What the Category Data Looks Like
Sources for medical aesthetics due diligence data include practicing registration materials of medical aesthetics institutions, local health department public databases for medical aesthetics project announcements, doctor practicing qualification files, traceability documents from consumable suppliers, and compliance inspection records from industry associations. Materials reported by institutions are updated in real time, while regulatory announcement information is synchronized every quarter. The document structure is divided into four modules: qualification, project, personnel, and consumables. Each module includes a unique code field, effective date field, and validity period field. Most fields use string-formatted numbers or date formats, with no numeric quantitative fields.
Constraints for Multi-turn Dialogue and Prompt Engineering
Medical aesthetics due diligence data is divided into four modules and includes unique codes and date fields. Multi-turn dialogue must split questions by module while retaining context associations to avoid cross-module confusion. Most fields use code or date formats, so prompts must clearly specify extraction rules for each field to prevent generation of non-compliant formatted content. The data update rhythm includes real-time and quarterly synchronization, so dialogue must support confirming the latest synchronization status of data to avoid using expired registration information. Association relationships exist between modules—for example, doctor qualifications must be bound to their practicing institutions. Multi-turn dialogue must allow recalling prior query results to complete association validation.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxHistory | Previous 3 turns of dialogue | Medical aesthetics due diligence data is divided into four modules. 3 turns of context cover association queries for qualification, project, and personnel, avoiding interference from redundant information |
contextTokenLimit | 8000–12000 characters | A single medical aesthetics due diligence document is approximately 2000–3000 characters. Multi-module association queries require retaining context for 2–3 documents. This range meets requirements and prevents token overflow |
promptTemplate | Extract medical aesthetics due diligence fields by module. The qualification module must include practice license number and validity period, the project module must include registration number and effective date, with date format as YYYY-MM-DD | The format of medical aesthetics due diligence fields is clearly defined. This template constrains the format and module division of generated results, avoiding confusion between different categories of data |
historySaveDuration | 90 days | Regulatory announcement information for medical aesthetics is updated every quarter. 90 days covers the latest quarterly update cycle while preventing expired data from occupying storage |
fileParseTimeout | 300 seconds | Medical aesthetics due diligence documents are mostly multi-page compliance materials with long parsing times. 300 seconds covers the complete parsing process |
UPLOAD_FILE_MAX_SIZE | 100 MB | Medical aesthetics due diligence documents are mostly scanned copies or PDFs, with a single document typically not exceeding 50 MB. This value covers most scenarios |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: An error occurs when calling the document parsing tool after configuring a file upload node in the workflow. Cause: The
UPLOAD_FILE_MAX_SIZEparameter was not adjusted, and the uploaded medical aesthetics due diligence document exceeded the default limit. - Issue: When accessing the workflow with the same ID multiple times, the context from the first model call does not retain valid information. Cause: The
maxHistoryparameter is set to 1, which only retains the last 1 turn of dialogue and cannot associate prior query conditions. - Issue: The date field format in the generated due diligence report is inconsistent, including Chinese dates or incorrect numeric values. Cause: No targeted
promptTemplatewas configured, and no clear date format requirements were specified.
How to Verify Correct Configuration
- Upload a single medical aesthetics due diligence document, trigger workflow execution, and confirm that the dialogue context retains the preset number of historical information turns.
- Initiate multi-turn association queries, and confirm that the due diligence fields generated by the model comply with the preset format and module division rules.
- View the dialogue history management interface, and confirm that saved dialogue records fall within the preset duration range.
- Upload a medical aesthetics due diligence document of conventional size, verify that the document parsing process has no errors and the generated results are complete.
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.