What the Data for This Category Looks Like
Data for industrial metals intelligent due diligence reports comes from three main sources: global major futures exchanges, domestic industry associations, and public financial reports from mining and smelting enterprises.
Update frequencies cover real-time, daily, and weekly tiers. Spot price data updates daily. Futures contract prices are pushed in real time. Industry inventory and import/export data updates weekly or monthly.
Document structures are combinations of multi-page tables. Common fields include product name, specification grade, origin, transaction price, weekly average price, end-of-period inventory, and upstream and downstream demand proportion. Units are mostly yuan/ton, ton, and ten thousand tons. Some sub-categories require labeling delivery grades and smelting process parameters.
Constraints Imposed on Deployment and Upgrade Workflows
The data characteristics of industrial metals due diligence reports create multiple constraints for deployment and upgrade workflows.
Multi-source heterogeneous data access requires configuring multi-data source synchronization links during deployment. It also requires separating scheduling logic for different update frequencies, such as real-time spot prices and weekly industry inventory data.
Large document volumes and complex fields require adjusting the parsing engine’s sharding rules and timeout thresholds during upgrades. This prevents parsing failures for single reports.
Differences in units and field naming across data sources require presetting standardized mapping rules during deployment. It also requires supporting format changes for new data sources during upgrades.
Parameter differences across sub-categories require reserving configurable category adaptation fields during deployment. This avoids conflicts across cross-category deployments.
Configuration Settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Single industrial metals due diligence report contains multi-page, multi-dimensional data tables. Standard timeout durations are insufficient to complete full parsing |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Industrial metals due diligence reports often include multi-year industry statistical data, resulting in large individual file sizes |
Recall count | Top 20 entries | Industrial metals data has many fields and high correlation. Sufficient related data on upstream/downstream, prices, and inventory must be recalled |
Similarity threshold | 0.75–0.85 | There are many sub-categories of industrial metals. Low-match irrelevant industry data must be filtered to improve query accuracy |
SCHEDULED_REFRESH_INTERVAL | 3600 seconds | Covers the main update cycles of daily spot price updates and weekly inventory data updates, balancing synchronization delay and resource usage |
WEBHOOK_MAX_BATCH_SIZE | 50 entries | Adapts to the bulk table push requirements of industrial metals due diligence reports, avoiding timeouts caused by overly large single batch data volumes |
The parameter values provided on this page are common 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 Configuration Errors
- After deploying with Docker Compose, the
ONEAPI_BASE_URLenvironment variable is not found in the configuration file, and model channel access fails after startup. Cause: Some older version deployment templates do not include the oneapi configuration segment by default. Manually add the corresponding parameters to the environment variable configuration. - When configuring Webhooks for multi-table formats, only single data entries are pushed after triggering, and due diligence report data cannot be synchronized in batches. Cause: The
WEBHOOK_BATCH_ENABLEparameter is not enabled, and a reasonable single-batch data volume threshold is not set. - A
400 Bad Requesterror is returned in the interface when configuring a model channel after local deployment, prompting that the model interface response format is abnormal. Cause: The large model context length required for industrial metals due diligence reports is not matched, or the model’s API key permissions are not correctly configured.
How to Confirm Configuration is Complete
- Upload a standard industrial metals due diligence report file, wait for parsing to complete, and check if the parsed fields include preset fields such as origin, specification grade, and transaction price.
- Manually trigger a scheduled refresh task, check the system operation logs, and confirm that multi-source data (futures, spot, industry data) have all completed synchronization without errors.
- Initiate a test query, enter a query instruction for the price and inventory of the corresponding category, and check if the returned results include relevant upstream and downstream data and correct unit labels.
- Check the Docker container’s environment variable loading logs, and confirm that all configured parameters have been read normally, with no missing or formatting errors.
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.