What the Data for This Category Looks Like
Medical aesthetics research report data primarily comes from industry association compliant filing documents, market research from third-party medical aesthetics data institutions, technical white papers from medical aesthetics consumable manufacturers, quarterly operational disclosures from compliant medical aesthetics institutions, and excerpts of industry compliance guidelines released by medical aesthetics regulatory authorities.
Data update cadence is divided into monthly, quarterly, and annual: monthly updates cover industry compliance dynamics and single-procedure price monitoring; quarterly updates cover market parameters for segmented categories such as injection-based and surgical-based procedures; annual releases cover overall industry development white papers.
Document structure includes four core sections: executive summary, segmented category parameter table, compliance requirements description, and typical case analysis. Unique fields include "Compliance Filing Number", "Single Operation Dosage (Unit: Units/mL)", "Customer Unit Price (Unit: Yuan/Person-Time)", "Treatment Cycle (Unit: Weeks)", and all data includes a source annotation field.
What Constraints These Characteristics Impose on the Tool Calling and Plugins Workflow
The multi-source and dispersed nature of medical aesthetics research reports requires tool calling plugins to support aggregation and parsing of multiple data sources. Plugins must adapt to different formats of filing documents, research reports, and technical white papers to avoid field extraction errors caused by failed format parsing.
Unique professional fields and units require automatic matching of parameter units during tool calling, to prevent retrieval deviations caused by inconsistent dosage and price units. For example, automatically map the association between "units" and "milliliters".
Data with different update cadences requires plugins to be configured with scheduled incremental pull rules, to avoid excessive server resource usage from full pull operations. Plugins must also handle field changes caused by data version differences.
The long document structure requires the tool calling process to support segmented parsing and context retention, to ensure complete matching of professional fields and avoid parameter recognition errors caused by context truncation.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chatId | Required, format: 医美研报检索-YYYYMMDD | Used to distinguish research report retrieval requests for different sessions, matching the user identifier in backend logs |
globalVariables | Configured as {"medicalReportScope": "合规备案数据"} | Binds exclusive retrieval dimensions for medical aesthetics research reports, resolving issues where global variables do not take effect |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Single medical aesthetics research report documents have relatively long length, requiring extended parsing timeout |
recallTopK | Top 8 results | Medical aesthetics research reports have many segmented fields, requiring sufficient candidate results to cover professional parameters |
similarityThreshold | 0.75–0.85 | Filters low-match non-medical aesthetics professional data, preventing irrelevant results from being included |
streamMode | Enabled | Adapts to large models that only support stream mode, avoiding call failures |
API_KEY_AUTH | Validation enabled | Prevents unauthorized calls, matching the protection requirements for the unAuthApiKey error |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing values.
Three Common Misconfigurations
- Symptom: The backend log does not display the corresponding identifier after passing the
chatIdparameter when calling the API. Cause: The session identifier binding configuration is not enabled in the FastGPT backend, or the passed format does not meet requirements. - Symptom: Retrieval results do not match the new global variable value after updating the global variable during tool calling. Cause: Global variable synchronization is not enabled in the plugin configuration, or the variable update timing is later than the retrieval trigger.
- Symptom: Calling the API returns the error
{"code":514,"statusText":"unAuthApiKey"}. Cause: A valid API key validation configuration is not set, or the key permission is not bound to the medical aesthetics research report retrieval plugin.
How to Confirm Successful Configuration
- Initiate a test request, check the backend conversation log, and confirm that the
chatIdfield is correctly displayed in the request parameters. - Modify the global variable value, initiate a retrieval request, and verify that the returned results match the new variable configuration.
- Call the API and check the returned status code, confirming that no
unAuthApiKeyrelated errors appear. - Call a large model that only supports stream mode, confirm that the returned results are output in streaming segments.
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.