What the data for this category looks like
Medical beauty intelligent due diligence report data mainly comes from three types of channels: regulatory agency publicized medical beauty institution practice licenses, physician practice registration information, and medical advertising review certificates; internally archived surgical records and compliance rectification files from institutions; desensitized consumer feedback from third-party compliance platforms.
Data update rhythms: Regulatory public information is synced in real time, internal institutional files are updated quarterly, and third-party feedback is updated monthly.
Documents include structured qualification certificates (PDF, image formats), semi-structured surgical ledgers (spreadsheet documents), and unstructured regulatory announcements.
Fields include unified social credit code, practice license number, national standard code for medical beauty projects, and qualification validity period. Their respective units are string, numeric code, national standard project code, and year-month-day.
What constraints these characteristics impose on workflow orchestration
Medical beauty due diligence data includes image-based qualification files, spreadsheet-based ledgers, and unstructured announcements, and the update rhythms of data sources vary significantly. This creates core constraints for workflow orchestration:
- Configure a file type recognition node to distinguish uploaded qualification images from other file formats, to avoid parsing errors caused by mixed processing.
- Regulatory information requires real-time network access. Configure a stable HTTP request node to handle interface calls, and set up a timeout retry mechanism.
- Medical beauty projects need to match national standard codes. Add a field verification link to ensure input project codes comply with specifications, and add a sensitive information filtering node to process desensitized feedback data.
Since different data has different update cycles, set up periodically triggered workflow branches to adapt to the update rhythms of different data sources and avoid invalid calls.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_ALLOWED_TYPES | ["image/png", "image/jpeg", "application/pdf", "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"] | Covers core file formats required for medical beauty due diligence, such as qualification scans, qualification PDF files, and surgical ledger Excel files |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Parsing PDF qualification certificates or large surgical ledgers takes a long time, so reserve sufficient parsing time |
HTTP_REQUEST_RETRY_TIMES | 2 times | Temporary fluctuations may occur when calling regulatory interfaces over the network, and retries can reduce call failure rates |
FIELD_MATCH_RULE | Match codes in the Medical Beauty Project Hierarchical Management Catalog | Ensure that medical beauty project codes in due diligence data comply with industry unified standards, improving data validity |
CONTENT_MODERATION_SWITCH | Enabled | Sensitive information in consumer feedback needs to be filtered to meet compliance requirements |
WORKFLOW_TRIGGER_TYPE | Multi-cycle trigger: Trigger qualification data on demand, trigger institutional ledgers quarterly, update feedback data monthly | Adapt to the update rhythms of different data sources and optimize workflow execution efficiency |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material formats, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The symptom is that uploaded medical beauty qualification images are incorrectly parsed as text files, with empty output fields. The cause is that the
UPLOAD_FILE_ALLOWED_TYPESparameter is not configured, and allowed upload file types are not restricted, resulting in non-target files being mixed into the parsing process. - The symptom is that the workflow directly calls a large model to generate results without executing the preset HTTP request steps. The cause is incorrect workflow node connection order, the HTTP request node did not receive upstream trigger signals, or the node's trigger conditions are not correctly bound to upstream outputs.
- The symptom is that HTTP requests to regulatory interfaces return a 403 status code, causing workflow execution failure. The cause is that authentication parameters in the request header are not configured, and legitimate call permissions for the regulatory interface are not obtained.
How to confirm the configuration is complete
- Upload test files covering image, PDF, and Excel formats, and check whether the workflow triggers corresponding processing branches based on file types.
- Manually execute the workflow, check the running logs, and confirm that the HTTP request node is normally triggered and returns valid data.
- Input test codes that comply with national standard codes for medical beauty projects, and check whether the field verification node passes the verification.
- Upload test text containing sensitive information, and confirm that the content moderation node performs filtering operations.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.