What the data for this category looks like
Data sources for textile manufacturing investment research include raw material quotes from commodity exchanges, factory production ledgers, industry association capacity reports, fabric parameter reports from third-party testing institutions, and downstream brand order data. Update frequencies vary: raw material quotes are updated daily, production schedules weekly, industry research reports monthly or quarterly, and fabric test reports updated with each production batch. Document structures include structured CSV/Excel tables, PDF research reports, and image-format fabric swatch cards. Field units include yuan/ton, yuan/meter, count, threads/cm, kilograms, and others. Field formats differ across data sources.
How these characteristics affect multi-turn dialogue and prompting
Multi-source heterogeneous data types require multi-turn dialogue to support parsing adaptation across document types. Examples include extracting field associations from structured tables and extracting professional parameters from image swatch cards. Different update frequencies require the dialogue system to distinguish data timeliness. When querying raw material prices, daily updated data should be prioritized for recall. Diverse field units require prompts to preset unified conversion logic to avoid unit confusion in conversations. Dispersed data sources require multi-turn dialogue to gradually narrow the query scope and clarify the user’s specific needs. For example, narrowing from general fabric categories to products with specific yarn counts. Some data includes image-format fabric swatch cards. Prompts need additional configuration of OCR parsing professional parameters adapted to textile terminology.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Textile manufacturing investment research conversations need to associate multiple pieces of data such as raw material quotes and production ledgers. This length covers common multi-turn context requirements |
recallTopK | Top 8 entries | Textile manufacturing data has many fields. Excessive recall will cause context overload. This value balances information completeness and context length |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large industry research report PDFs or batch fabric swatch cards requires long processing time. This duration covers the parsing needs of most files |
similarityThreshold | 0.75–0.85 | There are many professional terms in textile manufacturing. This threshold filters irrelevant data while retaining information about relevant segmented product categories |
enableMultiTurnRefine | Enabled | Investment research conversations need to gradually clarify the user’s specific product category needs. Multi-turn refinement narrows the query scope and improves response accuracy |
UPLOAD_FILE_MAX_SIZE | 500 MB | Batch production ledgers or large research report files for textile manufacturing usually do not exceed this size, covering most upload scenarios |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Mistakes
- Phenomenon: Calling the dialogue interface returns the
unAuthChaterror code, and the apikey configuration is correct. Cause: The access permission for the corresponding knowledge base is not bound in the system settings, or the allowed request sources are not configured for the apikey. - Phenomenon: The dialogue return result contains line breaks, causing subsequent JSON request parsing failures. Cause: The prompt does not require the return content to use escape characters to handle line breaks, or the structured output switch for dialogue results is not enabled.
- Phenomenon: An error is triggered when uploading textile manufacturing-related files, but the text input dialogue function works normally. Cause: The parsing adaptation rules for the corresponding file types are not configured, or the connection timeout setting of the file parsing service is too short.
How to Verify Successful Configuration
- Initiate a multi-turn dialogue about textile raw material prices, verify that historical context is correctly associated, and confirm that the
maxContextconfiguration meets current needs. - Upload a textile industry research report, check if the parsed fields include correct professional parameters, and verify that the
recallTopKandsimilarityThresholdconfigurations adapt to data characteristics. - Call the dialogue interface, check if the return result includes escaped line breaks, and confirm the compatibility of JSON format requests.
- Upload multiple different types of textile manufacturing files, verify that the upload function works normally, and confirm that the file parsing service configuration is correct.
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.