What this category of data looks like
Duty-free investment research data mainly comes from three sources: General Administration of Customs off-island duty-free policy announcements, official inventory ledgers of off-island duty-free shops, and brand supplier duty-free price lists. Policy documents are stored structurally by document number, effective date, applicable region and quota restrictions. Inventory ledgers include SKU number, brand, specification, real-time inventory quantity and supply lead time. Price lists list tax-included price, duty-free retail price and supply batch. Policy data updates quarterly or annually. Inventory data updates daily. Price lists update monthly. Data fields include "Annual duty-free quota for off-island travelers" (unit: yuan), "SKU inventory balance" (unit: pieces), "Supply lead time" (unit: days). Field names vary slightly across different data sources.
What constraints do these characteristics impose on multi-turn dialogue and prompt engineering
The multi-source update rhythm of duty-free data requires recalling the latest data every time in multi-turn dialogue, and static caching cannot be relied on. Long policy texts contain clear effective time and applicable region restrictions. Multi-turn dialogue must associate historical query time ranges to avoid returning expired policies. SKU categories are rich with large field differences. Dialogue context must carry enough recalled entries, otherwise specific SKU information required by users will be missed. Units vary across different data sources. Prompts must specify unified field formats and units, otherwise model outputs will have unit confusion.
Configuration Settings
| Configuration Key | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Duty-free data includes long policy texts and multi-SKU lists. Sufficient context can carry historical queries and recall results for multi-turn dialogue |
recall count | Top 10–15 entries | Duty-free SKU categories are rich. A sufficient number of recalled entries is needed to cover users' specific query needs |
similarity threshold | 0.72–0.80 | Policy and SKU data have high similarity differentiation. This threshold filters irrelevant entries while retaining valid recall results |
re-ranked return count | Top 5–8 entries | Users need precise information in multi-turn dialogue. Limiting return entries avoids excessive redundant content interfering with model understanding |
custom prompt | Fixed extraction of "policy effective date", "SKU number" and "duty-free quota" fields, unified units as yuan/pieces/days | Duty-free data has many fields and inconsistent units. Clear prompts constrain output formats and avoid information confusion |
PARSE_FILE_TIMEOUT_SECONDS | 60–90 seconds | Parsing long policy documents takes time. This range avoids recall failures caused by timeouts |
Three Common Misconfigurations
- Phenomenon: API returned answers differ from those in the platform test interface, and some policy data is not recalled. Cause: The API request does not carry the
kbIdsparameter to bind the target duty-free knowledge base, or the default enabled knowledge base does not match the test environment. - Phenomenon: Unit confusion occurs in multi-turn dialogue, such as both "yuan" and "ten thousand yuan" being used to describe duty-free quotas. Cause: The unit unification rule is not specified in the custom prompt, and the model does not standardize fields from different data sources.
- Phenomenon: Empty results or timeout errors are returned in dialogue. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is set too short, long policy document parsing is terminated before completion, or too many recalled entries cause processing timeout.
How to Confirm Proper Configuration
- Enter the application configuration interface, check if the custom prompt contains clear requirements for extracting duty-free data fields and unifying units.
- Initiate the same query in both the platform test interface and API request, compare whether the returned policy and SKU information are consistent.
- Initiate consecutive multi-turn queries, confirm that the model can carry historical context without requiring repeated initial query conditions.
- Check the application runtime logs, confirm that the time taken for file parsing requests does not exceed the configured timeout threshold, and there are no abnormal errors.
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. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
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.