What This Category of Data Looks Like
Core data for engineering consulting supervision comes from on-site supervision records, construction inspection materials, engineering change visas, and similar sources. Data is updated synchronously with construction progress. Single-use documents are typically individual special reports or batch acceptance ledgers. Document structures are fixed, including fields such as project number, full supervision unit name, construction location, rectification requirements, and acceptance results. Field units are mostly hours, items, or copies, with no dynamically changing floating-point values.
Constraints for Tool Calling and Plugins
Fixed document structures require preset field matching rules when calling tools, to avoid generating content that does not comply with supervision specifications. Data updated synchronously with construction progress requires plugins to use real-time pull mechanisms. Expired historical ledgers must not be used as generation basis. Fixed field units require tool calls to verify input parameter unit consistency, to prevent document errors caused by unit mismatches. The presence of batch acceptance ledgers requires tool calls to support batch reading and integration, to adapt to parallel processing needs for multiple documents.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to multi-scenario generation needs for engineering consulting supervision documents, automatically matching corresponding tool calling logic |
functionCall | Configured per preset supervision field templates | Adapts to document generation with fixed fields, accurately calling preset field filling tools |
| Tool call timeout period | 300 seconds | Supervision document generation requires pulling on-site ledgers and historical records; 300 seconds covers most query and verification processes |
| Single-generation character limit | 8000–12000 characters | Supervision special reports are typically moderate in length; this range covers complete content for most documents |
| Batch document processing limit | First 20 copies | Single-batch supervision acceptance ledger count is usually limited; 20 copies balances processing efficiency and content completeness |
Three Common Mistakes
- Inserted URL image addresses in generated documents appear only as plain text links, and cannot render properly. This occurs because plugin image rendering rules are not configured, and tool calls only return the image URL without triggering front-end rendering logic.
- Tool call results differ from direct large model
functionCallcalls with identical input. This occurs because FastGPT tool calls automatically handle context truncation and parameter verification, which differs from the parameter passing logic of native function calls. - Locally created MCP services cannot be called normally, and tool calls return a connection timeout error. This occurs because correct local service port and access path are not filled in plugin configurations, and cross-domain access permissions are not enabled.
How to Verify Configurations Are Correct
- Manually trigger a tool call, and verify that the generated document includes preset fixed fields, and that field units comply with general supervision industry specifications.
- View plugin operation logs to confirm successful pulling of the latest project data, with no connection timeouts or parameter errors.
- Test the batch document processing workflow to confirm the tool reads corresponding ledger files per the configured quantity limit.
- Insert a test image URL, and verify that image content displays normally in the document.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.