building-streamlit-chat-ui

Build Streamlit chat interfaces with st.chat_message and st.chat_input.

Updated Feb 19, 2026
One-click install
npx skills add https://github.com/guihousun/NTL-GPT-Clone --skill building-streamlit-chat-ui-guihousun
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: building-streamlit-chat-ui
Source: https://github.com/guihousun/NTL-GPT-Clone/tree/main/skills/developing-with-streamlit/skills/building-streamlit-chat-ui
Command: npx skills add https://github.com/guihousun/NTL-GPT-Clone --skill building-streamlit-chat-ui-guihousun

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Developers need to create conversational Streamlit interfaces quickly without building custom UI components.

Core Features & Use Cases

  • Streamlit chat elements including st.chat_message and st.chat_input to manage message history and user input.
  • Streaming responses to render assistant messages in real-time.
  • Avatars, suggestion chips, and simple UI customization for a polished chat experience.
  • Quick-start scaffolding to prototype conversational interfaces rapidly.

Quick Start

Create a minimal Streamlit app that uses st.chat_message and st.chat_input to render a live chat UI.

Frequently Asked Questions about building-streamlit-chat-ui

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a Streamlit chat UI for conversational AI?

Build a Streamlit chat UI using st.chat_message and st.chat_input elements to manage message history and user input without writing custom UI components. This provides quick-start scaffolding to prototype conversational interfaces rapidly.

Can I render streaming responses in a Streamlit chat interface?

Yes, you can render streaming responses in a Streamlit chat interface to display assistant messages in real-time. This allows users to see the conversational AI output as it generates, creating a more dynamic chat experience.

What Streamlit components are needed for message history and user input?

Message history and user input require the st.chat_message and st.chat_input components. These built-in Streamlit elements handle the conversational interface structure, allowing you to manage chat logs and capture user text entries directly.

Does this Streamlit chat UI approach support avatars and suggestion chips?

Yes, the Streamlit chat UI approach supports avatars, suggestion chips, and simple UI customization. These features help create a polished conversational AI chat experience directly within the Streamlit application framework.

Do I need to write custom UI components for a Streamlit chatbot?

No, you do not need to write custom UI components for a Streamlit chatbot. You can use built-in elements like st.chat_message and st.chat_input to create interactive conversational interfaces quickly and efficiently.