What this category of data looks like
Data sources for this category include MES systems, online testing equipment, laboratory test results, process parameter logs, customer quality standards, and historical defect databases. Data update cycles follow production batches, shift cycles, or continuous collection. Daily documents include control plans, patrol inspection records, SPC reports, finished product inspection reports, nonconforming product review forms, release forms, and quality monthly reports. Fields include inspection item numbers, defect levels, release thresholds, batch identifiers, nonconforming judgment results, and more. Units adapt to document types and content, with no unified fixed standard.
What constraints these characteristics impose on the "tool calling and plugins" link
Multi-source and heterogeneous data sources require tool calling to support cross-system data pulling and format adaptation. High-frequency update cycles require plugin configuration to adapt to real-time or near-real-time data synchronization, to avoid expired data affecting the accuracy of bid quotations. Diverse document types require tools to support parsing of documents with different structures, including clause-divided control plans and batch-summary inspection reports. The feature of non-unified field naming requires plugins to support custom field mapping rules to adapt to field differences across different documents. In bid scenarios, it is necessary to associate customer standards with historical defect databases, and tool calling must support accurate matching of corresponding quality clauses.
How to configure the settings
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapts to multi-tool calling scenarios, automatically matches quality data pulling and document generation needs |
| Document chunking rules | Preset by document type: control plans chunked by clauses, inspection reports chunked by batches | Significant structural differences exist across documents in this category; preset chunking improves parsing accuracy |
| Data pulling interval | 10–30 minutes | Matches the update cycle of batches and shifts, avoids using expired data that affects bid content |
| Workflow/API function-call configuration | enabled | Supports calling multiple tools to complete cross-system data aggregation, document format conversion, and bid document splicing |
| Custom field mapping | Enabled | Adapts to the feature of non-unified field naming within the category, achieves field standardization across different documents |
| Real-time response switch | Calibrated based on actual testing | Adapts to urgent data update needs in bid scenarios, balances resource usage and response speed |
Three common mistakes
- Phenomenon: No return data after calling a custom URL parsing tool, with no abnormal errors shown in logs. Cause: No category-specific document parsing adaptation rules configured, so the structure of specific documents such as control plans and inspection reports cannot be recognized.
- Phenomenon: When sending consecutive API requests, subsequent requests wait for previous requests to complete before processing. Cause: No reasonable concurrent request rules configured; the server processes requests in queue order by default, and does not support real-time interruption of the generation process.
- Phenomenon: Model output in the workflow cannot be directly converted to a document format usable for bids. Cause: The document conversion tool configured with
functionCallis not enabled, and category-specific document template mapping rules are not bound.
How to confirm the configuration is correct
- A test request to call the data pulling tool is initiated, and the returned content is checked for core data such as current production batch inspection reports and control plans, to confirm that the data pulling interval configuration is effective.
- Multiple consecutive API requests are simulated, and whether subsequent requests can interrupt previous generation processes is verified, to confirm that concurrency and interruption configurations meet scenario requirements.
- Typical documents within the category are uploaded, and whether parsed fields can be correctly mapped to preset custom field rules is checked, to confirm that the document parsing configuration is effective.
- The server's cross-domain configuration is checked for allowance of access from the bid system's domain name, to confirm that there are no cross-domain errors in API calls.
The values provided are common starting points and should be assessed against applicable samples.