Building GenAI applications with Streamlit involves best practices that enhance robustness, scalability, and responsibility. Key strategies include structuring your app for sanity, customizing chat elements, effectively displaying LLM outputs, mastering prompt engineering, securely handling API keys, maintaining context with st.session_state, implementing rate-limiting, using caching for performance improvement, leveraging asynchronous operations, and applying observability tools for insights.
Table of contents
1. Structure your app for sanity and scalability2. Customize chat elements3. Display LLM outputs effectively4. Master prompt engineering in Streamlit5. Handle API keys securely6. Use st.session_state to maintain context7. Implement rate-limiting to keep API costs under control8. Use caching to improve performance and save cost9. Keep your app snappy with asynchronous operations10. See what your GenAI model is doing with observabilityConclusion2.6K Impressions