What data looks like for this category
Data for this category primarily comes from BIM detailed design documents, rebar and concrete batch ledgers, mold table and curing kiln operation records, laboratory test reports, and component QR code traceability systems. Daily documents include component detailed drawings, rebar cutting lists, mold inspection records, pouring and vibration logs, curing cycle records, and demolding and factory inspection reports. Data is updated per individual component, each batch of materials, and each curing kiln run. Fields include component ID, rebar specification, concrete strength grade, curing duration, inspection pass flag, and others. Most units use engineering standard units such as millimeters, megapascals, and hours. The typical range for curing duration is 24–72 hours.
What constraints these characteristics impose on tool calling and plugins
Data sources are scattered, and update granularity is fine. Tool calling must support batch pulling and real-time synchronization across multiple data sources. Field matching for component detailed drawings and cutting lists must accurately correspond to details such as rebar specifications and embedded part positions. Tools must be able to parse CAD-format engineering drawing data. Real-time data from curing kilns and mold tables requires high-frequency synchronization. The trigger frequency of tool calling must adapt to the curing cycle of each kiln run. QR code traceability data must be bound to the unique identifier of individual components. Tools must support querying full-process records associated with the identifier. The consequences of errors are severe. Result validation for tool calling must cover core indicators such as strength and position, to prevent incorrect data from entering the audit process.
How to configure settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapts to multi-tool calling scenarios, automatically matching the tool types required for the current audit workflow |
| Tool calling timeout | 300–600 seconds | Cross-system data pulling for precast concrete components covers design, production, and inspection phases, requiring sufficient response time |
| Number of entries returned per tool call | Top 10 entries | The volume of associated ledger data for a single batch of components is moderate, preventing excessive returned data from causing workflow stalls |
| Workflow/API function-call configuration | Enable mandatory validation | Ensures tool calling output meets the format requirements for audits, preventing invalid data from entering the workflow |
| Plugin cache duration | 4–8 hours | Batch data for precast concrete components is updated at a low frequency, setting a reasonable cache to avoid repeated pulling |
| Workflow nested call permission | Allow passing context parameters | Adapts to the needs of split audit workflows, supporting calls to sub-workflows for specialized inspection or data verification |
Three common mistakes
- Phenomenon: After a custom plugin runs, the output download address keeps flickering before returning a result. Cause: The result waiting logic for tool calling is not configured, causing the system to repeatedly poll the plugin service until complete output is generated.
- Phenomenon: A third-party interface call prompts
Error: write EPROT. Cause: HTTPS protocol certificate verification rules are not configured correctly, resulting in a protocol error during data transmission. - Phenomenon: After a parent workflow calls a sub-workflow, the sub-workflow fails to execute completely. Cause: The context passing configuration for workflow nesting is not enabled, so the sub-workflow lacks necessary input parameters.
How to confirm configurations are correctly set
- Trigger a complete audit workflow, check whether the returned results of tool calling include all required data types such as component detailed drawings and curing records.
- Simulate abnormal data input, verify whether the tool calling validation logic can identify issues such as mismatched rebar specifications and insufficient curing duration.
- Call a nested workflow, confirm that the execution results of the sub-workflow can be fully passed back to the parent workflow and participate in subsequent audit steps.
- Test HTTPS interface calls, confirm that there are no protocol errors during data transmission, and that the returned test data matches the actual ledger records.
The values provided are common starting points and should be measured against the reader's own samples.