Update app.py

app.py

@@ -2,36 +2,35 @@
 #Once you have Streamlit installed, you can import it into your Python script using the import statement,
 
 import streamlit as st
+from transformers import pipeline
 
+# Load the Hugging Face model (GPT-2 in this case)
+@st.cache_resource
+def load_model():
+    return pipeline("text-generation", model="gpt2")
 
-from langchain.llms import openai
-
-#Function to return the response
+# Function to return the response from Hugging Face model
 def load_answer(question):
-    llm = OpenAI(model_name="gpt-4-turbo-preview",temperature=0)
-    answer=llm(question)
-    return answer
-
+    model = load_model()
+    answer = model(question, max_length=100, num_return_sequences=1)
+    return answer[0]['generated_text']
 
-#App UI starts here
-st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
-st.header("LangChain Demo")
+# App UI starts here
+st.set_page_config(page_title="Hugging Face Demo", page_icon=":robot:")
+st.header("Hugging Face Demo")
 
-#Gets the user input
+# Gets the user input
 def get_text():
     input_text = st.text_input("You: ", key="input")
     return input_text
 
-
-user_input=get_text()
+user_input = get_text()
 response = load_answer(user_input)
 
-submit = st.button('Generate')  
+submit = st.button('Generate')
 
-#If generate button is clicked
+# If generate button is clicked
 if submit:
-
     st.subheader("Answer:")
-
     st.write(response)