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import streamlit as st |
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from transformers import pipeline |
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from PIL import Image |
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from datetime import time |
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if "messages" not in st.session_state: |
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st.session_state.messages = [] |
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st.title("USC GPT - Find the perfect class") |
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class_time = st.slider( |
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"Filter Class Times:", |
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value=(time(11, 30), time(12, 45))) |
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units = st.slider( |
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"Number of units", |
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1, 4, |
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value = (1, 4) |
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) |
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for message in st.session_state.messages: |
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with st.chat_message(message["role"]): |
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st.markdown(message["content"]) |
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if prompt := st.chat_input("What kind of class are you looking for?"): |
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with st.chat_message("user"): |
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st.markdown(prompt) |
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st.session_state.messages.append({"role": "user", "content": prompt}) |
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with st.chat_message("assistant"): |
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message_placeholder = st.empty() |
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full_response = "" |
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assistant_response = "Hello there! How can I assist you today?" |
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) |
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for chunk in assistant_response.split(): |
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full_response += chunk + " " |
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time.sleep(0.05) |
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message_placeholder.markdown(full_response + "▌") |
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message_placeholder.markdown(full_response) |
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st.session_state.messages.append({"role": "assistant", "content": full_response}) |