What the data for this category looks like
Data sources include brand manuals, product SKU parameters, official marketing copy provided by beauty and personal care brands, e-commerce platform sales data, social media user interaction data, industry regulatory announcement information, and financial investment research market data for brands. Sync in real time when new products launch or marketing campaigns change. Routine content is updated once weekly. Document structure includes structured SKU tables (with fields such as item number, specification, selling price), unstructured marketing materials, and semi-structured activity rule documents. Field units include item number, gram weight, selling price (yuan), advertising budget (ten thousand yuan), interaction count (times), and others.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Structured SKU tables and financial investment research-related budget fields are dense, and require precise matching. Multi-turn dialogue must explicitly prompt the model to prioritize identifying key fields such as item number and advertising budget. High-update-frequency marketing and investment research content requires the multi-turn dialogue link to default to prompting users to confirm the latest version of information. This avoids using expired materials. Unstructured marketing materials and semi-structured activity rule documents have wide semantic spans. Prompt engineering must limit the recall range to avoid irrelevant content interfering with dialogue logic. Units across multiple document types are inconsistent. Prompt engineering must forcibly bind the unit system provided by the brand to prevent unit confusion.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 12000–15000 characters | Multi-turn dialogue for brand agency operations needs to associate multiple SKU queries and activity rules. This range covers historical information for conventional multi-turn interactions, and prevents the model from losing context |
recallTopK | Top 8–10 results | Multiple relevant SKU parameters and marketing materials must be recalled simultaneously. This number covers information requirements for core business scenarios |
similarityThreshold | 0.75–0.85 | Structured SKU field matching requires a high similarity threshold. This avoids recalling irrelevant competitor data or unstructured materials that interfere with precise matching |
chunkSize | 800–1200 characters | Marketing copy and activity rules need to maintain semantic integrity. This segment length covers the semantic units of conventional marketing materials |
workflowFormDisplay | Enabled | Brand agency operation investment research requires collecting information such as SKU item number and activity type. When enabled, form interaction fields are rendered in the dialogue interface |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Brand documents contain a large number of high-definition materials and structured tables. This duration covers conventional upload and parsing time |
The parameter values provided on this page are all conventional recommendations, used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: Form inputs configured in the workflow do not display interactively in the dialogue. Cause: The
workflowFormDisplayconfiguration item is not enabled, resulting in form fields not being rendered in the dialogue interface. - Phenomenon: After uploading a brand SKU table via API, item number fields cannot be matched accurately in the dialogue. Cause: The
similarityThresholdis set too low, which recalls a large number of irrelevant unstructured marketing materials and interferes with structured field matching. - Phenomenon: Unit confusion frequently occurs in multi-turn dialogue, for example, identifying "selling price (yuan)" as "selling price (USD)". Cause: The prompt does not explicitly specify the unit rules in the document, and does not restrict the model to use the unified unit system provided by the brand.
How to confirm the configuration is complete
- Upload a brand's SKU table and marketing material documents, perform an API upload operation, and check whether the upload progress is completed within the duration configured by
PARSE_FILE_TIMEOUT_SECONDS. - Initiate a multi-turn dialogue, sequentially ask about the selling price and activity rules of different SKUs, and check whether preset form input fields are displayed in the dialogue interface.
- Adjust the value of
similarityThreshold, test recall results under different thresholds, and confirm that the accuracy of matching SKU item numbers meets business requirements. - Copy a long marketing copy, test the semantic integrity after segmentation, and confirm that the
chunkSizeconfiguration range covers the semantic units of the document.
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.