What the Data for This Category Looks Like
Iron ore data primarily comes from Dalian Commodity Exchange futures market quotes, coastal port spot transaction ledgers, and domestic mainstream steel mill procurement daily reports. Update cadence falls into three categories: futures market quotes are pushed in real time, port spot prices are updated daily, and steel mill procurement data is updated weekly. The document structure includes fields such as grade (measured in percentage), origin, transaction price, total inventory, single-day trading volume, etc. Some documents will include additional information such as loading and unloading efficiency and transportation cycle.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
The real-time and batch-update data characteristics require that multi-turn dialogue processes distinguish between calling data sources with different time sensitivities, to avoid returning expired price or inventory information. The fine-grained structure of multiple fields requires that prompts clearly specify the specific fields and units to be returned, preventing issues such as grade values not labeled with percentages or mixed price units. For the accuracy requirements of marketing content, multi-turn dialogue must first verify the update timeliness of the data requested by the user, then match the corresponding data source interface, to ensure that the output content meets the timeliness requirements of the marketing scenario. At the same time, multi-turn dialogue must retain the iron ore parameters specified in earlier interactions, to avoid parameter deviations in subsequent responses that affect the consistency of marketing content.
Configuration Settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Iron ore data has many fields. Multi-turn dialogue needs to retain previously queried parameters such as grade and origin to avoid context overflow |
RETRIEVE_TOP_K | Top 8–10 entries | Iron ore data includes multi-dimensional information. Too many retrieved entries will cause context redundancy, while too few will fail to cover required fields such as price and inventory |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Some iron ore monthly ledger documents have long lengths, so sufficient parsing time must be reserved |
PROMPT_TEMPLATE | Fixedly specify that returned fields include grade, origin, current day's price, total inventory, with unified units of percentage, origin name, yuan/wet ton, ton | Prevent the model from generating irrelevant information, and meet the conciseness and accuracy requirements of marketing content |
CONNECTION_RETRY_TIMES | 2–3 times | Some data source interfaces may have temporary fluctuations, and retries can reduce the probability of connection errors |
MAX_OUTPUT_TOKENS | 1500 characters | Marketing content needs to control its length to avoid exceeding user reading expectations |
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 Mistakes
- Symptom: A
connection errorprompt appears after submitting a dialogue, and the issue persists after enabling a proxy. Cause: The whitelist for the iron ore data source interface has not been configured, or the request header does not adapt to the dedicated authentication requirements of the data source. - Symptom: Irrelevant transportation cycle fields appear in dialogue outputs, or price units mix USD/dry ton and yuan/wet ton. Cause: The prompt fails to clearly specify fixed return fields and units, causing the model to generate redundant or incorrect information.
- Symptom: After multiple consecutive dialogue turns, subsequent responses lose the previously specified iron ore grade parameter. Cause: The
maxContextvalue is too small, and insufficient context history is retained, causing the model to forget earlier parameters.
How to Verify Proper Configuration
- Initiate an iron ore data query that includes specified grade and origin, and check whether the returned content includes the preset fields and unified units.
- Initiate consecutive multi-turn parameter queries, and check whether subsequent responses retain the previously specified iron ore attributes without context loss.
- Simulate temporary fluctuations in the data source interface, and check whether the system triggers the retry mechanism without directly returning a connection error.
- Upload a long iron ore ledger document, and check that the parsing process does not trigger a timeout error.
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.