st.write(response)