What the data for this category looks like
Medical aesthetic marketing content data primarily comes from internal compliance project filing documents of the organization, promotional material libraries compiled by the marketing team, publicly available compliant materials from partnered medical aesthetic platforms, and user consultation history records. Update frequency adjusts with compliance policy changes, new project launches, and quarterly marketing node shifts, with no fixed cycle. Document structure typically categorizes content by project type: plastic surgery, skin care, anti-aging, and others. Each category includes fields such as project name, qualification filing number, applicable population range, prohibited scenarios, promotional speech specifications, and associated material links. Most fields are text or link types, with no complex numerical units.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Compliance requirements for medical aesthetic marketing content mandate that prompts for multi-turn dialogue embed compliance verification logic. Each output must be checked against the filing information of the current project to avoid promotional content beyond compliance scope. The presence of multiple project categories requires the context window to be filtered by the project dimension associated with the current conversation, to prevent historical contexts of different projects from confusing model judgments. The scattered nature of user consultation history requires that only the most recent 3 rounds of precise requests be retained in the context, to reduce interference from irrelevant information on the model. The feature of associated material links requires that prompts be configured with file retrieval trigger rules, to ensure that compliant material resources can be attached to outputs.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContextTokens | 8000–12000 characters | Medical aesthetic marketing conversations involve project details and compliance checks. Excessively long contexts can trigger token overflow. This range covers the needs of conventional multi-turn consultations |
contextFilterRule | Filter by current conversation project category | There are many categories of medical aesthetic projects. Filtering irrelevant contexts prevents the model from confusing compliance requirements and user requests across different projects |
promptTemplateType | Category-bound | Promotional speech specifications vary significantly across different medical aesthetic projects. Category-bound prompts can accurately match corresponding compliance requirements |
fileUploadMaxSize | ≤50 MB | Medical aesthetic marketing materials include long documents and high-resolution case images. This limit balances material availability and interface processing efficiency |
responseComplianceCheck | Enabled, linked to filing field verification | Medical aesthetic promotions must comply with regulatory requirements. The verification step ensures that output speeches match the project scope and compliance terms specified in filings |
multiModelTokenStrategy | Independent counting | When orchestrating multiple models, token consumption varies widely across different medical aesthetic project conversations. Independent counting prevents single-model token limits from disrupting the workflow |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- A
413 Request Entity Too Largeerror or total token consumption limit breach occurs during multi-model orchestrated conversations. This happens whenmultiModelTokenStrategyis not set to independent counting, causing cumulative token consumption across multiple models to exceed limits. - The model confuses different users' medical aesthetic requests during multi-turn dialogue, outputting project content unrelated to prior questions. This occurs when
contextFilterRuleis not configured to filter by current conversation project category, retaining full historical context and causing information confusion. - The interface returns
invalid file typeorfile size exceeds limiterrors after uploading medical aesthetic marketing materials. This happens when file upload support is not enabled in the configuration, or allowed file formats and size ranges are not specified.
How to confirm proper configuration
- Initiate a test conversation with a clear medical aesthetic project category and compliance request, verify that the model output is linked to the compliance requirements of the current project.
- Orchestrate a multi-model conversation flow, trigger test cases with different token consumption levels, verify that token counting for each model is independent.
- Upload a medical aesthetic marketing material of conventional size, verify that the interface normally returns a file association link.
- Configure a multi-turn dialogue context, initiate three consecutive requests with different requirements, verify that the model retains the precise prior requests.
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.