What the data for this category looks like
Iron ore-related financial reports and industry data primarily come from global mining enterprise quarterly financial reports, domestic futures exchange monthly spot reports, and industry association supply and demand analysis documents. Update frequencies follow three cycles: quarterly for enterprise financial reports, monthly for industry supply and demand reports, and weekly for spot price data. Document formats are mostly encrypted PDF financial reports and Excel attachments with detailed breakdowns. Core fields include iron ore production, port inventory, import volume, and benchmark average price. Common units are ten thousand tons, yuan per wet ton, or US dollars per dry ton. Some documents include related data such as sea freight and steel mill purchase volumes.
Constraints imposed on deployment and upgrade
The multiple sources, formats, and update frequencies of iron ore-related data create multiple constraints for deployment and upgrade. Pre-configure mixed parsing plugins for PDF and Excel to meet extraction requirements for encrypted financial reports and detailed attachments. Data sources with different update frequencies require differentiated scheduled synchronization rules. Trigger full imports for quarterly financial reports per fiscal quarter. Set up incremental synchronization tasks for weekly spot price data. During upgrades, synchronously update parsing rules to adapt to format changes in new financial reports, and add unit conversion logic to unify price and production units across different sources.
How to set configurations
| Config Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Iron ore financial reports often include multiple detailed Excel attachments. Parsing the full set takes significant time. Extend the timeout to prevent parsing interruptions. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Large mining enterprise quarterly financial reports contain multiple industry report attachments. Total file size may exceed default platform limits. |
maxContext | 8000–12000 characters | Individual financial report text can exceed ten thousand words. Retain sufficient context to support complete logical analysis of the report. |
Recall count | Top 8 entries | Core data in iron ore financial reports is scattered across multiple sections. Retrieve enough related fragments to support integrated analysis. |
Similarity threshold | 0.75–0.85 | Filter generic industry statements and accurately match core iron ore-specific fields such as production, price, and inventory. |
PARSE_EXCEL_ENABLE | Enabled | Most iron ore financial reports include structured Excel detailed data. Enable Excel parsing to extract structured fields. |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, 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: A
404 no bodyerror is returned when calling the model for testing after local deployment. Cause: The model interface request key or access address is not configured correctly. The platform cannot establish a normal connection with the model service. - Phenomenon: The [Text Processing] module does not appear in the backend after deployment is complete. Cause: The corresponding function plugin is not installed, or the plugin version is incompatible with the current FastGPT version. Manually install a plugin version that matches the FastGPT version.
- Phenomenon: Valid data cannot be extracted after importing an iron ore financial report image with charts. Cause: The preprocessing flow for image-to-base64 conversion is not configured. The visual model cannot recognize and analyze the image content.
How to confirm the configuration is correct
- Upload a standard iron ore financial report document. Check if the parsing result extracts core business fields to confirm that the file parsing configuration is effective.
- Manually trigger a preset synchronization task. Check if the data source completes data import as expected to confirm that the scheduled synchronization rule configuration is correct.
- Enter targeted financial report analysis query instructions. Check if the model return results match the iron ore-specific business logic to confirm that the retrieval and model configuration are effective.
- View system operation logs. Confirm that there are no errors such as file parsing timeouts or interface call exceptions to confirm that the overall deployment configuration is stable.
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.