Streamlit

Instead of writing HTML and JavaScript, a Streamlit developer writes an ordinary Python file, and every widget interaction reruns that script from top to bottom with the new values, while st.cache_data and st.cache_resource keep model or dataset loads from repeating. For AI work the useful pieces are st.chat_message and st.chat_input for chat layouts, st.write_stream for token-by-token LLM output, file uploaders, media and dataframe elements, and session state for keeping conversation history. Multipage navigation, built-in authentication, secrets handling, database connections, an app testing framework, and a custom components API round it out. Install from PyPI on Python 3.10 or newer, then start an app with streamlit run; finished apps deploy to the free Community Cloud, to Snowflake, or to any server or container that runs Python. The library is Apache 2.0, so commercial use is unrestricted. Snowflake owns the project, and outside pull requests are currently paused, though bug reports are welcome. Best for data scientists and ML engineers who need a demo, internal tool, or chatbot UI without frontend work.