What the data for this category looks like
Iron ore financing daily report data draws primarily from public data of domestic commodity spot trading platforms, Dalian Commodity Exchange, and industry associations. Teams update the reports once daily, usually within 2 hours after the same day’s market close. Each report includes fields such as release date, underlying variety, spot benchmark price, main futures contract settlement price, total port inventory, margin trading and short selling balance, warehouse receipt quantity, and day-over-day change. Price-related fields use yuan/ton as their unit. Financing balance and warehouse receipt quantity use ton or hundred million yuan as their units. Day-over-day changes only note the direction of change and numerical magnitude.
Constraints on multi-turn dialogue and prompt engineering
The daily update schedule for iron ore financing daily reports requires multi-turn dialogue to limit its context window scope, to prevent expired data from reducing response accuracy. The large number of fields with varying units requires prompts to clearly state each field’s definition and corresponding unit, to stop the model from confusing the statistical scopes of spot price, financing balance, and warehouse receipt quantity. Users frequently ask follow-up questions about day-over-day changes or cross-cycle comparisons, so multi-turn dialogue must retain the last 3 rounds of interactive context to link historical queries. It does not need to keep earlier conversation records, to avoid deviations from data timeliness. Teams must also clearly distinguish data from different sources (spot and futures) in prompts, to ensure the model matches the data source type specified in user queries when generating responses.
How to set configurations
| Configuration Item | Recommended Value Range/Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the token length of a single iron ore financing daily report, while retaining sufficient context to support associated queries in multi-turn dialogue |
historyMaxCount | 3 rounds | Adapts to the daily updated data characteristic, avoiding introducing expired historical data that interferes with current queries |
similarityThreshold | 0.75–0.85 | Filters low-relevance document fragments, ensuring that recalled content strongly matches the core indicators of iron ore financing |
recallTopK | Top 3 entries | The data volume of a single daily report is moderate, and a small number of recalls can cover the core indicators required by users |
promptTemplate | "Please accurately reply to user questions based on the provided iron ore financing daily report data, strictly use the fields and units in the document, and mark the corresponding date if day-over-day changes are involved" | Clarifies data usage rules and field units, preventing the model from confusing different statistical scopes and data sources |
responseMaxToken | 1500 token | Limits output length, ensuring responses focus on iron ore financing-related content and avoid redundant information |
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 case-by-case analysis, and testing on in-house samples is recommended before finalizing settings.
Three common mistakes to avoid
- Phenomenon: The model outputs external data not present in the iron ore financing daily reports, or uses field units that do not match the document. Cause: The prompt does not explicitly require only using recalled document content, and does not label the standard units for each field.
- Phenomenon: In multi-turn dialogue, the model fails to link the current query to the most recent iron ore financing data, and incorrectly calls earlier historical data. Cause: The
historyMaxCountparameter is set too large, retaining excessive expired historical conversation context that interferes with matching current data. - Phenomenon: The same iron ore financing query returns inconsistent results across different application scenarios. Cause: Parameters such as
similarityThresholdandrecallTopKare not unified, leading to differing recall rules across different environments.
How to confirm the configuration is set correctly
- Initiate a single-round targeted query, and verify that the returned result fields and units fully match the content of the iron ore financing daily reports in the knowledge base.
- Initiate two rounds of associated queries: first request iron ore financing data for a specified date, then request the day-over-day change of that data, and verify that the model correctly links the two rounds of interactive context.
- Review the parameter settings in the configuration panel, and confirm that the values of
maxContext,historyMaxCount, and other parameters adapt to the current data update rhythm and document length. - Initiate a query outside the scope of the current knowledge base, and verify that the model does not generate irrelevant content and only prompts that the corresponding information cannot be retrieved.
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.