What data this category covers
This category of data covers end-to-end records from enterprise metrology rooms and CNAS system laboratories. It includes gauge ledgers, calibration plans, calibration certificates, periodic verification reports, original test records, reference material ledgers, and deviation handling documents. Data sources include internal metrology management systems, external calibration institution certificates, standard devices, LIMS systems, and environmental monitoring data. Updates align with calibration cycles, single test nodes, or when abnormal events occur. Core fields include instrument ID, calibration validity period, measurement uncertainty, test environmental parameters, and handling results.
What constraints these characteristics impose on workflow orchestration
Data sources for this category are scattered, and formats are inconsistent. Workflow orchestration must support multi-source data pulling and structured parsing. Update rhythms change dynamically with calibration cycles and test nodes. Fixed scheduled triggers cannot be relied upon, so event-driven node jumps must be configured. Core documents include multi-dimensional professional fields, such as measurement uncertainty in calibration certificates and approval records for deviation handling. Workflow nodes must support precise field extraction and binding. To trace the product scope affected by inaccurate instruments, workflows must link metrology data and production batch data. Cross-module variable transfer rules must be configured.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables configuration | Bind calibration certificate number, instrument ID | Support transferring core traceability fields across nodes |
| Node trigger rule | Trigger by abnormal events | Match the non-scheduled update characteristics of data in this category |
| Knowledge base recall limit | Top 8 entries | Calibration certificates and test records are concise, no need for excessive recall |
| Conversation context length | 1200–1800 characters | The content length of core documents in this category falls within this range |
| Node timeout setting | 600 seconds | Time spent on calibration certificate parsing and data association does not exceed 10 minutes |
| Node error handling | Trigger alert and record nodeId | Quickly locate abnormal workflow nodes |
| Variable transfer rule | Set based on actual calibration | Traceability field structures vary across different laboratories |
Three common configuration errors
- Workflow stops after reaching a specific node, and the interface displays "Cannot convert undefined or null to object". Cause: No null value check is performed on the calibration certificate number field bound in
variables. A type conversion error is triggered when this field is missing. - Workflow cannot use historical records as code runtime variables. Cause: No globally reusable historical record storage node is configured in
variables, and data is only temporarily stored within a single node. - Only AI chat module output can be displayed in the dialog box, and subsequent node results cannot be processed. Cause: No result output binding node is configured, and post-processed content is not mapped to the dialog box display field.
How to confirm the configuration is correct
- Use the workflow editor in FastGPT v4.17.0 to trigger a simulated abnormal event, and check if the workflow jumps to the corresponding node according to preset rules.
- Pull workflow operation logs, and confirm whether the traceability fields in
variablesare correctly transferred to each node. - Run test data with complete fields, and check that no type conversion errors occur.
- Configure result output binding, and verify that processing results from non-AI chat modules can be displayed in the dialog box.
Note: The configuration values listed above are common starting points. Adjust them based on your own specific samples and use cases.