What the Data for This Category Looks Like
Personal care product data sources primarily include official brand-compliant filing documents, e-commerce platform authorized product detail pages, product qualification information published by regulatory authorities, and user practical test feedback. The update schedule follows these rules: bulk SKU information updates when new products launch, compliant qualification information syncs irregularly per regulatory requirements, and user feedback is updated daily. Document structure uses one structured entry per SKU, including fields such as product name, SKU code, core ingredient list, applicable skin type, usage instructions, filing number, and more. Net content uses milliliters or grams as units. Launch dates use the YYYY-MM-DD format.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Structured SKU and attribute fields require multi-turn dialogue to first collect prequalifying information such as the user’s skin type and usage scenario, before accurately locating content for the corresponding SKU and avoiding generic responses. The presence of compliant filing fields requires prompt engineering to embed compliance check rules, prohibiting efficacy claims beyond the filing scope. Real-time updated user feedback data requires dialogue context to include the past 7 days of user test content, while controlling context length to avoid overflow. Unified physical unit fields require prompt engineering to enforce consistent unit terminology, preventing confusing responses.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Needs to accommodate structured documents for a single SKU, user feedback from the past 7 days, and multi-turn dialogue history, to avoid context overflow |
recallTopK | Top 6 entries | Personal care products have a large number of SKUs. Precise recall of core information for the target SKU is required to avoid redundant content interfering with responses |
promptTemplate | Fixed embedding of compliance check rules + SKU positioning logic | Must enforce that response content complies with filing requirements, while quickly locating the specific SKU the user is inquiring about |
apiResponseFilter | Only return product content related to the user’s question | Prevents AI dialogue content from intermediate workflow steps from being included in the final output |
contextWindowCleanupStrategy | Retain core attribute information by conversation turn | Filter non-critical preliminary redundant information during multi-turn dialogue, retain core parameters such as user skin type and usage scenario |
The parameter values provided on this page are common recommended starting points for configuration setup. 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 values.
Three Common Configuration Mistakes
- Phenomenon: After the workflow completes execution, inserted AI dialogue content is included in the final output. Cause: The
apiResponseFilterparameter is not configured, and non-target output from intermediate workflow steps is not filtered. - Phenomenon: When calling the API, title content is visible in conversation logs, but this content is not present in external link calls. Cause: The API request does not carry the
excludeMetadataparameter, resulting in metadata fields being returned in the response. - Phenomenon: Responses that fail to accurately match the user’s skin type adaptation requirements appear frequently during multi-turn dialogue. Cause: The
recallTopKparameter is not configured, resulting in too many or too few recalled SKU information, failing to accurately locate the specific product the user is inquiring about.
How to Confirm Proper Configuration
- A multi-turn test dialogue including SKU, skin type, and efficacy demands can be initiated, and the response can be verified to only include compliant content for the corresponding SKU.
- Workflow execution logs can be reviewed to confirm that intermediate AI dialogue content is not included in the final output.
- The API interface can be called, and the response content can be verified to only include product information related to the user’s question, with no redundant metadata.
- Context switching during multi-turn dialogue can be simulated, and the system can be verified to retain key attribute information and accurately match subsequent inquiries.
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.