What the data for this category looks like
Special steel intelligent due diligence reports serve due diligence needs in the financial, insurance, and wealth management sectors. Data mainly comes from steel plant production logs, batch quality inspection reports, downstream purchase orders, and industry association special steel category monitoring databases. Production logs are updated daily. Batch quality inspection reports are released with each smelting batch. Industry monitoring data is updated weekly.
Document structure includes batch details page, capacity summary page, and demand tracking page. Core fields include smelting batch number, alloy composition proportion, yield strength (MPa), delivery cycle (days), raw material purchase price (yuan/ton). Some documents include certification attachments from third-party testing institutions.
What constraints these characteristics impose on workflow orchestration
Differences in update rhythms across multi-source data require configuring independent scheduled trigger rules for each data source. This avoids repeated pulling or missing latest batch data.
The batched structure of special steel data requires the workflow to adapt to batch execution nodes. Tasks are split by smelting batch to avoid timeouts caused by single nodes processing excessive data.
The format diversity of third-party testing attachments requires configuring multi-format file parsing nodes. This adapts to different attachment types such as PDF and Excel.
Unit differences in core fields require presetting unit conversion rules in data cleaning nodes. This unifies units of strength and price fields from different sources, ensuring accurate subsequent verification logic.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Scheduled Trigger Interval | Set production data source to 86400 seconds, industry data source to 604800 seconds | Matches the actual update rhythm of the corresponding data source |
Batch Execution Node Batch Size | 50 batches per run | Adapts to the conventional processing scale of special steel smelting batches, avoiding single-node timeouts |
File Parsing Supported Formats | PDF, Excel, TXT | Covers common attachment output formats from third-party testing institutions |
Model Node Thinking Switch | Enabled | Meets compliance verification logic for alloy composition and strength data |
Global Variable Batch Append Rule | Associate and store by smelting batch number | Enables aggregation of batch results within loop nodes using unique identifiers |
Node Error Retry Count | 3 times | Addresses temporary network fluctuations or interface rate limiting for model requests |
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 against your own samples before finalizing settings.
Three common mistakes
- Phenomenon: When configuring a model node, only adjusting the "Display Thinking" switch fails to disable the model's chain-of-thought generation, resulting in redundant output. Cause: Failed to correctly identify the scope of the
model node thinking switch, confusing the interface display switch with the reasoning logic switch. - Phenomenon: After the batch execution node completes, the global variable only retains the results of the last batch, making it impossible to obtain all sub-item data. Cause: The
global variable batch append rulewas not configured, and the global variable was only assigned directly, overwriting previous batch results. - Phenomenon: After a model request reports an error, the workflow terminates directly without triggering retries or exception handling. Cause: Node error capture configuration was not enabled, and retry counts and exception branch logic were not set.
How to confirm the configuration is complete
- Trigger a manual run of the workflow, check whether the pull time of each data source matches the configured
scheduled trigger interval. - View the running logs of the batch execution node to confirm that the number of processed batches matches the preset
batch execution node batch size. - Upload a third-party testing attachment to confirm that the file parsing node successfully extracts core fields, and the format matches the configured
file parsing supported formats. - Simulate a model request error scenario to confirm that the workflow triggers the retry mechanism and generates corresponding exception records.
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.