What Data for This Category Looks Like
Data for this category is generated and used by manufacturing enterprise change management teams. Core documents include ECN/ECR forms, change assessment reports, drawings and BOM version records, process validation reports, production switchover plans, inventory disposal documents, and customer approval files. Data sources cover PLM, ERP, MES systems, supplier qualification materials, validation test records, and customer specific requirements. Updates trigger irregularly with each process or engineering change. Data fields include change number, version number, effective time, impact scope, approval status, and other items. No unified fixed batch update rhythm exists for this data.
Constraints for Tool Calling and Plugin Workflows
Data for this category spans multiple systems and uses varied formats. Tool calling must support associated retrieval across PLM, ERP, MES and other data sources to ensure change data integrity. Change triggers follow no fixed cycle. Plugins must support on-demand triggering to adapt to temporarily initiated change audit scenarios. Documents include structured forms and unstructured drawings, validation reports. Tools must support multi-format data parsing to cover field extraction and content verification needs. Changes involve cross-departmental approval statuses. Plugin calls must carry accurate change numbers and permission parameters to avoid pulling invalid data that has not completed approval.
Configuration Guidelines
This configuration is written for the FastGPT v4.17.0 plugin system.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool calling trigger timing | Triggered on change status update | This category of change triggers has no fixed cycle; on-demand triggering avoids invalid calls |
| Data source connection timeout | 600 seconds | Cross-system retrieval of PLM and ERP data requires sufficient wait time to prevent failure due to network latency |
| Single batch data retrieval count | Top 10 entries | Single batches of change data should not be too large to avoid plugin processing timeouts |
| Workflow/API tool selection | auto | Adapts to parsing requirements for multiple types of change documents, automatically selects appropriate tool functions |
| Workflow/API function-call configuration | Bound by change type | Different change types require different parsing plugins to accurately match data extraction rules |
| Plugin call retry count | 3 times | Addresses call failures caused by temporary network fluctuations |
| Maximum context length | 8000 token | Adapts to text parsing for multi-page drawings and validation reports |
Three Common Configuration Mistakes
- Symptom: When using a database connection plugin to connect to PostgreSQL, the error "Workflow verification failed. Please check for missing or empty values, and verify that connections are properly configured" appears. Cause: The database table name and change number field associated with the change data were not filled in the plugin configuration, or the field configuration does not match the actual fields in PLM or ERP systems.
- Symptom: Tool calling runs normally in debug mode but throws an error in runtime mode. Cause: Permission credentials for cross-system access were not configured in runtime mode, or the approval status parameter for change audits was not bound, leading to permission verification failure.
- Symptom: A request error occurs when calling the marker-pdf plugin, and connection fails even when deployed using 127.0.0.1. Cause: The plugin container and FastGPT container are not on the same Docker network, or the corresponding port of the plugin service was not opened, leading to cross-container network connection failure.
How to Verify Successful Configuration
- Review plugin call logs to confirm that retrieved change data includes core fields such as ECN number and version number, and that field content matches records in the PLM system.
- Simulate a temporary change trigger to check whether the plugin can normally retrieve corresponding data and complete format verification.
- Configure permission verification parameters to verify that change data that has not completed approval will not be pulled into the audit workflow.
- Adjust the data source connection timeout to confirm that connection timeout errors are not triggered in network latency scenarios.
The values provided are common starting points and should be measured against the reader's own samples.