What the data for this category looks like
Normally, business data for mold design and manufacturing comes from customer product models, mold flow/forming simulation files, CAD/CAM drawings, machining and measurement records, and trial mold sample data. Data updates proceed according to project milestones, with new documents and records generated after each trial mold or mold modification. Daily documents include mold design task sheets, DFM reports, part drawings, machining process cards, trial mold reports, mold modification notices, and mold records. Fields include mold number, part material, number of cavities, demolding angle, shrinkage rate, etc. Units are mostly millimeters, megapascals, hours, and similar.
What constraints these characteristics impose on the "tool calling and plugins" link
Heterogeneous data from multiple sources requires tool calling to support parsing of different formats, to avoid calling failures caused by mismatched data formats. Frequent updates according to project and trial mold milestones requires tool calling to trigger dynamically, to adapt to temporarily generated exception reports and process documents. The complex document field structure requires tool calling to accurately match preset fields, to ensure that the data written into process documents meets enterprise standardization requirements. At the same time, the consequences of errors such as mold delivery delays and workpiece defects require tool calling to have failure retry and result verification capabilities, to ensure stable business processes.
How to set the configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Workflow/API tool selection | Set to auto | Adapts to automatic scheduling of multiple tools in mold design scenarios, no need to manually specify calling items, and meets the processing needs of multi-source data |
| Workflow/API function-call configuration | Enable forced mode | Ensures that tool calls return structured results, making it easy to accurately extract mold fields and write them into standardized process documents |
| File upload timeout threshold | 300–600 seconds | Adapts to the upload and parsing process of large files such as CAD drawings and trial mold reports. FastGPT v4.17.0 supports customizing this parameter |
| Tool call retry count | 2–3 times | Responds to network fluctuations or temporary interface exceptions during trial mold data synchronization, reducing the probability of call failures |
| Context window size | 8000–12000 token | Accommodates complete mold project documents and historical iteration records, ensuring that tool calls can obtain sufficient context information |
Three common mistakes
- Calling the Feishu multi-dimensional table interface returns a 400 error, with empty fields. Cause: The standardized fields in mold documents (such as mold number, number of cavities) are not matched, resulting in interface verification failure.
- After calling the MySQL tool to obtain trial mold data, the large language model response does not reference original data fragments. Cause: The structured return configuration of
functionCallis not enabled, making it impossible to extract and retain database original text fragments. - Uploading a CAD file shows no index completion status for a long time. Cause: A reasonable timeout threshold is not set, or the parsing queue for large-size drawings is not adapted, resulting in task backlog.
How to confirm the configuration is complete
- A tool call based on a trial mold report is initiated, and the returned result is checked for the presence of preset mold standardized fields.
- The Feishu multi-dimensional table interface is called, simulated mold process data is submitted, and the interface is confirmed to return a successful status code.
- A small CAD drawing is uploaded, and after waiting, the file index status is checked to confirm that parsing is completed.
- The MySQL tool is called to obtain trial mold data, and the output result is checked for retention of complete fragments of the original data.
The values provided are common starting points and should be measured against the reader's own samples.