import streamlit as st from transformers import pipeline import torch # Set page title and layout st.set_page_config(page_title="Paraphrase Chat Interface", layout="wide") # Initialize the model @st.cache_resource def load_model(): model = "GeneZC/MiniChat-2-3B" return pipeline(task='text-generation', model=model) generator = load_model() tones = { 'natural': 'human, authentic', 'fluency': 'readable, clarified', 'formal': 'sophisticated', 'academic': 'technical and scholarly', 'simple': 'simple and easily understandable', } def generate(text, max_length): return generator(text, max_length=max_length, num_return_sequences=1) def respond(message, tone="natural", max_length=512): prompt = f" [|User|]Paraphrase this text in a more {tones[tone]} way: {message} [|Assistant|]" text = generate(prompt, max_length) text = text[0]["generated_text"] text = text.split("[|Assistant|]", 1)[1] return text # Streamlit UI st.title("Paraphrase Chat Interface") # Sidebar for tone and max length selection st.sidebar.header("Settings") tone = st.sidebar.selectbox("Select Tone", list(tones.keys()), index=0) max_length = st.sidebar.slider("Max new tokens", min_value=1, max_value=2048, value=512, step=1) # Explanation of the app st.sidebar.markdown(""" ## How to use 1. Type your text in the chat input below. 2. Select a tone from the dropdown menu. 3. Adjust the max token length if needed. 4. Press Enter to get a paraphrased version. The AI will rephrase your text in the selected tone. """) # Initialize chat history if "messages" not in st.session_state: st.session_state.messages = [] # Display chat messages from history on app rerun for message in st.session_state.messages: with st.chat_message(message["role"]): st.markdown(message["content"]) # React to user input if prompt := st.chat_input("What would you like to paraphrase?"): # Display user message in chat message container st.chat_message("user").markdown(prompt) # Add user message to chat history st.session_state.messages.append({"role": "user", "content": prompt}) # Show a spinner while processing with st.spinner("Generating paraphrase..."): response = respond(prompt, tone, max_length) # Display assistant response in chat message container with st.chat_message("assistant"): st.markdown(response) # Add assistant response to chat history st.session_state.messages.append({"role": "assistant", "content": response}) # Add a button to clear chat history if st.button("Clear Chat History"): st.session_state.messages = [] st.rerun() # Use st.rerun() instead of st.experimental_rerun() # Footer st.markdown("---") st.markdown("Powered by Hugging Face Transformers and Streamlit")