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Guía del usuario de Maestro
- Introducción
- Primeros pasos
- Crear con Maestro BPMN
- Comprender el modelado de Maestro BPMN
- Abrir el lienzo de modelado
- Modelar tu proceso
- Alinear y conectar elementos BPMN
- Autopilot para Maestro (vista previa)
- Repositorio de procesos
- Implementar un proceso BPMN simple
- Implementar un proceso BPMN complejo
- Depuración
- Simular
- Escenarios de implementación comunes
- Crear con Maestro Case
- Introducción a Maestro Case
- Maestro BPMN frente a Maestro Case: cuándo utilizar la gestión de casos
- El ciclo de vida de Maestro Case: del desencadenador de eventos a la experiencia de la aplicación
- Crea tu primer caso con Maestro Case
- Build a Maestro Case with a coding agent (preview)
- Definir claves de caso (de sistema o externo)
- Establecer contratos de entrada/salida y de escritura diferida de tareas
- Reglas de salida y terminación temprana de etapas
- Modelar las etapas principal y secundaria
- Iniciar un caso desde Data Fabric
- Implementar perfiles y permisos a nivel de etapa
- Establecer SLA y reglas de escalado automatizadas
- Configurar un bucle de reprocesamiento (reingreso)
- Configuring and testing the Case Manager Agent (preview)
- Contrato de entrada y salida del gestor de casos
- Diccionario de componentes de Maestro Case
- Crear con Maestro Flow
- Nodos del conector
- Integraciones
- En funcionamiento
- Supervisión
- Optimizando
- Información de referencia
Importante :
La localización de contenidos recién publicados puede tardar entre una y dos semanas en estar disponible.
Chat nodes for modeling conversational experiences in Maestro Flow, covering routing control, conversational AI turns, and deterministic messages.
The Chat nodes build a conversational Flow. Once deployed, it reaches end-users through every chat channel supported for conversational agents — iFrame embeds, Assistant, Microsoft Teams, Slack, and custom surfaces built with the UiPath TypeScript SDK. Monitor its performance, metrics, and user feedback through chat agent observability.
Nodos disponibles
| Nodo | Lo que hace |
|---|---|
| Conversation Trigger | Marks the Flow as conversational and starts it when a user initiates a chat on any channel. |
| Esperar mensaje | Suspends until the user sends a message, then outputs the latest conversation context (chat history) for downstream nodes to consume. |
| Agente conversacional | Runs a single chat agent turn. Streams its responses and takes actions through tool-calls. |
| Enviar mensaje | Writes an arbitrary message to the conversation. Use for fixed replies, routing messages, and emitting data from other nodes to the chat. |
| Get Conversation Context | Reads the current conversation history and metadata without suspending the Flow. Generally not needed, but can be used when a downstream node needs to inspect latest chat messages without waiting for new input. |
Capability examples
Combine the conversational nodes with the rest of Flow's palette to unlock a variety of capabilities, such as:
- Deterministic branching — route to different node paths based on message content or agent output.
- Agent hand-off — pass the conversation between multiple conversational agents, each with its own prompt and tools.
- Parallel branches — launch any other Flow branches in parallel - such as human approval tasks - while the conversation continues seamlessly to the user.
- Chat termination — end the conversation when a goal is reached.
- Zero-agent conversations — build a fully deterministic chat experience with no LLM turns at all.
End-to-end walkthrough
Visit build a chat agent workflow for a step-by-step example that combines the chat nodes into an agent-handoff routing pattern.
Relacionado
- Chat conversational agents — surface overview in the Agents user guide.
- Chat deployment — publish to Orchestrator and expose through Instance Management, Assistant, Teams, Slack, iFrame, or the TypeScript SDK.