WorkflowsApr 8, 2026·2 min read

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.

AI
AI Open Source · Community
Quick Use

Use it first, then decide how deep to go

This block should tell both the user and the agent what to copy, install, and apply first.

pip install taipy
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

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

2. Pipeline Orchestration

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

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

4. Multi-Page Apps

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. Licensed under Apache 2.0.

Avaiga/taipy — 15k+ stars

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