What data looks like for this category
Data for this category comes from steel coil labels and quality certificates, press and feeder operation data, mold management systems, MES systems, and coordinate measuring machine or fixture inspection results. Daily documents include stamping work instructions, material utilization rate sheets, mold inspection sheets, first/last piece records, dimensional inspection reports, and mold change records. Data updates are triggered per coil of material, per batch of materials, or each mold change. Fields include steel coil grade, sheet thickness, press operating pressure, mold number, mold change time, dimensional deviation values, and more. Units include millimeters, tons, hours, and others.
What constraints these characteristics impose on the tool calling and plugins workflow
Decentralized data sources and frequent update cycles require tool calling to support on-demand triggering of multi-source data pulling, to avoid accumulating too much invalid data in a single call. Multiple types of production documents require compatible parsing plugins to ensure accurate extraction of content from formats such as work instructions and inspection sheets. Fields use specific industrial units, so unified mapping must be completed in tool calling configurations to prevent ledger summary errors caused by unit mismatches. Mold changes are strongly linked to material batches, so tool calling must bind corresponding batches and mold change records to ensure generated ledgers correspond one-to-one with actual production steps.
How to configure settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapts to mixed scenarios of multi-data-source pulling and ledger generation, automatically matching corresponding tools |
| Workflow/API function-call configuration | enabled | Enables structured function calls to ensure tool return parameters can be accurately parsed for summary |
| Tool call timeout | 600 seconds | Covers response times of multiple data sources such as presses and mold management systems, to avoid mid-call interruptions |
| Parallel plugin call limit | 3 | Balances data pulling efficiency and system load, to avoid call failures caused by excessive concurrency |
| Field mapping rules | Match according to production document standard fields | Unifies field correspondence across different data sources, ensuring consistency in ledger fields |
Three common mistakes
- Symptom: Tool calling errors occur in runtime mode, but no errors appear in debug mode. Cause: Context quota or plugin permission configurations in runtime mode differ from those in debug mode, and plugin authorization configurations were not updated synchronously.
- Symptom: PDF document parsing plugin returns a connection failure, and connectivity cannot be restored even when using a local address. Cause: The port corresponding to the plugin was not opened during Docker deployment, or the container network was not properly bridged with the host network.
- Symptom: Ledger fields returned by tool calling have unit mismatches. Cause: No unified field mapping rules were configured, and raw data source unit formats were used directly, leading to unit confusion during summary.
How to confirm configurations are correct
- Manually trigger a tool call, and verify that the returned structured data includes all preset production ledger fields.
- Switch between runtime mode and debug mode, and confirm that the results and error messages from both calls are consistent.
- Check the plugin's port and network configurations, and confirm that the corresponding data source addresses can be accessed normally within the container.
- View the tool calling logs, and confirm that the
toolChoiceandfunctionCallparameter configurations have been loaded correctly.
The values provided here are common starting points and should be evaluated against the reader's own samples.