E-commerce customer service scene landing program
Combined with the features described in the article, the implementation of an e-commerce customer service bot can be done in three steps:
- infrastructure::
1. CreationCustomerServiceAgentInheritance Base Agent
2. Use state to store user shopping cart and order data
3. Configure HTTP routing to interface with the commodity database API - business logic::
- Frequently asked questions library: pre-set Q&A pairs to deal with high-frequency questions
- Order Inquiry: viafetchCalling the backend API to get real-time data
- Return process: managing multi-step interactions using state machines - enhancement::
1. WebSocket push notification of inventory changes
2. React front-end integration to achieve rich interactive interface
3. Using AI models for complex semantic understanding
Deployment Scenario: It is recommended to create separate Agent instances for each language region, utilizing the Cloudflare global network to ensure low latency. Critical data needs to be backed up to R2 storage on a regular basis.
This answer comes from the articleCloudflare Agents: building real-time interactive intelligences on edge networksThe
May not be reproduced without permission:AI productivity tools " How to apply Cloudflare Agents for intelligent answering in e-commerce customer service scenarios?
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