What this category of data looks like
Declaration materials and file review data for power generation equipment manufacturing mainly come from internal enterprise design drawings, factory inspection reports, grid connection approval files, and equipment operation and maintenance logs. Data is statically stored after archiving upon completion of individual projects. Operation and maintenance files are updated quarterly during inspection cycles. Document formats are primarily docx files with embedded parameter tables and pdf files with technical descriptions. Structured fields include equipment model, rated power, factory serial number, inspection batch, and approval node. Units involved include kW, MPa, operating hours, and other standard units.
What constraints these characteristics impose on tool calling and plugin workflows
The multi-format and structured nature of declaration and file data for power generation equipment manufacturing creates multiple constraints for tool calling and plugins. Mixed-format documents require plugins to support structured parsing of docx and pdf files. This avoids losing parameter tables when only plain text is extracted. Fields with specific units require plugins to retain unit information during parsing. This prevents unit mismatches in subsequent verification steps. Large volumes of data archived per individual project require tool call context length to support long document processing. This avoids truncating critical parameters. Regularly updated operation and maintenance files require plugins to be configured with trigger logic for pulling updated data sources on a set schedule.
How to set up configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Document parsing format | Prioritize parsing docx embedded tables and retain unit fields | Match the structured parameter table characteristics of power generation equipment data |
| Single call context length | 8000–12000 characters | Match the volume of single-project archived documents, avoid truncating critical parameters |
| Single call timeout | 600 seconds | Match the time requirements of long document parsing and multi-field verification |
toolChoice | auto | Adapt to the dynamic calling needs of multiple types of approval nodes |
functionCall | Enable mandatory parameter verification | Ensure that declaration fields meet required units and formats |
| Data source update cycle | Trigger quarterly | Align with the inspection and update rhythm of operation and maintenance files |
Three common errors
- Symptom: Plugins fail to read docx documents pointed to by a URL, returning connection timeout or file parsing failure. Cause: Structured parsing adaptation for docx format is not enabled in plugin configuration, and only plain text document pulling is supported.
- Symptom: Audit results do not include unit fields for equipment parameters, leading to verification failure. Cause: Unit information such as kW and MPa is not retained during document parsing, only pure numerical content is extracted.
- Symptom: Audit results returned after calling the
functionCalltool do not match preset declaration field requirements. Cause: Mandatory parameter verification is not enabled, causing non-standard format fields to be included in the audit scope.
How to confirm correct configuration
- Upload a docx document containing structured parameter tables such as rated power and factory serial number, check whether the parsing result retains fields and their corresponding units.
- Call the
functionCalltool, submit simulated declaration data that does not meet format requirements, and check whether parameter verification prompts are triggered. - Configure data source update trigger rules, verify whether the latest operation and maintenance file data is pulled according to the set cycle.
- Adjust the trigger logic of tool calls, check whether corresponding verification tools are triggered according to declaration and approval nodes.
The values given 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.