> For the complete documentation index, see [llms.txt](https://docs.tabiya.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tabiya.org/tabiya-documentation/es/nuestra-pila-tecnologica/livelihoods-classifier/web-application.md).

# Aplicación web

Para facilitar su uso, desarrollamos una aplicación FullStack simple (una API basada en Flask como BackEnd y un FrontEnd con jQuery) para analizar descripciones de puestos y predecir ocupaciones, habilidades y cualificaciones relevantes mediante el modelo de vinculación de entidades.

### Uso

Primero, activa el entorno virtual como se explica [aquí](/tabiya-documentation/es/nuestra-pila-tecnologica/livelihoods-classifier/getting-started.md#dep). Luego, ejecute el siguiente comando en Python en la `raíz` directorio:

#### Ejecución de la API

**Ejecute la aplicación Flask**:

```bash
python app/server/matching.py
```

O establezca la variable de entorno de la aplicación Flask y use el comando Flask:

```bash
export FLASK_APP=app/server/matching.py
flask run --host=0.0.0.0 --port=5001
```

### Uso de ejemplo

1. **Abra el navegador** y vaya a `http://127.0.0.1:5001/`.
2. **Pegue una descripción del puesto** en el área de texto proporcionada.
3. **Haga clic en el botón "Analizar puesto"** para enviar la descripción del puesto al `/match` endpoint.
4. **Vea los resultados** debajo de "Ocupaciones previstas," "Habilidades previstas," y "Cualificaciones previstas."

{% hint style="danger" %}
Esta aplicación es solo para fines de demostración. Si desea desplegar este modelo, utilice una estrategia más fiable/segura.
{% endhint %}


---

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