What Data for This Category Looks Like
Data sources for this category include health supervision information systems, medical institution electronic registration systems, complaint and reporting platforms, and law enforcement inspection records. The update frequency is monthly. Commonly processed documents include supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Document fields include institutional unified social credit codes, practice scope, inspection dates, rectification requirements, penalty reasons, and more. The field structures of each source system differ, so targeted matching and calls are required.
What Constraints Do These Characteristics Impose on HTTP Interfaces and External Systems
The scattered data sources and differing field structures for this category require HTTP interfaces to support multi-source field mapping and adaptation. This prevents document generation errors caused by incompatible data formats. The monthly update frequency means interface call frequency must be controlled. Overly short polling cycles should be avoided to reduce invalid requests. Diverse document types require interfaces to support document parsing and field extraction in different formats, adapting to the generation logic of documents such as supervision inspection forms and rectification notices. Additionally, data involves sensitive compliance information of medical institutions. Strict permission verification rules must be configured for the Authorization parameter to prevent sensitive data leaks.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {exclusive docking token} | Verifies external system access permissions, and adapts to sensitive data access rules of health supervision institutions |
variables | {"kb_id": "health supervision compliance knowledge base", "update_cycle": "monthly"} | Binds the exclusive knowledge base and data update cycle, matches the monthly update business rhythm of this category, and adapts to the variable binding rules of FastGPT v4.17.0 |
responseData | Extract the top 2-5 matching institutional qualification data | Focuses on the core qualification verification link, aligning with the core needs of daily supervision inspections |
| Single request timeout | 300-600 seconds | Adapts to the time consumption requirements of multi-source data pulling, avoiding request interruptions caused by large data volumes |
| Document parsing format | Supports PDF and structured table formats | Adapts to the parsing requirements of commonly used documents such as supervision inspection forms and penalty case files |
| Workflow trigger method | Triggered by external system callback | Adapts to the fixed monthly update rhythm, reducing resource occupation from active polling |
Three Common Mistakes
- Symptom: An error reading "Invalid knowledge base ID" is returned when calling the interface, or the preset health supervision knowledge base cannot be associated. Cause: The correct knowledge base ID is not passed in the
variablesparameter, or the passed ID does not match the actual ID stored in the FastGPT platform. - Symptom: The institutional qualification data pulled by the interface is empty, and information related to medical institution practice licenses cannot be pulled. Cause: The permission configuration scope of the
Authorizationparameter is insufficient, preventing access to the health supervision information system or medical institution electronic registration system data sources. - Symptom: After uploading a file by triggering a workflow via the API, the generated rectification notice has missing fields. Cause: Global variables are not correctly bound in the interface request, or the passed
variablesparameter does not include the corresponding field mapping rules for rectification requirements.
How to Confirm Configurations Are Correct
- Call the test interface, check whether the
responseDataincludes core fields such as the medical institution's unified social credit code and practice scope. A field matching degree that meets business requirements is acceptable. - Review the status codes returned by the interface, confirm that the frequency of normal status codes aligns with the preset call rhythm, and there are no frequent permission errors.
- Trigger the corresponding workflow on the FastGPT platform, check whether the generated supervision opinion includes the latest inspection date, rectification requirements and other content pulled from the external system.
- Upload a test supervision inspection form PDF file, confirm that the interface can normally parse and extract the inspection item data in the table.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.