What Data for This Category Looks Like
Cosmetics investment research data primarily comes from official brand filing materials, third-party ingredient test reports, e-commerce platform user reviews, and ingredient research white papers released by industry associations. Update frequency fluctuates with new brand product launches and compliance filing updates, and is also synchronized with new ingredient research findings on an ongoing basis. Document structures typically include fields such as basic product information, ingredient lists (with specific content annotations), applicable skin type classifications, usage instructions, and compliance warning clauses. Ingredient content units are mostly mg/g or percentage. Filing numbers and production batch numbers are required identification fields. Individual document lengths usually range from several thousand characters.
What Constraints These Characteristics Impose on Multiturn Dialogue and Prompt Engineering
Cosmetics data contains many precise fields, such as ingredient concentration and filing numbers. Multiturn dialogue must track the specific product or ingredient the user is currently focused on, to avoid mixing parameters from different products. Frequently updated data sources require prompt templates to regularly trigger incremental synchronization checks for the knowledge base, to ensure retrieved content uses the latest versions. The presence of compliance warning fields requires multiturn dialogue to actively guide users to confirm compliance-related questions, to avoid generating content that does not meet regulatory requirements. Long paragraph structures in documents require dialogue context retention lengths to adapt to complete product information extraction, to prevent truncation of critical content.
How to Set the Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Cosmetics filing documents and ingredient research reports have lengthy text, requiring sufficient context retention to track multiturn questions about ingredient concentration, skin type suitability, and similar topics |
recallTopK | Top 6–8 results | Documents related to a single cosmetics product include multiple categories of data such as ingredients, filings, and reviews. A sufficient number of retrieved entries is needed to cover complete investment research information |
similarityThreshold | 0.75–0.85 | There are many precise fields such as ingredient names and filing numbers. This range balances retrieval precision and coverage |
dialogueHistoryMaxTurns | Previous 4–6 turns | Investment research conversations mostly revolve around specific products or ingredients. Excessive historical dialogue can interfere with precise matching of current questions |
fileParseChunkSize | 800–1000 characters | Cosmetics filing documents have clear paragraph structures. Chunk lengths adapt to complete extraction of modules such as ingredient lists and usage instructions |
UPLOAD_FILE_MAX_SIZE | 10–15 MB | Cosmetics filing documents are mostly multi-page PDFs. Individual file sizes typically fall between 5–12 MB. A reasonable upload limit should be reserved |
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 Configuration Errors
- A 413 status code is returned when calling the API to upload cosmetics filing documents, and the dialogue does not respond. The cause is that the
UPLOAD_FILE_MAX_SIZEparameter is not set correctly, and the uploaded document size exceeds the configured threshold. - Investment research results from AI dialogue nodes continue to appear in the user’s conversation chain. The cause is that the node’s "auto-append to conversation history" configuration is enabled, causing non-interactive investment research results to be mixed into the dialogue context.
- Custom JSON format replies fail to generate compliant standard structures. The cause is that the prompt template does not clearly specify the required rules for JSON fields, and the large model output does not follow the preset format.
How to Confirm Successful Configuration
- Upload a single cosmetics filing document, call the dialogue interface to initiate a query, and check if the returned content includes precise fields such as ingredient concentration and filing number from the document.
- Initiate consecutive multiturn queries, such as first asking about the core ingredients of a specific product, then following up on the compliance of that ingredient. Check if the dialogue context is correctly retained, and no information mixing occurs.
- After configuring a custom JSON reply format, initiate a corresponding query, and check if the returned result includes preset fields such as
product_name,ingredient, andcompliance_note. - Upload multiple similar cosmetics documents, and check if the retrieval results cover dimension information for different products, with no redundant irrelevant content.
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.