Multi-turn Dialogue and Prompt Engineering for Steel Trade Marketing Content

Steel trade category data primarily comes from enterprise inventory and sales systems, direct mill quotation sheets, downstream purchase ledgers, and

What the data for this category looks like

Steel trade category data primarily comes from enterprise inventory and sales systems, direct mill quotation sheets, downstream purchase ledgers, and logistics tracking documents. Data update cycles vary: spot quotations update daily, inventory ledgers sync in real time with inbound and outbound operations, and purchase contract data is entered upon transaction completion. Most documents use structured table formats, with fields including steel grade, nominal diameter, yield strength, delivery location, and settlement method. Common units are tons, yuan per ton, and delivery cycle (days).

What constraints these characteristics impose on multi-turn dialogue and prompt engineering

Steel trade data has scattered sources and significant differences in update cycles. Most documents use structured business fields with strict unit requirements, creating multiple constraints for multi-turn dialogue and prompt configuration. First, standard terminology for terms such as steel grade and nominal diameter must be clearly defined in prompts to avoid ambiguous dialogue. Second, spot quotations update in real time and inventory changes dynamically with transactions. Multi-turn dialogue must support real-time calls to backend business data; static knowledge bases cannot cover real-time changing business information. Additionally, field units must strictly match business logic. Prompts must embed unit verification logic to prevent errors caused by mismatched units for quantities and unit prices.

How to Set Configurations

Configuration ItemRecommended ValueRationale
maxContext8000–12000 charactersSteel trade business data includes contracts, quotations, and inventory information for multiple transactions. The configuration must cover context for at least 3 complete transactions to avoid losing key business fields
Recall countTop 3–5 entriesSteel trade has dense professional terminology. Too many retrieved entries will introduce redundant information and interfere with dialogue logic judgment
PARSE_FILE_TIMEOUT_SECONDS300 secondsSteel trade contracts and logistics documents are multi-page structured files, requiring longer parsing time than general scenarios
UPLOAD_FILE_MAX_SIZE500 MBBulk inventory ledgers, annual purchase contracts, and other files have large sizes, requiring support for large file uploads
Similarity threshold0.75–0.85Professional terms in steel trade have high similarity. The threshold must filter low-match redundant knowledge base content to ensure accurate retrieved information
maxHistoryTop 10–15 turnsSteel trade transaction processes involve multiple rounds of confirmation. Retaining too much history increases the burden of context processing

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 targeted analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Configuration Errors

  • Phenomenon: Calling the POST interface for deleting conversation records returns a 200 status code, but conversation records are not cleared. Cause: The conversationId field is not carried correctly, or the interface permission configuration does not enable delete operation permissions.
  • Phenomenon: After uploading a bulk steel trade inventory Excel file, parsing fails and a 413 status code is returned. Cause: The UPLOAD_FILE_MAX_SIZE configuration is not set to a value adapted for large files, causing the file to exceed platform limits.
  • Phenomenon: After enabling the guess you may ask function, no relevant recommended questions are returned after the conversation ends. Cause: The system prompt does not embed the logic for generating recommended questions, or the maxContext configuration is too small to extract core business keywords from the conversation.

How to Verify Configuration Correctness

  • Initiate a simulated conversation, input a query for steel grade and specifications, and verify that the returned context includes the latest quotation or inventory data to confirm the configuration meets business requirements.
  • Upload an Excel contract file with a volume matching the business scenario, check if the parsing result includes all structured fields to confirm the configuration adapts to file size and parsing duration.
  • Call the delete conversation record interface with the correct conversationId field, verify the interface return and the actual state of the conversation records to confirm the interface permission and field configuration are correct.
  • Enable the guess you may ask function, complete a complete business conversation, and check if relevant business recommended questions are generated to confirm the configuration meets conversation process requirements.

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.