What the data for this category looks like
Textile manufacturing yield and market data covers three core modules: raw material end, processing link, and finished product end. Data sources include spot quotes of textile raw materials from public commodity trading platforms, monthly monitoring reports from industry associations, and internal production accounting ledgers of enterprises. Update frequencies vary: raw material spot quotes are updated daily, unit loss parameters for the processing link are updated weekly, and ex-factory quotes for finished products and daily yield calculation data are updated every working day. A single daily report document includes fields such as raw material purchase unit price, unit processing cost, finished product ex-factory unit price, and unit product gross profit. Field units include category-specific units such as yuan/ton, yuan/meter, and yuan/item, with no unified standardized format.
Constraints imposed on multi-turn dialogue and prompt engineering
Since data is split across multiple links with inconsistent units, multi-turn dialogue must guide users to clarify the link and corresponding unit of their inquiry. Prompts must preset unit conversion rules to avoid confusing numerical values across different categories. Since different data sources have varying update frequencies, prompts must specify the time range of data to avoid returning outdated historical data. Since some data comes from internal enterprise ledgers, recall weights for public data sources and internal documents must be differentiated in recall configuration to ensure core business data is recalled first. Since individual daily report documents have long paragraphs, adjust segment lengths to avoid disrupting the coherence of accounting logic and affecting information association during multi-turn dialogue.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 4000–6000 characters | Adapts to the long context splicing requirements of multi-link data in textile manufacturing, avoiding truncation of critical raw material and finished product association data |
recall count | Top 8–10 entries | Covers data sources across the raw material, processing, and finished product links, avoiding missing core information from single-link recall |
similarity threshold | 0.72–0.78 | Distinguishes market quotation data of similar textile raw material categories, avoiding confusing quotation information between polyester and nylon |
segment length | 1200–1500 characters | Adapts to the long paragraph structure of daily report documents in the textile industry, avoiding splitting that disrupts the logical association of cost accounting |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Processes batch historical production ledgers and monthly monitoring documents, avoiding timeout during large file parsing |
rerank return count | Top 5 entries | Focuses on the most relevant link data, reducing unnecessary information interference during multi-turn dialogue |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Symptom: A
connection erroroccurs when calling the Qianwen model, and the issue persists after enabling a proxy. Cause: ThePROXY_URLparameter is not configured, or the proxy address does not adapt to the network rules for domestic model calls. - Symptom: Images returned by the knowledge base cannot be displayed in the dialogue, and the prompt does not take effect. Cause: The prompt does not explicitly specify the format and calling method for returning images, or the image parsing switch for the knowledge base is not enabled.
- Symptom: Keyword variables such as raw material category and procurement cycle cannot be accurately extracted during multi-turn dialogue. Cause: The prompt does not define variable extraction rules for exclusive fields of textile manufacturing, and does not limit the scope of extracted fields.
How to verify proper configuration
- Initiate a test dialogue, inquire about the daily market quotation of a specific textile raw material, and verify whether the source and update time of the returned data match the configured data sources.
- Upload a historical production ledger document, check whether parsing is completed within the time set by
PARSE_FILE_TIMEOUT_SECONDS, with no truncation or errors. - Adjust the
similarity threshold, test recall results under different thresholds, and confirm that similar textile raw material market quotation data can be distinguished. - Initiate multi-step progressive questions, such as first asking about the purchase price of polyester raw materials, then asking about the loss parameters of the weaving link, then asking about the ex-factory unit price of finished products, and check whether the context is correctly retained with no information loss.
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.