What the data for this category looks like
The data for this category primarily comes from order design systems, sheet and wood batch ledgers, CNC cutting and drilling equipment, ERP/MES systems, and moisture content testing equipment. Data update frequency aligns with production milestones. Each custom order generates exclusive split-order data, production progress is synced daily, and batch information is updated for each raw material batch. Daily documents include split-order drawings, cutting lists, edge banding and drilling programs, coating process documents, hardware material lists, trial assembly and packaging records. Fields include panel dimensions, material batch numbers, process parameters, hardware models, etc., using industry-standard units such as millimeters and kilograms.
What constraints these characteristics impose on the tool calling and plugins link
The custom-order-driven multi-panel production model requires tool calling to support pulling heterogeneous data across multiple systems, and adapt to dynamically changing production parameters. Frequently updated raw material batch and order progress data requires tool calling context synchronization frequency to match production milestone rhythms, to avoid calling expired data. The mixed processing requirement for multiple types of production documents requires tools to support parsing data sources in different formats such as split-order drawings, cutting lists, and process programs, and establish association logic for fields such as panel dimensions and batch numbers. The production characteristic of no fixed BOM requires tool calling to adapt to dynamic data association logic, without relying on fixed templates. Information returned by tool calling must include traceable field identifiers, to quickly locate panel batches and production links, and support quality problem traceability analysis.
How to set up the configuration
This page’s configuration instructions are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | Auto mode | Adapt to dynamic calling requirements for multiple types of production data, no need to manually specify a single tool |
| Workflow/API function-call configuration | Enabled | Force generation of structured tool calling requests, adapt to precise matching of fields such as panel batches and dimensions |
| Single tool call limit | Top 10 data entries | Match the conventional range of panel quantity per batch of custom orders, avoid returning excessive redundant information |
| Tool call timeout | 600 seconds | Adapt to time requirements for pulling production data across systems, avoid call interruptions due to large data volume |
| Tool call retry count | 3 times | Address temporary network fluctuations when pulling data across systems |
| Maximum context length | 8000 characters | Adapt to splicing requirements for multiple types of production documents in this category, avoid context overflow |
| Context association fields | Panel dimensions, material batch numbers | Match core association fields for category data, ensure data returned by tool calling is accurately bound to the current production task |
Three common mistakes
- Symptom: Tool calling returns empty results. Cause: The context of tool calling is not bound to the panel data of the current order, so the tool cannot obtain a valid retrieval range.
- Symptom: Tool calling returns Invalid JSON: Bad control character error. Cause: Newline characters and special symbols in production documents are not escaped, causing the generated tool calling request format to fail to meet requirements.
- Symptom: Tool call nodes cannot add connection lines, and call termination logic cannot be configured. Cause: The tool calling function switch for the corresponding node is not enabled, and the connection configuration control is not loaded in the interface.
How to confirm the configuration is correct
- Submit a test task, view the tool calling log, confirm that the returned data includes core category fields such as panel dimensions and material batch numbers.
- Simulate a production data exception scenario, trigger tool calling, check whether a structured request that meets requirements is generated.
- Verify the node connection function, confirm that connection lines between tool calling nodes and subsequent processing nodes can be added via dragging.
- Test the timeout scenario, confirm that the tool calling triggers termination logic after the set timeout period, with no residual unfinished tasks.
The values provided are common starting points and should be measured against the reader's own samples.