What data for this category looks like
Data for this category is generated by manufacturing enterprise change management teams. It covers cross-department collaboration across research and development, process, quality, production, and procurement teams. Data sources include PLM, ERP, MES, supplier materials, validation tests, and customer special requirements. Updates are triggered irregularly for each change. Core documents include ECN/ECR, change assessment reports, drawings and BOM versions, process validation reports, transition plans, inventory disposal forms, and customer approval documents. Structured fields include change number, effective date, and affected bill of materials. Unstructured content includes drawings and test reports.
Constraints on tool calling and plugins for this category
Data for this category is scattered across multiple systems with no fixed update cycle. Tool calling must support on-demand triggering to meet temporary data requirements for each change. Documents contain mixed structured and unstructured content. Format parsing plugins are required to handle files of different formats. Changes involve cross-department collaboration. Tool calling must integrate permission checks to prevent unauthorized access to sensitive customer approval documents and process drawings. Change data volume fluctuates based on impact scope. Resource allocation for tool calling must be adjusted dynamically to avoid overload during single calls.
Configuration settings
This configuration is based on the FastGPT v4.17.0 plugin system.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Supports automatic matching of tools for change scenarios, adapts to different types of change requirements |
| Workflow/API function-call configuration | enabled | Forces structured tool calling to ensure generated change documents and abnormal reports meet compliance formats |
| Multi-source data fetch plugin | Call on change trigger, fetch up to 5 data source entries per call | Adapts to the irregular update feature of this category's data, avoids ineffective scheduled fetching |
| Timeout threshold | 120 seconds | Reserves sufficient time for cross-system data fetching and format parsing |
| Format parsing plugin | Prioritize parsing the first 3 associated documents, maximum 1500 characters per document | Prioritizes documents core to the change, improves processing efficiency |
| Permission check configuration | Set based on actual testing | Adapts to differences in permission rules across enterprises, ensures data access compliance |
Three common errors
- Phenomenon: When calling the AntV Chart MCP plugin, only XML or JSON code blocks are returned, and no visual charts are rendered. Cause: Associated trigger rules for chart rendering are not configured. Tool calling only completes data fetching and does not execute the rendering step.
- Phenomenon: Change documents generated via API calling differ significantly from results from online chat. Cause: The API request does not carry complete context parameters, or the knowledge base association configuration enabled in online chat is not synchronized.
- Phenomenon: Empty fields are returned when fetching PLM data via tool calling. Cause: Permission check parameters for the data source are not correctly configured. Access to drawing and BOM version data associated with the corresponding change is blocked.
How to verify correct configuration
- Initiate a simulated change request. Check if the tool calling log automatically matches the fetching action for the corresponding data source.
- Enter a query related to the change. Confirm that returned results include structured tool calling output and compliant document formats.
- Call the API interface to initiate the same request. Compare returned results from online chat and the API to confirm consistency.
- Test abnormal scenarios, such as requesting a non-existent change number. Check if the tool calling returns clear error prompts.
The values provided are common starting points and should be measured against the reader's own samples.