What the data for this category looks like
Data sources for this category include the health supervision information system, medical institution electronic registration system, complaint and reporting platform, and law enforcement inspection records. Data update frequency is monthly. Commonly processed documents are supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Data fields cover basic institution information, licensing qualifications, inspection records, rectification requirements, penalty results, and additional relevant content. Fields and units vary based on the corresponding document type, with no unified fixed format or units.
Constraints for HTTP APIs and External Systems
Multi-source data access requires APIs to support authentication adaptation and data format matching for different systems. The monthly update frequency eliminates the need for high-frequency API synchronization, allowing fixed-period pull tasks to be configured. Handling multiple document types requires APIs to support parsing both structured and unstructured document content. Field variation across document types requires the response data format returned by APIs to be flexible, adapting to field differences across different business documents. Business error outcomes directly tie to API data accuracy, so the integrity and consistency of data returned by APIs must be maintained.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer ${custom token} | Complies with general authentication specifications for external systems |
variables | {"scope": "health supervision data", "period": "monthly"} | Limits the business scope and time cycle for API queries |
| Response data extraction | Extract core business fields from responseData | Focus on content required for supervision inspection, qualification verification, and related tasks |
| Cache period | 720 hours | Matches the monthly data update frequency to avoid unnecessary pull requests |
| Timeout setting | 60 seconds | Adapts to average response latency for multi-system integration |
| Retry strategy | Retry 2 times after failure, with a 5 second interval | Addresses temporary network fluctuations or short-lived API anomalies |
Three Common Misconfigurations
- A 400 status code is returned when calling the API, with a prompt indicating incorrect parameter format. This occurs when the
Authorizationauthentication parameter is not configured correctly, or there is a syntax issue in the JSON format of the request variables. - Specified file content cannot be obtained when loading external documents. This occurs when the
CUSTOM_READ_FILE_URLenvironment variable is not configured correctly, or the entered address cannot be accessed normally by the system. - The API return result does not include the required supervision inspection data. This occurs when the business scope is not limited in
variables, resulting in the pull of irrelevant non-health supervision data.
How to Confirm Proper Configuration
- Call the test API, check whether the returned
responseDataincludes core business fields such as supervision inspection forms and practice licenses, and confirm field completeness based on business requirements. - Check the validity of the authentication configuration: call the API with an invalid token, confirm that a 401 status code is returned, to verify that the authentication logic functions correctly.
- View the API call logs, confirm that the request cycle matches the cache period, and there are no high-frequency unnecessary calls.
- Simulate a data update scenario, trigger an API pull, and confirm that the update time of the returned data matches the monthly update frequency.
The values listed above are common starting points, and should be evaluated against the reader's own specific 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.