shinychat
An AI Chat interface for Shiny apps.
Decision gist · record as of 2026-08-14
Yes, if you are building a Shiny for Python application that needs a chat interface. The component is actively maintained, has no known vulnerabilities, low install friction, and integrates seamlessly with Shiny's reactive model. It is permissively licensed and already included with Shiny, so installing it separately is optional unless you need a specific version or want to use it outside a Shiny context.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later and a working Shiny for Python environment.
- Low friction installation with a pure-Python wheel.
- Actively maintained with a recent release and no known vulnerabilities.
License · maintenance · safety
MIT (permissive) — MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 136 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 320,603 downloads/mo, #7,635 on PyPI
Alternatives
Verify before relying
pip install shinychat
from shiny.express import render, ui
from shinychat.express import Chat
chat = Chat(id="chat", messages=[{"content": "Hello!", "role": "assistant"}])
chat.ui()
@chat.on_user_submit
async def handle_input(user_input: str):
await chat.append_message(f"You said: {user_input}")- Whether the package includes built-in LLM integration or only provides UI scaffolding for user-supplied models.
- Performance characteristics and message history size limits for typical chat applications.
- Styling and customization options beyond what the example demonstrates.
What it is and what it does
shinychat is a chat UI component library for Shiny for Python that abstracts the interface layer for building conversational applications. It provides a Chat class that manages message display, user input collection, and event handling, letting developers focus on the backend logic rather than HTML/CSS markup. The component integrates directly into Shiny's reactive framework and supports both imperative and declarative usage patterns.
Typically used to add a chat interface to a Shiny app by instantiating a Chat object, rendering it with `.ui()`, and attaching an async callback to handle user submissions. Messages are managed as a reactive list, and the component handles rendering, scrolling, and input field management. It is automatically included with Shiny for Python but can be installed separately if needed.
Use it for
- Build a chatbot UI in a Shiny app that delegates message generation to an external LLM API.
- Create an interactive Q&A interface where user queries trigger backend computations and responses are appended to the chat.
- Prototype conversational data exploration tools that accept natural-language queries and display results.
- Add a support or help chat widget to an existing Shiny dashboard without writing custom HTML/JavaScript.
- Develop multi-turn dialogue systems where message history is maintained and used for context in subsequent calls.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building a Shiny for Python application that needs a chat interface.
The component is actively maintained, has no known vulnerabilities, low install friction, and integrates seamlessly with Shiny's reactive model. It is permissively licensed and already included with Shiny, so installing it separately is optional unless you need a specific version or want to use it outside a Shiny context.
Install
shinychat on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained with a recent release and no known vulnerabilities. Depends on htmltools, pydantic, and shiny—all stable, widely-used libraries.
Requires Python 3.10 or later and a working Shiny for Python environment.
License in practice
MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
Quickstart
pip install shinychat
from shiny.express import render, ui
from shinychat.express import Chat
chat = Chat(id="chat", messages=[{"content": "Hello!", "role": "assistant"}])
chat.ui()
@chat.on_user_submit
async def handle_input(user_input: str):
await chat.append_message(f"You said: {user_input}")Verify before relying
- Whether the package includes built-in LLM integration or only provides UI scaffolding for user-supplied models.
- Performance characteristics and message history size limits for typical chat applications.
- Styling and customization options beyond what the example demonstrates.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packageshtmltoolspydanticshiny |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 320,603 / month, #7,635 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: shinychat-0.6.1-py3-none-any.whl
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