AI chatbot call center: Taxi service (Production-ready, part 3)

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

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 Service Cache, Save Service Cache, Reset Session, Delete Route Data, Route Data, Update User Session and Create Route Data.
4. Create you Postgres credentials, refer to n8n integration documentation for more information.
5. Select your Credentials in Load Service Data, Postgres Chat Memory, Load User Memory and Save User Memory.
6. Modify the AI Agent prompt to fit your need
7. Set you Google Map API key in Find Route Distance

How to adjust it to your needs

1. By default, this template will use the sys_service table provider information, you could change it for your own design.
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. 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.
5. Create difference Taxi Providers to process the and feedback the estimate.