What the data for this category looks like
Data sources include engineering orders, sand, gravel, cement and admixture inspection records, on-site aggregate moisture content measurement data, mixing plant control system production records, and laboratory test reports. Update frequency follows per production task per vehicle, per batch of incoming raw materials, and daily summary.
Daily documents include mix proportion notices, opening identification forms, production and delivery slips, raw material inspection records, test block molding records, and strength reports. Document fields include raw material dosage, reference water dosage, slump requirements, departure time, pouring location, test indicator values, and more. There is no fixed unified format, and corresponding information must be extracted separately by document type.
What constraints these characteristics impose on the tool calling and plugins link
Multi-source and scattered real-time data requires tool calling to support cross-system data pulling. This ensures that the latest raw material inspection and moisture content data are used for batching correction and scheduling coordination.
Field differences across multiple document types require plugins to be configured with flexible field mapping rules. This prevents data extraction failures caused by different document formats.
The high-frequency update rhythm requires tool calling to adapt to short-cycle tasks. This ensures that review tasks for a single production batch can be completed within a reasonable time frame.
Severe error consequences require tool calling to include abnormal threshold verification. This early identifies deviations in indicators such as slump and strength.
How to set the configurations
The following configurations apply to FastGPT v4.17.0
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | Auto | Adapts to cross-check requirements for multiple types of technical documents, no need to manually specify a single tool |
| Call timeout threshold | 120 seconds | Covers the typical time required for single-batch production data pulling and multi-document field comparison |
| Number of items returned per tool call | Top 8 | Matches the typical number of raw material inspection and test block records associated with one vehicle's production |
| Document chunking trigger threshold | 1500 characters | Adapts to content splitting for long documents such as mix proportion notices and strength reports |
| Document chunking overlap length | 100 characters | Prevents loss of contextual association after long document splitting |
| Workflow/API function-call configuration | Enabled | Supports directly returning structured verification results during tool calling, facilitating anomaly marking |
Three common mistakes
- Symptom: Tool calling records are not displayed in the calling log module of the FastGPT platform, making it impossible to troubleshoot verification exceptions for batching parameter corrections. Cause: The global switch for tool calling logs is not enabled, resulting in no retention of intermediate data during the verification process.
- Symptom: Empty fields are returned when calling raw material inspection data, making it impossible to complete slump requirement matching. Cause: No field mapping rules are configured for the corresponding data source, causing the tool to fail to correctly extract test indicators from raw material inspection records.
- Symptom: Tool calling times out, and cross-review tasks for production scheduling fail. Cause: The call timeout threshold is set to 60 seconds, which does not cover the actual time required for multi-document association comparison.
How to confirm correct configuration
- Initiate a simulated review task for a single production batch, check whether the document list returned by tool calling includes associated documents such as the corresponding mix proportion notice and raw material inspection records.
- View the calling log module of the FastGPT platform, confirm that each step's field extraction and parameter correction results are fully recorded, with no missing or abnormal prompts.
- Adjust relevant tool calling configurations, verify whether abnormal scenarios such as aggregate moisture content exceeding a reasonable range can correctly trigger verification.
- Upload a single test block strength report, check whether the tool can associate the age requirements of the corresponding opening identification form and complete strength matching verification.
The values provided are common starting points and should be measured against the reader's own samples.