Update app.py

app.py

@@ -2,37 +2,26 @@ import streamlit as st
 from transformers import pipeline
 from langchain.schema import AIMessage, HumanMessage, SystemMessage
 
-# ------------------------
-# Streamlit UI
-# ------------------------
 st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
 st.header("MHRV Chatbot")
 
-# Initialize session messages
 if "sessionMessages" not in st.session_state:
     st.session_state.sessionMessages = [
         SystemMessage(content="You are a helpful customer support chatbot for a website.")
     ]
 
-# ------------------------
-# Load Hugging Face model (CPU-friendly)
-# ------------------------
-# Using a smaller model for free Spaces CPU plan
+# Smaller CPU-friendly model
 generator = pipeline(
     "text-generation",
-    model="mosaicml/mpt-7b-instruct",  # smaller, instruction-tuned, CPU-compatible
-    device=-1,  # -1 = CPU
+    model="tiiuae/falcon-1b-instruct",
+    device=-1,  # CPU
     max_new_tokens=256,
     temperature=0.3
 )
 
-# ------------------------
-# Helper functions
-# ------------------------
 def load_answer(question):
     st.session_state.sessionMessages.append(HumanMessage(content=question))
 
-    # Convert session messages to a single prompt string
     prompt = ""
     for msg in st.session_state.sessionMessages:
         if isinstance(msg, SystemMessage):
@@ -42,21 +31,15 @@ def load_answer(question):
         elif isinstance(msg, AIMessage):
             prompt += f"AI: {msg.content}\n"
 
-    # Generate response
     output = generator(prompt, max_new_tokens=256, do_sample=True, temperature=0.3)
     answer_text = output[0]["generated_text"][len(prompt):].strip()
 
-    # Add AI message to session
     st.session_state.sessionMessages.append(AIMessage(content=answer_text))
-
     return answer_text
 
 def get_text():
     return st.text_input("You: ", key="input")
 
-# ------------------------
-# Main App
-# ------------------------
 user_input = get_text()
 submit = st.button("Generate")