# Taipy — Build AI Web Apps in Pure Python

> Create production AI web applications with Python only. Taipy handles frontend UI, data pipelines, and scenario management without JavaScript or HTML knowledge.

## Install

Copy the content below into your project:

## Quick Use

```bash
pip install taipy
```

```python
from taipy.gui import Gui
import taipy as tp

prompt = ""
response = ""

def chat(state):
    state.response = my_llm(state.prompt)  # Your LLM call

page = (
    "# AI Chat\\n"
    "<|{prompt}|input|>\\n"
    "<|Send|button|on_action=chat|>\\n"
    "<|{response}|text|>"
)

Gui(page).run()
```

## What is Taipy?

Taipy is a Python framework for building production-grade AI web applications. Unlike Streamlit or Gradio which are designed for prototypes, Taipy handles complex data pipelines, multi-user scenarios, and enterprise deployment. You write pure Python — no JavaScript, HTML, or CSS required.

**Answer-Ready**: Taipy is a Python framework for production AI web apps. Handles UI, data pipelines, and scenario management in pure Python. Enterprise-ready alternative to Streamlit/Gradio. Multi-user support, pipeline orchestration. 15k+ GitHub stars.

**Best for**: Data scientists deploying AI apps to production. **Works with**: Any Python ML library, LLM APIs, Claude, GPT. **Setup time**: Under 5 minutes.

## Core Features

### 1. Visual UI Builder

```python
page = (
    "<|{data}|chart|type=bar|x=category|y=value|>\\n"
    "<|{df}|table|>\\n"
    "<|{slider_val}|slider|min=0|max=100|>"
)
```

### 2. Pipeline Orchestration

```python
from taipy import Config

input_cfg = Config.configure_data_node("input_data")
output_cfg = Config.configure_data_node("output_data")
task_cfg = Config.configure_task("process", function=my_ai_model, input=[input_cfg], output=[output_cfg])
scenario_cfg = Config.configure_scenario("ai_pipeline", task_configs=[task_cfg])
```

### 3. Scenario Management

```python
scenario = tp.create_scenario(scenario_cfg)
tp.submit(scenario)
# Compare multiple AI model runs
# Track versions, parameters, results
```

### 4. Multi-Page Apps

```python
pages = {
    "/": root_page,
    "/dashboard": dashboard_page,
    "/settings": settings_page,
}
Gui(pages=pages).run()
```

## Taipy vs Alternatives

| Feature | Taipy | Streamlit | Gradio |
|---------|-------|-----------|--------|
| Multi-user | Yes | Limited | Limited |
| Pipeline orchestration | Built-in | No | No |
| Scenario comparison | Yes | No | No |
| Production deployment | Enterprise | Basic | Basic |
| Callbacks | Native | Rerun model | Events |

## FAQ

**Q: How does it compare to Streamlit?**
A: Taipy is designed for production. It supports multi-user, pipeline orchestration, and scenario management. Streamlit reruns scripts on every interaction.

**Q: Can I style the UI?**
A: Yes, supports CSS customization and theme configuration.

**Q: Does it support real-time updates?**
A: Yes, built-in WebSocket support for live data.

## Source & Thanks

> Created by [Avaiga](https://github.com/Avaiga). Licensed under Apache 2.0.
>
> [Avaiga/taipy](https://github.com/Avaiga/taipy) — 15k+ stars

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## 快速使用

```bash
pip install taipy
```

纯 Python 构建生产级 AI Web 应用。

## 什么是 Taipy？

Taipy 是纯 Python 的生产级 AI Web 应用框架。不同于 Streamlit/Gradio 的原型定位，Taipy 支持复杂数据管线、多用户场景和企业部署。

**一句话总结**：纯 Python 生产级 AI Web 应用框架，内置 UI、管线编排和场景管理，Streamlit/Gradio 的企业替代方案，15k+ stars。

**适合人群**：将 AI 应用部署到生产环境的数据科学家。

## 核心功能

### 1. 可视化 UI
Python Markdown 语法定义界面组件。

### 2. 管线编排
配置式数据管线，自动依赖管理。

### 3. 场景管理
多版本对比，参数追踪。

## 常见问题

**Q: 和 Streamlit 比？**
A: Taipy 面向生产，支持多用户和管线编排，Streamlit 每次交互重跑脚本。

## 来源与致谢

> [Avaiga/taipy](https://github.com/Avaiga/taipy) — 15k+ stars, Apache 2.0

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Source: https://tokrepo.com/en/workflows/18c2908b-e126-4ca2-84de-06f4b3fd7325
Author: AI Open Source