What Data for This Category Looks Like
The data for this category primarily comes from raw fiber inspection reports, ERP systems, real-time collected data from spinning and weaving machines, evenness testers, fabric inspection machine test results, and order specification documents. Update frequency syncs with each batch of raw materials, each shift’s production, and each piece of cloth produced. Daily documents include cotton blending or batching lists, process setup sheets, equipment operation records, yarn inspection sheets, grey fabric inspection sheets, and defect ledgers. Fields cover fiber indicators, process parameters, equipment operating status, and test results. Units include grams per meter, twists per meter, and other relevant units.
Constraints on Tool Calling and Plugin Configuration
High update frequency, scattered data sources, and diverse document types for this category create multiple constraints for tool calling and plugin configuration. First, frequently updated raw material, production, and test data require plugins to support real-time data pulling, to prevent outdated parameters from static caching. Second, multi-source data transfer logic requires plugins to configure data sources in the order of ERP, spinning machines, and test equipment, to align with standard business processes. Additionally, multiple types of business documents require plugins to support association with different knowledge bases, to match query needs for core documents such as cotton blending lists and process sheets. The large number of equipment units and continuous spread of defect data also require tool calling to support bulk equipment data pulling and cross-batch defect correlation analysis.
Configuration Settings
This configuration applies to FastGPT v4.17.0 and later versions.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Supports automatic tool calling for scenarios including equipment inspection, fault troubleshooting, and parameter queries |
| Workflow/API function-call configuration | enabled | Forces tool calling to ensure that equipment parameter and process knowledge bases are called during maintenance Q&A sessions |
| Tool call timeout threshold | 300 seconds | Equipment data pulling and test result queries for this category typically take 100-200 seconds, with a reasonable buffer added |
| Multi-source data source configuration order | Configure data sources in the order of ERP, spinning machine collection equipment, and test equipment | Aligns with the data transfer logic from raw materials to finished products for this category |
| Knowledge base association scope | Bind cotton blending lists, process setup sheets, and defect record knowledge bases | Matches the core types of daily business documents for this category |
| Tool return content filtering rules | Only display final maintenance recommendations | Avoids redundant intermediate call logs from interfering with maintenance personnel’s judgment |
Three Common Mistakes
- Symptom: An "invalid key" prompt appears when calling the application, and the interface returns a call failure. Cause: The application-specific app key was not used, and an account-level account key was mistakenly used for authentication.
- Symptom: Calling a workflow nested with a knowledge base assistant via the API returns an empty value. Cause: The current FastGPT version is lower than v4.8.10, which does not support the API calling logic for workflows nested with knowledge base assistants.
- Symptom: Intermediate return content from two levels of tool calls in a workflow is printed and displayed, interfering with viewing the final result. Cause: No tool return content filtering rules were configured, and all levels of call logs are displayed by default.
How to Verify Correct Configuration
- Initiate a query related to equipment inspection, to verify whether the tool call automatically pulls real-time operating data of the corresponding spinning machine.
- Trigger the workflow via the API, to check whether the returned results include process parameter content matched by the knowledge base, with no empty values returned.
- View the application interface embedded via iframe, to confirm that the application image and user avatar display correctly in commonly used browsers.
- Trigger a workflow with two levels of tool calls, to verify that the intermediate call content from the first level is not displayed directly.
Note: The values provided here are common starting points, and should be evaluated against specific samples and use cases.