AI Chatbot Call Center: Taxi Service (Production-Ready, Part 3)

Description

Workflow Name: 🛎️ Taxi Service

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)

Prerequisite

Execute Sub-workflow Trigger: Taxi Service Workflow (or your own node)
Sub-workflow: Taxi Service Provider (or your own node)
Sub-workflow: Demo Call Back (or your own node)

Production Features

Scaling Design* for n8n *Queue mode** in production environment
Service Data* from *external Database* with *Caching Mechanism**
Optional Long Terms Memory design
Find Route Distance* using *Google Map API**
Optional Multi-Language Wait Output example
Error Management**

What this workflow does?

This is a n8n Taxi Service Workflow demo. It is the core node for Taxi Service. It will receive message from the Call Center Workflow, handling the QA from the caller, and pass to each of the Taxi Service Provider Workflow to process the estimation.

How it works

The Flow Trigger node will wait for the message from Call Center or other Sub-workflow.
When message is received, it will first check for the matching Service from the PostgreSQL database.
If no service or service is inactive, output Error.
Next, always reset the Session Data in Cache, with channel_no set to taxi
Next, delete the previous Route Data in Cache
Trigger a AI Agent to process the fare estimation question to create the Route Data
Use the Google Map Route API to calculate the distance.
Repeat until created the route data, then pass to all the Taxi Service Provider for an estimation.

Set up instructions

Pull and Set up the required SQL from our Github repository.
Create you Redis credentials, refer to n8n integration documentation for more information.
Select your Credentials in Service Cache, Save Service Cache, Reset Session, Delete Route Data, Route Data, Update User Session and Create Route Data.
Create you Postgres credentials, refer to n8n integration documentation for more information.
Select your Credentials in Load Service Data, Postgres Chat Memory, Load User Memory and Save User Memory.
Modify the AI Agent prompt to fit your need
Set you Google Map API key in Find Route Distance

How to adjust it to your needs

By default, this template will use the sys_service table provider information, you could change it for your own design.
You can use any AI Model for the AI Agent node
Learn we use the prompt for the Load/Save User Memory on demand.
Include is our prompt for the taxi service. It is a flexible design which use the data from the Service node to customize the prompt, so you could duplicate this workflow as another service.
Create difference Taxi Providers to process the and feedback the estimate.