What this category of data looks like
The business process data for power generation equipment manufacturing mainly comes from equipment operation and maintenance logs, parts quality inspection reports, project BOM lists, and industry technical standard documents. Data update rhythms vary by business stage: operation and maintenance logs are generated in real time as equipment runs. BOM lists are updated when a project is initiated or changed. Industry standard documents are revised quarterly or annually. Each document is tied to a single device or work order, and includes fields such as component number, rated power, operating temperature threshold, maintenance cycle, and fault code. All field units use international standard units, such as kW, ℃, hours, and times.
What constraints do these data characteristics impose on tool calling and plugins
The data characteristics of power generation equipment manufacturing impose multiple constraints on the tool calling and plugins workflow. Real-time generated operation and maintenance logs require that local cache duration for tool calls not be too long, to avoid returning outdated equipment operating data. Project-level BOM lists change frequently, so plugins must support dynamic binding of project numbers as call parameters to ensure pulled spare parts information matches the current work order. Equipment fault codes are strongly tied to operating parameters, so tool calls must carry the unique device number as a required input item. Without this number, the corresponding fault handling process cannot be accurately matched. Structured fields in industry technical standard documents are fixed, so plugin output format must strictly follow standard field naming to avoid call failures caused by parameter mismatches.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool call timeout duration | 300–600 seconds | Business data for power generation equipment manufacturing often involves cross-system data pulling, such as operation and maintenance logs and spare parts inventory data. A longer timeout duration can prevent call failures caused by delayed data pulling. |
toolChoice | auto | Business process guidance involves multiple types of tool calls, such as work order query and spare parts application. The automatic mode can automatically select the appropriate tool based on user input. |
| Required parameter validation | Enable device number and work order ID as required validation items | All business data for power generation equipment is tied to device or work order identifiers. Missing these identifiers will make it impossible to match the corresponding business data. |
| Plugin cache duration | 1–4 hours | Operation and maintenance logs are updated at the minute level, while BOM list changes occur less frequently. Setting the cache duration to 1–4 hours balances data timeliness and call performance. |
functionCall | Enable based on the business tool list | Include commonly used tools for business process guidance, such as work order query, spare parts application, and fault troubleshooting, in the callable range to ensure the model can call tools as needed. |
| Workflow nested call validation | Enable child workflow execution status callback | Avoid issues where the parent workflow cannot receive execution results after the child workflow completes, and matches the process linkage requirements of actual business operations. |
Three common configuration mistakes
- Symptom: After the parent workflow calls a child workflow, all nodes after the user-selected node in the child workflow do not execute. Cause: The child workflow's execution status callback configuration is not enabled, so the parent workflow cannot obtain the child workflow's execution progress and terminates subsequent linked processes.
- Symptom: When calling a built-in tool to obtain business data, an empty response is returned. Cause: Required parameter validation for tool calls is not configured, or the model did not correctly bind the tool's input and output formats, preventing the tool from normally pulling the corresponding data.
- Symptom: When calling a visual tool to process PNG format images, a 400-format error is returned. Cause: The allowed range for PNG format was not added in the tool configuration, or recent model interface updates added format validation rules, causing valid formats to be blocked.
How to confirm the configuration is correct
- In the test panel of FastGPT v4.17.0, manually trigger a tool call, enter complete required parameters such as device number and work order ID, and check whether the corresponding business data can be returned.
- After setting
toolChoicetoauto, enter a test statement that includes multiple types of business requirements, and check whether the model automatically selects the matching tool. - Trigger a workflow nested call, and check whether the parent workflow can correctly receive the execution results and continue subsequent processes after the child workflow completes.
- Call a visual tool to upload a PNG format image, and check whether the processing result can be returned normally without format errors.
All configuration values listed here are common starting points. They should be evaluated against the reader's own specific samples and use cases.
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.