What the Data for This Category Looks Like
Carbon steel-related data primarily comes from steel mill ERP systems, bulk commodity spot trading platforms, official factory price announcement channels, and downstream manufacturing demand survey data. Factory guidance prices are updated daily, spot trading prices refresh hourly, and inventory and production capacity data are updated weekly. A single data document typically includes fields such as steel category, specification parameters, production origin, supplying steel mill, quoted price (yuan/ton), available inventory (tons), delivery cycle (days), etc. Most field formats are structured tables or standardized CSV files.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The carbon steel category has numerous subcategories and complex specification parameters. Multi-turn dialogue must continuously track the specific steel category and specifications mentioned by users to avoid cross-category confusion. Data update frequencies vary widely; prompt configuration must adapt to synchronization rules for real-time or near-real-time data sources to prevent returning outdated quotes. Structured fields include clear pricing and measurement units; multi-turn interactions must unify unit expressions to avoid confusion between yuan/ton and other pricing units. Downstream users often associate information such as purchase volume and delivery scenarios; the multi-turn process must gradually collect supplementary parameters to support the generation of precise marketing content.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single carbon steel data documents are relatively long, and multi-turn dialogue needs to retain context related to multi-turn categories, specifications, and quotes |
systemPrompt | Match the latest quotes and inventory of the corresponding data source based on information such as the steel category, specifications, and purchase volume mentioned by the user, and output structured marketing content | Carbon steel marketing requires precise matching of specific parameters to avoid generic, vague responses |
recallTopK | Top 6–8 entries | Carbon steel data sources include multi-dimensional parameters; an appropriate number of recalls can cover core information such as categories, specifications, and quotes |
contextRefreshInterval | Every 12 hours | Factory guidance prices are updated daily, and near-real-time spot data requires regular synchronization to avoid returning outdated content |
workflowAiNodeMaxTurns | 3–5 turns | Carbon steel marketing needs to gradually collect supplementary information such as procurement demand and delivery location; excessive turns will reduce interaction efficiency |
The parameter values provided on this page are conventional recommendations used as a starting point 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 the settings.
Three Common Mistakes
- Phenomenon: Multiple
<ai dialogue>nodes are configured in the workflow. When invoking the workflow dialogue, the replies of all nodes are displayed simultaneously in the chat window. Cause: No context transfer rules are configured in the workflow, and each AI node is not associated with a shared dialogue context, resulting in independent output results. - Phenomenon: Carbon steel marketing dialogue initiated in an unlogged state loses historical records after page refresh. Cause: Session persistence configuration is not enabled, or anonymous session storage rules are not configured, making it impossible to retain dialogue data for unauthorized users.
- Phenomenon: When building a carbon steel marketing workflow, the process ends after only one single question, and it is impossible to initiate follow-up questions based on user replies to collect supplementary information such as purchase volume and delivery location. Cause: No loop trigger or multi-turn follow-up questioning node is configured in the workflow, and only a single AI call process is executed.
How to Verify That the Configuration Is Complete
- Initiate a multi-turn dialogue involving different steel categories and specifications, check whether the context is correctly retained, and ensure no context loss or cross-category confusion occurs.
- Call the configured carbon steel marketing workflow to initiate a question, verify that only the reply from the AI node corresponding to the current interaction is displayed, with no redundant historical node output.
- Adjust the simulated update time of the data source, check whether the quotes returned by the dialogue are updated synchronously with the configured refresh interval.
- Test the dialogue isolation between anonymous users and authorized users, verify that different users cannot view each other's historical dialogue records.
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.