What Data for This Category Looks Like
Iron ore-related due diligence data sources include public commodity trading data, public customs clearance data, and public industry monitoring datasets. Update rhythms vary across data types:
- Spot price data updates daily
- Port inventory and arrival forecast data updates each workday
- Origin shipment statistics data updates weekly
Each data entry includes fields such as transaction date, origin, transaction price, total port inventory, arrival forecast volume, grade parameters, and delivery grade. Price units are based on per ton, and grade is expressed as a purity numerical value. There is no unified fixed format template.
What Constraints Do These Characteristics Impose on the "Model Access and Configuration" Link
Dispersed data sources and inconsistent formats require configuring unified field mapping rules to integrate multi-source data. Different data sources have varying update frequencies, requiring configured batch scheduled synchronization tasks to match data timeliness. Professional fields such as grade and delivery grade have industry-specific definitions, requiring configured custom system prompts to ensure the model accurately identifies them. Data file volumes vary due to multi-source integration, requiring adjustment of file processing timeout parameters. Due diligence reports must strictly limit use to only iron ore-related data, requiring configured recall rules to filter irrelevant content.
How to Set the Configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
ragRecallTopK | Top 6-8 entries | Iron ore due diligence requires integrating multi-source data. Excessive recall will introduce irrelevant information, while insufficient recall will fail to cover core due diligence dimensions |
vectorModel | Calibrate based on actual testing (adapt to industry-specific text embedding models) | Iron ore data contains specialized terminology and exclusive fields. An embedding model supporting industry text must be matched to ensure retrieval accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Multi-source integrated iron ore data files have large volumes. The default timeout duration is insufficient to complete full processing |
systemPrompt | Fixed prompt to limit responses to only recall data related to iron ore due diligence | Avoid interference from irrelevant data sources on the professionalism and accuracy of due diligence reports |
syncSchedule | Batch configuration: spot data synchronized hourly, port data synchronized each workday, weekly data synchronized weekly | Match the update rhythms of different data sources to ensure due diligence reports use the latest valid data |
maxContext | 8000-12000 characters | Iron ore due diligence reports require integrating multiple long text segments. Model parameters supporting long context must be adapted |
The parameter values provided on this page are all conventional recommendations used to determine starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: Returned results include more than the specified number of irrelevant iron ore data. Cause: The
ragRecallTopKparameter was not configured correctly, causing the number of recalled entries to exceed the expected range. - Phenomenon: Knowledge base file processing fails, with error code
408. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient to process large multi-source iron ore data files. - Phenomenon: Vector retrieval results include both dry ton and wet ton price data. Cause: Custom field mapping rules were not configured, and price data with different units was not unified for conversion.
How to Confirm Configuration Is Complete
- Test a single iron ore data recall request, and verify that the number of returned recalled entries matches the configured
ragRecallTopKvalue. - Upload a large multi-source iron ore data file, and verify that processing duration does not exceed the configured
PARSE_FILE_TIMEOUT_SECONDS. - View knowledge base file processing logs to confirm that field mapping and unit conversion rules have taken effect.
- Call the model to generate an iron ore due diligence report, and verify that the output content does not include non-iron ore related data source information.
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.