What the data for this category looks like
Daily documents for this category include grouping rules, BOM lists, welding and torque records, BMS flash records, insulation withstand voltage reports, EOL test reports, and system configuration lists. Data is sourced from cell grading and sorting equipment, MES systems, welding equipment, torque tools, BMS software version repositories, and EOL test benches. The data update cadence is once per produced battery PACK or energy storage cabinet, with syncing each time the BMS software version changes. Document fields include material code, torque value, test voltage, software version number, and other items. Corresponding physical units include N·m, V, Ah, and others.
What constraints do these characteristics impose on the "workflow orchestration" link
Data sources for this category are scattered across multiple types of production equipment and management systems. Workflow orchestration must configure cross-data source pull nodes to obtain heterogeneous information such as cell grading and sorting data and welding torque records. Data update frequency is tied to individual product units. Workflows must support triggering variable replacement per individual product unit to avoid redundancy caused by full batch updates. Document fields include parameters with physical units. Workflows must add field validation nodes to check the units and formats of parameters such as torque values and test voltages. Bid documents must match grouping rules for different projects. Workflows must configure conditional branch nodes to adapt to compliance requirements for different projects.
How to set the configurations
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
| Variable Node | Bind the variables parameter of a single product unit, including cell grading and sorting data and BOM information | Matches the data update characteristic of this category per individual product unit |
| Timeout Setting | 600–1200 seconds | Covers the time requirements for multi-source data pulling and complex grouping calculations |
| Conditional Branch Node | Configure branch rules by project type | Adapts to grouping rules and quotation templates for different projects |
| Field Validation Node | Validate that torque value units are N·m and test voltage units are V | Ensures compliance with document parameter formats |
| Tool Call Node | Turn off the AI response output switch | Focuses on parameter transfer and document generation workflows |
| Code Execution Node | Configure timeout thresholds based on actual measurements | Adapts to complex grouping calculations and data integration logic |
Three common errors
- Phenomenon: Workflow execution exceeds 600 seconds and triggers a connection disconnect, returning a timeout status code. Cause: The workflow timeout configuration was not adjusted, and the default short timeout threshold was used, which cannot cover the time required for multi-source data pulling and complex grouping calculations.
- Phenomenon: After the tool call node completes execution, the interface returns empty AI response content. Cause: The AI response output switch of the tool call node was not turned off, causing the node output to be overwritten by AI responses, or the parameter transfer link was not configured correctly.
- Phenomenon: The code execution node outputs valid results, but the specified response node cannot read the result fields. Cause: The output variable of the code execution node was not correctly bound in the
nodeIdconfiguration, causing the parameter transfer link to break.
How to confirm the configuration is correct
- Use the workflow debugging tool in FastGPT v4.17.0 to trigger workflow execution for a single product unit, and check whether the variable node correctly pulls the cell grading and sorting data and BOM information for the corresponding batch.
- Run a workflow with validation rules, input parameters that do not meet unit requirements, and confirm that the field validation node triggers an error intercept.
- Call the workflow API, and check whether the returned results include complete bid documents and quotation data with no missing fields.
- Debug the tool call node, and confirm that there is no redundant AI response content after execution, only retaining the parameter transfer results.
The values provided are common starting points and should be measured against the reader's own samples.