What the data for this category looks like
Apparel and home textile investment research data comes from four main sources: industry association monthly supply and demand reports, listed brand quarterly financial reports, e-commerce platform weekly sales reports, and upstream fabric supplier quotation sheets. Update frequencies vary by source. Industry reports update monthly. Financial reports release quarterly. E-commerce sales data syncs daily. Most documents combine structured tables and paragraphs. They include fields such as SKU count, tag price, fabric cost proportion, and inventory turnover days. Units include yuan, pieces, square meters, and sales per square meter (yuan/square meter).
Constraints on Multi-turn Dialogue and Prompt Engineering
The varying update frequencies of multi-source heterogeneous data require clear separation of usage boundaries between historical financial report data and real-time e-commerce data during multi-turn dialogue. Prompts must define clear time range parameters. The large number of structured fields and diverse units mean prompts must specify exact formats and unit rules for field extraction. This prevents mismatches between numerical values and their units. The high volume of SKUs requires limiting the number of entries in context recall for multi-turn dialogue. This stops redundant information from interfering with core reasoning. Multi-round follow-up questions in investment research often involve month-on-month and year-on-year calculations. Prompts must include pre-designed guiding rules for these calculations.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | Previous 6–8 turns of dialogue history | Apparel and home textile investment research data is mostly structured tables. Excessive history consumes context quota. 6–8 turns cover complete follow-up question logic |
recallTopK | Top 3–5 knowledge base entries | This category has many SKUs and sub-categories. Excessive recall causes information overload. 3–5 entries accurately match investment research questions |
similarityThreshold | 0.75–0.85 | Structured field matching requires high precision. This range filters low-relevant industry reports and financial report data |
systemPrompt | Guiding statements to extract values per specified fields, label units, and distinguish financial report accounting cycles from e-commerce natural cycles | Adapts to the category’s multiple structured fields and multi-source data characteristics, avoiding extraction errors |
fileParseChunkSize | 800–1200 characters | Most category documents combine long tables and paragraphs. This chunk length retains complete structured field groups |
apiTimeout | 30–60 seconds | Investment research data requires aggregation across multiple sources. A longer timeout ensures complete data recall |
The parameter values provided on this page are conventional recommendations used to set starting points 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 Mistakes
- Prompts fail to extract current year or current month investment research data. The symptom is empty fields in returned results. The cause is missing clear time range matching rules in the prompt, and failure to distinguish between financial report accounting cycles and e-commerce natural cycles.
- Setting
maxContextto 0 in the workflow still leaves residual context. The symptom is dialogue history is passed to the API. The cause is failure to turn off the workflow’s context transfer switch, or default context caching logic in version v4.8.10. - Multi-turn dialogue produces result deviations. The symptom is returned fabric cost proportion values do not match their units. The cause is missing clear unit rules for fields in the prompt, and failure to perform mandatory verification on structured data fields.
How to Confirm Proper Configuration
- Submit test questions that include time ranges and field requirements. Check if returned results include specified units and numerical ranges.
- Initiate two or more follow-up questions. Check if dialogue history is truncated or retained per the
maxContextsetting. - View workflow logs. Confirm the number of context entries passed to the API matches the
maxContextsetting. - Upload financial report and e-commerce documents for this category. Check if parsed chunks retain complete structured field groups.
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.