What this category of data looks like
Power generation equipment administrative consultation data has three main sources: factory technical documentation, on-site operation and maintenance logs, and component quality inspection records. Factory technical documentation is stored statically and updated quarterly with product iterations. Operation and maintenance logs are updated in real time with daily shift entries. Quality inspection records are updated per production batch. Documents are organized by component model, and include fields such as rated power (unit: megawatts), operating duration (unit: hours), and 4-digit fault code. Single documents can be up to 12,000 characters long. Some classified documents require permission verification.
What constraints these characteristics impose on workflow orchestration
The multi-source data characteristics of power generation equipment manufacturing create multiple constraints for workflow orchestration. Split calls for static and dynamic data. Configure independent data source nodes in the workflow to distinguish the two knowledge bases, avoiding mixed recall that causes context confusion. Limit the total character count of recalled documents per session, to prevent exceeding model context limits due to long individual documents. Fault codes use standardized 4-digit numeric values. The question classification node must support precise matching of these numeric codes, and should not rely solely on semantic similarity for judgment. Embed a permission verification step in the workflow for classified technical documents. Only eligible process branches may call the corresponding data.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | {"real_time_data": "daily_sync", "secret_level": "internal"} | Adapts to the daily synchronization requirement of operation and maintenance logs and permission classification for classified documents, and complies with FastGPT v4.17.0 variable configuration rules |
| Question classification node | Top 6 matching results | Power generation equipment fault codes are standardized. A small number of matches enables precise classification and reduces computational resource usage |
| Specified response component | Bind nodeId to the technical documentation node | Ensures returned content directly correlates to technical parameters of the corresponding component, and avoids irrelevant information interfering with consultation results |
| AI chat node temperature toggle | Disabled | Technical consultation requires precise parameter matching. Do not introduce randomness to ensure consistency of response content |
| Total recalled characters per session | 800–1200 characters | Adapts to the single-segment recall length of power generation equipment technical documentation, and prevents exceeding model context limits |
| Permission verification node | Triggered by user role | Differentiates document access permissions between internal operation and maintenance personnel and external consultation users, and ensures security of classified data |
Three Common Misconfigurations
- Phenomenon: The string returned by the specified response component starts with a line break. Cause: The component's automatic line break prefix is not disabled in the configuration. The default setting adds a line break before responses to separate context.
- Phenomenon: Inconsistent results are returned when the AI chat node temperature toggle is disabled versus when temperature is set to 0. Cause: The underlying logic of the two configurations differs. Disabling the temperature toggle enforces deterministic output, while setting temperature to 0 retains a tiny amount of randomness verification logic.
- Phenomenon: The processing duration of the question classification node exceeds 30 seconds. Cause: The total number of recalled documents is not limited. Semantic matching calculations for a large number of long documents consume excessive resources, leading to slow node performance.
How to Verify Proper Configuration
- Trigger a test consultation, check if the returned content has unnecessary leading line breaks, and adjust the automatic line break configuration of the specified response component to meet expectations.
- Test the AI chat node with the temperature toggle disabled and with temperature set to 0 separately, compare the returned technical parameter content to confirm the difference matches expectations.
- Check the workflow run logs to confirm the processing duration of the question classification node is within a reasonable range, with no obvious timeout alerts.
- Trigger the permission verification node, initiate consultations using test accounts with different roles, and confirm that only authorized accounts can access classified document content.
The configuration values listed above are common starting points. Adjust them based on your own specific samples and operational requirements.
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.