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import streamlit as st | |
from transformers import pipeline | |
# Load the conversational model from Hugging Face | |
# chatbot = pipeline('text-generation', model='shaneperry0101/Health-Llama-3.2-1B') | |
chatbot = pipeline('text-generation', model='microsoft/DialoGPT-medium') | |
# Initialize session state for storing the conversation | |
if 'conversation' not in st.session_state: | |
st.session_state.conversation = [] | |
# Streamlit app layout | |
st.title("Chatbot Application") | |
user_input = st.text_input("You:", key="input") | |
if st.button("Send"): | |
if user_input: | |
# Append user input to the conversation | |
st.session_state.conversation.append({"role": "user", "content": user_input}) | |
# Generate response | |
response = chatbot(user_input) | |
bot_response = response[0]['generated_text'] | |
# Append bot response to the conversation | |
st.session_state.conversation.append({"role": "bot", "content": bot_response}) | |
# Display the conversation | |
for message in st.session_state.conversation: | |
if message["role"] == "user": | |
st.text_area("You:", value=message["content"], key=f"user_{message['content']}", height=50) | |
else: | |
st.text_area("Bot:", value=message["content"], key=f"bot_{message['content']}", height=50) | |