What data this category includes
The data for this category mainly comes from the random inspection and public disclosure supervision platform, enterprise credit information publicity system, law enforcement officer directory, and industry supervision system. Daily produced documents include inspection plans, inspection target lists, inspection item lists, on-site inspection records, rectification notices, and inspection result announcements. Document fields typically include inspection target identification, inspection item entries, law enforcement officer information, inspection time, rectification requirements, and other content. The data update frequency is monthly.
Constraints on workflow orchestration from these characteristics
The monthly updated data requires the workflow to be configured with regularly triggered data source synchronization logic, avoiding static, fixed inspection target and item data. The need to generate multiple document types requires splitting the workflow into corresponding nodes, handling plan generation, list matching, record filling, and announcement template filling separately. Multi-source data must bind interfaces from different systems through variables to ensure accurate field matching. Verification links for law enforcement officer matching and inspection target extraction must be embedded in the workflow to prevent non-compliant extraction or repeated disturbing of enterprises.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
variables scope | User-level | Adapt to the exclusive variable needs of different law enforcement officer IDs, avoid global variable conflicts |
Trigger node nodeId | Bound to monthly data synchronization node | Ensure subsequent document generation processes automatically trigger after data source updates |
| Knowledge base retrieval matching limit | Top 8 entries | Cover the common number of inspection item list entries, ensure retrieval coverage |
| Timeout threshold | 600 seconds | Adapt to the average time consumption of multi-data source synchronization and document template filling |
| Maximum character count per generation | 1000–1500 characters | Adapt to the standard length of rectification notices and inspection result announcements |
| Field mapping rules | Follow supervision platform standard fields | Match the fixed field formats of inspection target lists and law enforcement officer directories |
Three common configuration mistakes
- Phenomenon: Intermediate outputs from some AI dialogue nodes in the workflow are incorrectly included in the final generated document. Cause: Output hiding rules are not configured for specified nodes, causing unnecessary interactive content to be included in the final document.
- Phenomenon: When different law enforcement officers use the same workflow, variable values are globally overwritten, and exclusive law enforcement officer information cannot be obtained. Cause: The
variablesscope is not set to user-level, and the variable binding logic uses the global scope. - Phenomenon: Subsequent knowledge base retrieval nodes in the workflow cannot reference the configured datasetid variable. Cause: The datasetid parameter in
variablesis not correctly bound in the variable mapping of the retrieval node, causing the variable to fail to be passed.
How to verify correct configuration
- Trigger the monthly data synchronization node of the workflow, check whether the data source fields bound in
variablesare consistent with the standard fields of the supervision platform. - After configuring user-level variables, use different test user IDs to trigger the workflow, verify whether the variable values change with the user ID.
- Run the workflow, check whether unnecessary AI dialogue node outputs are hidden and do not appear in the final generated document.
- Verify that the knowledge base retrieval node can correctly call the bound datasetid variable and return matching inspection item-related content.
The values given 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.