What the data for this category looks like
Business data sources for steel smelting include blast furnace temperature sensors, steelmaking central control systems, rolling mill PLC equipment, quality inspection laboratory reports, and more. Data update rhythms fall into three categories: real-time sensor data updates every second, production plan data updates per shift, and quality inspection report data updates daily. The document structure uses a standardized format, containing fields such as device ID, timestamp, parameter value, and batch number. Parameter units include degrees Celsius, kilopascals, millimeters, minutes, and more. There is no fixed unified document template, and matching field rules must be done according to process type.
What constraints these characteristics impose on workflow orchestration
Real-time high-frequency sensor data requires workflow trigger frequency to be no lower than 10 seconds per trigger, otherwise abnormal equipment fluctuations cannot be detected. Structured data with multiple types and fields requires mapping via the variables configuration parameter to avoid field conflicts across different processes. File data such as images and PDF reports from quality inspection links requires the workflow to support dedicated file import and transcoding nodes. Parameter thresholds vary significantly across different processes, so the workflow must support dynamic parameter adjustment to fit business needs for scenarios like blast furnaces and rolling mills.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Map parameters grouped by process, for example, bind blast furnace temperature and furnace pressure to corresponding variable names | There are many types of steel smelting equipment parameters; grouped mapping prevents field matching errors |
| File upload size limit | 1000 MB | Single business files such as quality inspection reports and furnace condition images typically fall within this size range, calibrated based on actual measurements |
| Workflow timeout threshold | 600 seconds | Smelting processes have relatively long waiting cycles; an overly short timeout will interrupt normal execution flows |
nodeId | Bind a dedicated ID to each process node, for example, bind the feeding node and temperature measurement node to corresponding IDs | Allows accurate location of execution nodes during cross-process calls, preventing process chaos |
| Global variable configuration | Bind the knowledge base ID as a global variable | Supports passing the knowledge base via API without repeated ID configuration |
Three common errors
- Symptom: After calling the API to upload a local image, the base64 encoded field output by the workflow is empty. Cause: The output mapping of the transcoding node was not configured via
variables, so the transcoding result is not passed to subsequent AI nodes. - Symptom: A parameter error prompt is returned when calling the API to pass the knowledge base. Cause: The knowledge base ID was not bound as a global variable, and the directly passed custom ID does not match the variable rules preset in the workflow.
- Symptom: The workflow is interrupted after exceeding the set threshold. Cause: The timeout threshold was set lower than the actual waiting duration of the smelting process, forcing termination of the normal flow.
How to confirm the configuration is correct
- Trigger the test file upload node, upload a furnace condition photo, and check if the transcoded base64 encoding in the workflow log displays correctly.
- Call the API to pass the preset knowledge base ID, and check if the returned workflow execution status is successful.
- Verify that the parameter mappings configured in
variablescorrespond one-to-one with the equipment parameter fields for steel smelting, with no omissions or mismatches. - Simulate high-frequency equipment data to trigger the workflow, and confirm that the node execution interval meets business requirements.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.