app.py

import os
import streamlit as st
from datasets import load_dataset
from huggingface_hub import InferenceClient

# ... (rest of your code)

# Define the placeholder globally (outside columns)
placeholder = st.empty()
placeholder.markdown(f'<div class="scrollable-div"><p></p></div>', unsafe_allow_html=True)

def handle_submit():
    user_input = st.session_state.user_input

    if user_input:
        if st.session_state.include_context:
            messages = [
                {"role": "system", "content": f"Context: {context}"},
                {"role": "user", "content": user_input}
            ]
        else:
            messages = [
                {"role": "system", "content": f"Context: Adrega is a powerful project management and reporting tool. It can show Gantt diagrams, S-Curves, Tabular reports and various charts in single reports, report bundles or in a customizable dashboard."},
                {"role": "user", "content": user_input}
            ]

        response = client.chat.completions.create(
            model="Qwen/Qwen2.5-72B-Instruct",
            messages=messages,
            max_tokens=1000,
            stream=True
        )

        answer = ""
        for chunk in response:
            answer += chunk['choices'][0]['delta']['content']
            # Update content within the existing placeholder
            placeholder.markdown(f'<div class="scrollable-div"><p>{answer}</p></div>', unsafe_allow_html=True)
            st.session_state.conversation = f"<p>{answer}</p>" + st.session_state.conversation

    else:
        st.session_state.conversation(f"<p><strong>Adrega AI:</strong>: Please enter a question.")

# ... (rest of your code)

st.text_input('Ask me a question', key='user_input', on_change=handle_submit)
col1, col2 = st.columns(2)
with col1:
    if st.button("Ask"):
        handle_submit()

if 'conversation' not in st.session_state:
    st.session_state.conversation = ""

with col2:
    st.session_state.include_context = st.checkbox('Search in Help')