Mastering Ollama: A Comprehensive Guide to API Integration with a Streamlit User Interface — PART 3

Mastering Ollama: Advanced Customizations and Deployment Strategies for a Streamlit-Based AI App

1. Advanced Customizations in the Ollama-Streamlit Application

1.1. Enhancing the User Interface

While our previous parts focused on basic UI functionality, a production-grade app often requires a polished, highly interactive interface. Consider these improvements:

• Custom Styling: Modify the default Streamlit theme using custom CSS (embedded via st.markdown with HTML).
• Dynamic Layouts: Leverage columns, tabs, and expandable sections to organize content better.
• User Feedback: Enhance the interactivity with clear visual cues (progress bars, notifications, and alerts).

Example: Using columns and expanders for a more organized layout

import streamlit as st

st.title("Enhanced Ollama-Streamlit Dashboard")
# Create two columns for input and response side-by-side
col1, col2 = st.columns(2)
with col1:
    st.header("Input Section")
    user_prompt = st.text_area("Enter your prompt:", height=150)
    submit_button = st.button("Submit")
with col2…