Coze Studio's plug-in system is designed with a standardized interface and works on three levels:
- protocol layer: Define request/response format based on OpenAPI specification
- implementation layer: Isolating the runtime environment through Docker containers to ensure security
- scheduling layer: The workflow engine dynamically loads the plugin description file and handles the input-output mapping
Step-by-step instructions for developing a weather checker plugin:
- Creating plug-in templates: Select "New Plugin" in the console to set the unique identifier and base metadata
- Configuring the API Interface: Fill in the OpenAPI address of the weather service (e.g. Wabi Wabi Weather API), define the query parameters (city code/date, etc.)
- Designing Response Structures: mapping JSON fields returned by the API to structured data (temperature/humidity/wind) recognizable by the smart body
- Test Release: Add plug-in nodes to the workflow after saving, and enter test parameters to verify the accuracy of data return
Advanced development skills:
- Support JWT authentication and other security mechanisms to protect API keys
- Configurable caching policies to reduce duplicate requests
- Complex logic, such as dynamic parameter generation, is available through the Python SDK.
- Error Handling Proposal to Implement a "Service Degradation" Mechanism to Ensure Availability
This answer comes from the articleCoze Studio (Coze Open Source Edition): an open source low-code platform for rapidly building AI intelligencesThe
May not be reproduced without permission:AI productivity tools " How does Coze Studio's plugin system work? What are the steps required to develop a weather check plugin?
