What the data for this category looks like
Data sources for this category include regulatory and rule databases, higher-level law databases, departmental policy document repositories, and administrative normative document filing systems. Update frequency is irregular. Daily processed documents include normative document drafts, drafting explanatory notes, legality review opinions, solicited opinion summaries, and filing reports. Core fields include document number, drafting unit, review opinion items, filing number, volume of collected solicited opinions, and others. The length of individual documents varies widely.
What constraints these characteristics impose on the "workflow orchestration" link
Dispersed data sources and irregular update cycles require workflows to support dynamic access to multi-source heterogeneous data, avoiding hard-coded fixed data sources. Diverse document structures and wide length spans require configurable adaptive node splitting rules, preventing single processing from exceeding model context limits. The review process requires comparing reference materials item by item and consolidating opinions from multiple parties. Workflows must support cyclic execution of nodes for item-by-item processing, while recording each review result for ledger summarization. Full data traceability is required for filing, so workflow nodes must support automatic writing to specified fields in the filing system.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Batch execution node cycle interval | 10–30 seconds | Aligns with the time required to review a single normative document clause, avoiding interface rate limit triggers |
variables binding configuration | Bind to the output of the current cycle node | Ensures that reference files and review items called by the large model match the currently processed item |
| Workflow call timeout | 600 seconds | Covers the complete processing flow of multi-round higher-level law comparison and opinion consolidation |
| Automatic log writing trigger condition | Upon node execution completion | Automatically records each review result for ledger generation |
| Node retry count | 2 times | Addresses temporary interface fluctuations, reducing the probability of process interruption |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Misconfigurations
- The symptom is that the full process completes during online debugging, but batch execution nodes do not finish executing during API calls. The cause is that the cycle interval timeout parameter is not configured for API calls, causing the main process to terminate early.
- The symptom is that after modifying the prompt of the AI chat node to use variable references, the temperature setting button disappears, and generation parameters cannot be adjusted. The cause is that the model parameter configuration panel is hidden by default in variable reference mode. Custom generation parameters must be passed via
variablesbinding. - The symptom is that after calling the workflow via API, the running data field in the conversation log is empty. The cause is that the workflow's automatic log storage configuration is not enabled, or node outputs are not bound to return variables.
How to Confirm Proper Configuration
- Trigger a single test of the workflow, and verify that the cycle count of the batch execution node matches the number of normative document items to be reviewed.
- View node logs to confirm that the parameters bound via
variablesmatch the currently processed review items. - Check the ledger data output by the workflow to confirm that all record fields from the review links are included.
- Call the API to trigger the workflow, and verify that the returned results match the output from online debugging.
The values provided 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.