What the data for this category looks like
Data sources include resin batch property sheets, injection molding machine operating parameters, mold temperature controller logs, MES production management systems, and dimensional and appearance inspection equipment. Data is updated every production batch, each mold or material change operation, and at the end of each shift. Daily documents include injection molding process cards, raw material drying records, mold history sheets, first article inspection reports, production inspection logs, and material change and machine cleaning records. Document fields include core parameters such as resin batch number, drying temperature and duration, holding pressure and time, mold temperature set value, and inspection dimensions measured in millimeters.
What constraints these characteristics impose on the tool calling and plugins workflow
Multi-source and high-frequency updated data requires tool calling to pull the latest MES and inspection equipment data in real time, to avoid using expired process parameters. Diverse document types require plugins to adapt to field parsing rules for different documents, to accurately extract core information such as resin batch numbers and drying parameters. Frequent trigger nodes require the tool calling trigger logic to be bound to events such as mold changes, material changes, and shift-end inspections, to ensure the timeliness of data verification. The strong correlation between materials and processes requires tool calling to compare current raw material properties with process card parameters in real time, to prevent quality issues caused by material mixing or parameter deviations. Cross-component data interaction must also be compatible with output formats of different devices, to reduce call failure rates.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Supports automatic tool matching for multiple types of documents in injection molding scenarios. FastGPT v4.17.0 supports flexible configuration of this parameter |
| Workflow/API function-call configuration | {"name": "validate_injection_doc", "parameters": {"batch_no": "", "dry_temp": "", "mold_temp": ""}} | Matches core field verification logic for injection molding process cards and raw material records |
| Single tool call timeout | 600 seconds | Covers the time required for batch queries and data integration of mold history sheets and multi-batch property sheets |
| Tool call trigger timing | Triggered by mold/material change events, complete inspection data at the end of each shift | Matches the data update rhythm of this category, to avoid invalid calls |
| Log output level | Detailed | Facilitates troubleshooting of cross-component tool call exceptions, aligns with debugging needs for multiple data sources in this scenario |
Three Common Mistakes
- Phenomenon: Tool call returns Invalid JSON: Bad control character error. Cause: No escape processing for line breaks and tabs in raw material drying records, leading to generated call parameters that do not meet format requirements.
- Phenomenon: Tool call node cannot add connection lines, no connection circles are displayed. Cause: The tool call plugin enable switch for the corresponding workflow is not turned on, or the plugin configuration has not been saved.
- Phenomenon: MCP auxiliary task takes too long to think and detailed logs cannot be viewed. Cause: The candidate range of tool calls is not limited, and the detailed log output switch is not turned on.
How to Confirm the Configuration Is Complete
- Upload a latest raw material drying record, trigger tool call, check if verification results for corresponding fields are returned.
- View workflow logs, confirm that the tool call parameter format conforms to JSON specifications, with no illegal control characters.
- Try dragging connection lines on the tool call node, confirm that connection circles are displayed normally.
- Trigger a simulated mold change event, check if the tool call is automatically executed at the configured timing.
The values provided are common starting points and should be measured against the user's own samples.