AI prompts
base on 🧙 Build, run, and manage data pipelines for integrating and transforming data. <div align="left">
<h1>Mage AI</h1>
<p>Give your data team magical powers.</p>
<a href="https://mage.ai"><img alt="Mage AI GitHub repo stars" src="https://img.shields.io/github/stars/mage-ai/mage-ai?style=for-the-badge&logo=github&labelColor=000000&logoColor=FFFFFF&label=stars&color=0500ff" /></a>
<a href="https://hub.docker.com/r/mageai/mageai"><img alt="Mage AI Docker downloads" src="https://img.shields.io/docker/pulls/mageai/mageai?style=for-the-badge&logo=docker&labelColor=000000&logoColor=FFFFFF&label=pulls&color=6A35FF" /></a>
<a href="https://github.com/mage-ai/mage-ai/blob/master/LICENSE"><img alt="Mage AI license" src="https://img.shields.io/github/license/mage-ai/mage-ai?style=for-the-badge&logo=codeigniter&labelColor=000000&logoColor=FFFFFF&label=license&color=FFCC19" /></a>
<a href="https://www.mage.ai/chat"><img alt="Join the Mage AI community" src="https://img.shields.io/badge/Join%20the%20community-black.svg?style=for-the-badge&logo=lightning&labelColor=000000&logoColor=FFFFFF&label=&color=DD55FF&logoWidth=20" /></a>
</div>
<br />
<a href="https://mage.ai/pro">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/mage-ai/assets/blob/main/oss/hero.png?raw=true">
<img alt="Mage AI hero" src="https://github.com/mage-ai/assets/blob/main/oss/hero.png?raw=true" />
</picture>
</a>
<br />
<br />
Mage is a hybrid framework for transforming and integrating data. It combines the best of both worlds: the flexibility of notebooks with the rigor of modular code.
<br />
- Extract and synchronize data from 3rd party sources.
- Transform data with real-time and batch pipelines using Python, SQL, and R.
- Load data into your data warehouse or data lake using our pre-built connectors.
- Run, monitor, and orchestrate thousands of pipelines without losing sleep.
<br />
Plus hundreds of enterprise-class features, infrastructure innovations, and magical surprises.
<h1></h1>
#### Available in two spellbinding versions
<br />
<table style="width: 100%; border: none;" cellspacing="0" cellpadding="0" border="0">
<tr>
<td rowspan="2">
<a href="https://mage.ai/pro">
<img alt="Mage Pro" width="124" align="left" src="https://github.com/mage-ai/assets/blob/main/oss/card-pro.png?raw=true" />
</a>
<b>For teams.</b> Fully managed platform
for integrating and transforming data.
</td>
<td rowspan="2">
<a href="https://github.com/mage-ai/mage-ai?tab=readme-ov-file#its-magic">
<img alt="Mage OSS" width="124" align="left" src="https://github.com/mage-ai/assets/blob/main/oss/card-oss.png?raw=true" />
</a>
<b>Self-hosted.</b> System to build, run, and
manage data pipelines.
</td>
</tr>
</table>
<br />
<a href="https://mage.ai/pro">
<img alt="Try out Mage Pro" src="https://img.shields.io/badge/try%20it%20out%20now-black.svg?style=for-the-badge&logo=artifacthub&labelColor=6A35FF&logoColor=FFFFFF&label=mage%20pro&color=6A35FF">
</a>
<br />
<br />
<div align="left">
# It’s magic.
<p align="left">
For documentation on getting started, how to develop, and how to deploy to production check out the live
<br />
<a
href="https://docs.mage.ai?source=github"
target="_blank"
><b>Developer documentation portal</b></a>.
</p>
<br />
## 🏃♀️ Install
The recommended way to install the latest version of Mage is through Docker with the following command:
```bash
docker pull mageai/mageai:latest
```
You can also install Mage using pip or conda, though this may cause dependency issues without the proper environment.
```bash
pip install mage-ai
```
```bash
conda install -c conda-forge mage-ai
```
Looking for help? The _fastest_ way to get started is by checking out our documentation [here](https://docs.mage.ai/getting-started/setup).
Looking for quick examples? Open a [demo](https://demo.mage.ai/) project right in your browser or check out our [guides](https://docs.mage.ai/guides/overview).
## 🎮 Demo
### Live demo
Build and run a data pipeline with our <b>[demo app](https://demo.mage.ai/)</b>.
> WARNING
>
> The live demo is public to everyone, please don’t save anything sensitive (e.g. passwords, secrets, etc).
### Demo video (5 min)
[](https://youtu.be/GswOdShLGmg)
<sub><i>Click the image to play video</i></sub>
<br />
## 🔮 [Features](https://docs.mage.ai/about/features)
| | | |
| --- | --- | --- |
| 🎶 | <b>[Orchestration](https://docs.mage.ai/design/data-pipeline-management)</b> | Schedule and manage data pipelines with observability. |
| 📓 | <b>[Notebook](https://docs.mage.ai/about/features#notebook-for-building-data-pipelines)</b> | Interactive Python, SQL, & R editor for coding data pipelines. |
| 🏗️ | <b>[Data integrations](https://docs.mage.ai/data-integrations/overview)</b> | Synchronize data from 3rd party sources to your internal destinations. |
| 🚰 | <b>[Streaming pipelines](https://docs.mage.ai/guides/streaming-pipeline)</b> | Ingest and transform real-time data. |
| ❎ | <b>[dbt](https://docs.mage.ai/dbt/overview)</b> | Build, run, and manage your dbt models with Mage. |
<br />
<b>A sample data pipeline defined across 3 files ➝</b>
<br />
1. Load data ➝
```python
@data_loader
def load_csv_from_file() -> pl.DataFrame:
return pl.read_csv('default_repo/titanic.csv')
```
1. Transform data ➝
```python
@transformer
def select_columns_from_df(df: pl.DataFrame, *args) -> pl.DataFrame:
return df[['Age', 'Fare', 'Survived']]
```
1. Export data ➝
```python
@data_exporter
def export_titanic_data_to_disk(df: pl.DataFrame) -> None:
df.to_csv('default_repo/titanic_transformed.csv')
```
<br />
[<img alt="Water mage casting spell" height="300" src="https://github.com/mage-ai/assets/blob/main/mage-water-charging-up.svg?raw=True" />](https://www.mage.ai/)
", Assign "at most 3 tags" to the expected json: {"id":"7871","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"