What Data for This Category Looks Like
Medical aesthetics financial report data primarily comes from publicly disclosed annual, semi-annual, and quarterly audit reports of listed medical aesthetics institutions, as well as institutional operation data regularly aggregated by industry self-regulatory organizations. Data updates align with fixed disclosure cycles. Individual documents vary widely in length, ranging from a few pages to dozens of pages. Core fields in the documents include revenue breakdowns, customer unit prices, store operation data, marketing investment amounts, with units including ten thousand yuan, yuan, number of locations, etc. Some segmented categories such as light medical aesthetics and surgical medical aesthetics split independent data for their respective business modules.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Multi-turn dialogue must clearly define the current business module being analyzed, due to the multi-document structure and segmented category split features of medical aesthetics financial reports. This prevents the large model from confusing cross-category data. Fixed update cycles and resulting new data synchronization requirements mean knowledge base configurations must support batch file uploads per disclosure cycle, and multi-turn dialogue must guide users to clarify the reference financial report cycle. Wide variation in document length creates uneven effective information density in single documents, so retrieval rules must be adjusted to cover core business fields while avoiding redundant information interfering with dialogue logic. Diversity of units requires prompts to clearly specify the statistical unit of numerical values, to prevent analysis results with mismatched units.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
segment length | 800–1200 characters | Aligns with the length of core business content on a single medical aesthetics financial report page, and avoids breaking the logical integrity of associated fields such as revenue and customer unit price after splitting |
retrieval count | top 6–8 passages | Covers relevant passages of core business modules such as revenue composition, store data, and marketing investment in medical aesthetics financial reports, and avoids missing key information |
similarity threshold | 0.75–0.85 | Filters out redundant administrative and personnel-related fragments irrelevant to medical aesthetics financial report analysis, while retaining relevant content for segmented categories such as light medical aesthetics and surgical medical aesthetics |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapts to the wide variation in length of medical aesthetics financial report documents, ensures complete parsing of long documents and avoids mid-parsing timeout interruptions |
knowledge base sync cycle | quarterly | Matches the disclosure cycles of quarterly, semi-annual, and annual medical aesthetics financial reports, and ensures timeliness of knowledge base data |
citation content template | 【Financial Report Passage】{{content}}【/Financial Report Passage】 | Clearly marks the boundaries of retrieved passages, helps the large model accurately identify referenced knowledge base content and avoid confusion between general knowledge and financial report data |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Each scenario requires individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: Dialogue response results do not reference the specified medical aesthetics financial report file in the knowledge base, and only generate answers based on general knowledge. Cause: The prompt does not explicitly specify prioritizing use of retrieved knowledge base passages, or the citation content template is configured incorrectly, preventing the large model from identifying referenced content.
- Phenomenon: After calling the interface to create a knowledge base, the dialogue interface cannot associate the newly created knowledge base, and the returned results contain no relevant financial report data. Cause: The interface request does not carry the correct knowledge base binding parameters, or the knowledge base is called before completing parsing verification.
- Phenomenon: Unit-confused analysis results appear in multi-turn dialogue, such as mislabeling ten thousand yuan revenue as yuan. Cause: The prompt does not clearly require unified statistical units, and no unit verification guidance logic is added to the configuration.
How to Verify Proper Configuration
- Upload a single medical aesthetics financial report document, view the parsed segment list, confirm that the segment length falls within the preset range, and that core business fields are not split into unrelated paragraphs.
- Initiate a test dialogue, ask about the revenue composition of medical aesthetics institutions within a specified cycle, check whether the returned results reference the corresponding passages in the knowledge base, and that no unrelated content appears.
- Call the interface to create a knowledge base, then send an association request via the dialogue interface, confirm that the returned results contain data from the knowledge base and that no error prompts appear.
- Adjust the similarity threshold to different ranges, compare the retrieved passage content, confirm that the threshold setting can filter non-core administrative information and retain business-related passages.
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.