This document is written based on FastGPT v4.17.0.
What the data for this category looks like
Core data for this category comes from engineering, production, quality, and laboratory teams at printed circuit board factories. Daily documents include engineering production instructions, Gerber analysis records, drilling and lamination parameters, chemical solution analysis, AOI reports, electrical test reports, and slice reports. Data sources include Gerber, drill tape, and BOM files provided by customers, as well as CAM system data, production equipment parameters, bath solution test results, data collected from AOI and electrical test equipment, and laboratory test records. Data fields include specialized content such as drilling parameters, lamination temperature, AOI defect locations, and electrical test continuity values, with units including mils, degrees Celsius, millimeters, and other industry standard units. Data update frequency is adjusted according to production rhythm, including updates per production batch or per shift. Some equipment data is collected continuously.
What constraints these characteristics impose on the tool calling and plugins link
PCB manufacturing has diverse data formats, including binary Gerber files, tabular electrical test reports, and image-based AOI and slice reports. This requires tool calling plugins to support parsing and access to multi-format data. Data update frequency is high and batch-oriented, so tool calling must adapt to batch processing and real-time synchronization requirements to avoid delays that slow down audit processes. Core audit links rely on engineering document conversion and electrical continuity checks. Tools must interface with core systems such as CAM and electrical test data, and also have error capture capabilities to avoid serious consequences like scrapping entire batches of boards due to abnormal data. The specialized nature of data fields requires tools to accurately identify specialized parameters when called, to avoid parsing failures caused by format mismatches.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Supports model autonomous judgment of whether to call tools, adapting to dynamic processing needs for multiple types of data sources in PCB audits |
| Workflow/API function-call configuration | Trigger per preset rules | Fixed calls to specified tools for standardized operations such as Gerber parsing and electrical test data query |
| Tool call timeout threshold | 60 seconds | Core operations such as Gerber parsing and AOI report analysis usually take relatively short time; setting a timeout prevents process blocking |
| Plugin retry count | 3 times | PCB production data updates frequently, avoiding interruptions to audit processes due to single call failure |
| Tool call cache duration | 4 hours | Matches the data update cycle per production batch, reducing repeated call overhead |
| Keywords triggering tool calls | Gerber, AOI report, electrical test data | Accurately matches core data sources for PCB audits, reducing invalid calls |
Three common errors
- Phenomenon: When calling a multimodal visual model to process AOI slice report images, an error "unable to download image" is returned. Cause: Access permissions for the image storage path are not configured, or the plugin did not correctly interface with the download interface of the image data source, resulting in failure to obtain AOI report images required for PCB audits.
- Phenomenon: Tool call trigger rules are configured incorrectly, resulting in unprocessed core Gerber parsing requests. Cause: Trigger keywords do not include PCB-specific data source keywords such as Gerber and drill tape, so the model cannot identify scenarios that require tool calls.
- Phenomenon: When pushing audit results via DingTalk webhook, key information such as production batch number and AOI defect type is not included. Cause: Core fields for PCB audits such as production batch number and AOI anomaly type are not bound in plugin configuration, resulting in missing valid audit basis in pushed content, which cannot support subsequent supplier quality traceability.
How to confirm correct configuration
- Upload a test Gerber file to trigger tool calling, check if parsing is correct and return analysis results including drilling parameters and lamination requirements.
- Upload a test AOI report image, call the multimodal tool, confirm no "unable to download image" errors, and that defect locations in the image are correctly identified.
- Configure DingTalk webhook to push test data, check if the receiving end receives audit results including production batch number and AOI anomaly type.
- View tool call logs, confirm that trigger rules match correct data source keywords, call count matches preset retry times, and no abnormal timeout errors occur.
The values provided are common starting points and should be measured against the reader's own samples.