Workflow Name: ☎️ Demo Call Center

Template was created in n8n v1.90.2

Skill Level: High

Categories: n8n, Chatbot

Stacks

• Execute Sub-workflow Trigger node
• Chat Trigger node
• Redis node
• Postgres node
• AI Agent node
• If node, Switch node, Code node, Edit Fields (Set)

Prerequisites

• Execute Sub-workflow Trigger: Telegram Call In Workflow (or your own node)
• Sub-workflow: Taxi Service (or your own node)
• Sub-workflow: Taxi Booking Worker (or your own node)
• Sub-workflow: Demo Call Back (or your own node)

Production Features

• Scaling Design for n8n Queue mode in production environment
• Optional Rate Limit design to prevent overused
• Optional Long Terms Memory design
• Multi-Service Design
• Testing Flow with or without dependency on other workflow.
• Error Management

What does this workflow do?

This is a n8n Demo Call Center Workflow demo. It is the main entry node for a Multiple Services Chatbot . It will receive message from the Call In Workflow , and decide which service should be used, or which service provider should be process the selected result.

How it works

• The Flow Trigger node will wait for the message from the Call In Workflow or other Sub-workflow.
• When message is received, it will first check for the Rate Limit.
• If ok, load the Session Data from Cache.
• Next, check the current Session for the channel_no (default is chat ).
• if channel_no is chat , continue to the AI ​​Agent for chit-chat.
• if channel_no is taxi or others, pass to the Service Input (ie Taxi Service ) or Service Worker (ie Taxi Booking Worker ) to handle it directly.
• The AI ​​Agent should decide which service (ie taxi ) will be used at some point and update the channel_no in Session, and pass to the Service Node (ie Taxi Service ) at once.
• In case of any error, reply the error in Call Back .

Setup instructions

1. Pull and Set up the required SQL from our Github repository .
2. Create you Redis credentials , refer to n8n integration documentation for more information.
3. Select your Credentials in Rate Limit, Session, Provider and New Session .
4. Create you Postgres credentials , refer to n8n integration documentation for more information.
5. Select your Credentials in Postgres Chat Memory, Load User Memory and Save User Memory.
6. Modify the AI ​​Agent prompt to fit your need

How to adjust it to your needs

1. In Session, we have a timestamp fields which is created at the Input node. The usage of this is combined to use with the session id to create a unique session, since some media, such as Telegram, do not have a unique session along with the chat.
2. You can use any AI Model for the AI ​​Agent node
3. Learn we use the prompt for the Load/Save User Memory on demand.
4. Includes is our prompt for the taxi service. You can add more service similar to this.