What data for this category looks like
Data sources for this category include work safety supervision systems, enterprise hazard self-inspection systems, law enforcement inspection records, and accident statistics systems. The update frequency is daily. Daily output documents include hazard inspection lists, hazard management ledgers, rectification notices, review records, and major hazard targeted supervision orders. Core fields cover hazard level, rectification deadline, responsible department, review result, and similar fields. Field units are mostly days, counts, items, and similar units.
Constraints imposed on workflow orchestration by these characteristics
Multi-source data requires unified formatting, so workflows must be configured with data cleaning nodes. The daily update frequency requires workflows to set a scheduled trigger mechanism, adapted to off-peak business hours for execution. The multi-field attributes of core documents require workflows to accurately map fields in variables to avoid data misalignment. The closed-loop process of hazard inspection, rectification, and review requires workflows to flow in node order, and configure a verification link to intercept non-compliant content. This prevents subsequent risks caused by data errors. At the same time, data update frequency is high, so workflow execution cycles must match data update cycles to avoid processing outdated data.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow trigger timing | 2:00 AM daily | Adapt to off-peak business hours, avoid occupying production system resources |
| Variable mapping rule | Map to variables according to hazard ledger fields | Unify multi-source data formats, ensure fields match business document requirements |
| Node ID configuration | Set nodeId according to business node naming specifications | Facilitate subsequent debugging and node location, improve workflow maintenance efficiency |
| Node timeout setting | 1200 seconds | Cover the processing duration of batch hazard inspection lists, avoid task interruption mid-execution |
| Result filtering rule | Only retain the last AI question and answer result | Adapt to the output requirements of multiple sets of AI question and answer, align with the habit of business personnel viewing the latest conclusions |
| Component custom parameters | Add exclusive fields to target nodes as needed, associate with variables | Adapt to business-specific requirements for hazard rectification information entry |
| Log retention duration | 30 days | Meet the basic requirements of internal audit and traceability |
| Failure retry count | 2 times | Balance the repair probability of temporary network failures and task execution efficiency |
Three common errors
- Multiple sets of AI question and answer nodes return all round response content after execution. The cause is that the result filtering link is not configured, and the output field of the last question and answer in
variablesis not specified for extraction. - The generated hazard rectification notice contains knowledge base reference markers. The cause is that the context reference option is not turned off in the document generation node.
- The code running node has no printed information after execution, and output cannot be viewed during separate debugging. The cause is that the node log collection switch is not turned on, and printed content is not stored in
variablesfor subsequent nodes to call.
How to confirm the configuration is complete
- Trigger a test workflow, check if the final output only contains the last AI question and answer content.
- Download the generated hazard rectification notice, confirm that there are no knowledge base reference markers in the document.
- View the execution log of the code running node, confirm that printed information is normally retained.
- Check the fields in
variables, confirm that they correspond one-to-one with the required fields of the hazard management ledger.
The values listed above are common starting points, and should be evaluated 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.