What the data for this category looks like
Core data for power generation equipment manufacturing comes from equipment design drawings, operation and maintenance inspection logs, factory quality inspection reports, and bidding technical documents. The data update rhythm is adjusted according to the project phase: documents in the design phase are updated weekly, operation and maintenance logs are synchronized per shift, and quality inspection reports are produced with each product batch. The document structure includes fields such as equipment model, rated power, operating hours, fault code, and material grade. Units include kW, hours, MPa, tons, and others. The length of individual documents varies widely, ranging from several hundred-word inspection records to tens of thousands-word complete design plans.
What constraints these characteristics impose on the "tool calling and plugins" link
The data for power generation equipment manufacturing has wide span and significant format differences. This requires tool calling plugins to support dynamic adaptation to input documents of different lengths, to avoid calling failures caused by exceeding the single-segment length limit. Equipment parameters come with exclusive units and field naming rules. Plugins must include built-in field verification logic to ensure that the format and unit compliance of fields such as rated power and operating hours can be identified and verified during calls. The document structures of different data sources have obvious differences. Plugins must support switching parsing rules adapted to different scenarios such as design documents, operation and maintenance logs, and quality inspection reports. They must also be compatible with two calling modes: real-time pulling of operation and maintenance data and offline reading of archived documents.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
toolChoice | Set to auto, specify function for core parameter scenarios | Automatic mode adapts to general document drafting needs; specifying function mode forces tool calls to process structured equipment parameters |
| Function call timeout | 300–600 seconds | Adapts to the time required for parsing long documents and multi-field verification for power generation equipment |
| Field verification switch | Enabled | Ensures that the format and unit compliance of exclusive fields such as equipment model and rated power are verified during calls |
| Maximum single document block length | 800–1200 characters | Adapts to the wide span of individual documents from several hundred words to tens of thousands of words, avoiding call failures caused by exceeding single-block length limits |
functionCall | Calibrated based on actual measurements | Adapts to document structure differences across different projects, flexibly adjusting the parameter format for function calls |
| Result cache duration | 24 hours | Reuses tool call results for the same type of document drafting, reducing repeated resource consumption |
Three common mistakes
- Phenomenon: A cross-origin error is returned when using fetch to call the
api/v1/chat/completionsinterface, with a CORS-related prompt displayed. Cause: The allowed request sources and request headers are not configured on the backend, and preflight requests are not handled correctly. - Phenomenon: The model returns the "chat：llm—model—response-empty" error when the workflow is executed. Cause: Structured parameters are not passed correctly during tool calls, or data source fields are missing, preventing the model from generating valid responses.
- Phenomenon: The unit of the result fields returned by the tool call does not match, for example, rated power only shows a numerical value without a corresponding unit. Cause: The field verification switch is not enabled, or the verification rules do not cover the exclusive unit format for power generation equipment.
How to confirm the configuration is correct
- Initiate a tool call test targeting power generation equipment operation and maintenance logs, use the tool calling module of FastGPT v4.17.0, and check whether the interface can normally return parsed structured data.
- View the tool call log to confirm that the value of the
toolChoiceparameter matches the current scenario, with no abnormal error messages. - Manually input device parameters with exclusive units to verify whether the field verification switch can correctly identify compliant formats and block non-compliant inputs.
- Call the same type of document twice, confirm that the result cache takes effect as configured, with no duplicate tool call records.
The values provided here 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.