What this category of data looks like
Data sources for this category include urban management law enforcement platforms, urban operation grid platforms, video surveillance systems, and public complaint work orders. Daily generated documents include inspection records, case filing approval forms, on-site photos, rectification orders, penalty decisions, and case closure reports. Data updates occur daily. Fields cover case numbers, violation types, responsible entities, rectification statuses, disposal progress, and more. Some documents include multimedia attachments. The overall structure is built around the full lifecycle of a case, from discovery to closure.
Constraints on workflow orchestration from these characteristics
Dispersed data sources with multimedia attachments require workflows to support multi-source data pulling and format compatibility. Case processes involve multiple stages such as on-site evidence collection, responsibility determination, and rectification tracking. Workflows must be split by business nodes. High-frequency daily updates require workflow triggers to support real-time or scheduled pulling, to avoid data lag. Field differences across documents require configuring variables in workflows to adapt to field mappings for different data sources, ensuring accurate information flow. The rigor of law enforcement cases requires validation logic between workflow nodes, to prevent insufficient evidence or missing process steps.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables mapping configuration | Match by data source fields | Compensate for field differences across data sources such as inspection records and complaint work orders |
| Single question limit | 3 rounds | Adapt to multi-round communication needs for urban management law enforcement cases from consultation to rectification feedback |
| Context retention length | 800–1200 characters | Cover core case information and historical consultation records, avoid context overflow |
| Node timeout threshold | 600 seconds | Allow sufficient processing time for time-consuming stages such as on-site evidence collection and responsibility determination |
| Streaming call switch | Calibrate based on actual testing | Adapt to the calling characteristics of the Qwen3 model, ensure expected model behavior for workflow nodes |
| Node hiding configuration | Enable hiding for specified nodeId | Prevent unnecessary responses from mixing into final consultation replies, meet the rigor requirements of law enforcement responses |
Three common configuration mistakes
- Phenomenon: Responses from all AI dialogue nodes in the workflow appear in the final consultation reply. Cause: No hiding rule for the specified
nodeIdis configured, and output from all nodes is synced to the chat conversation link by default. - Phenomenon: The workflow only supports single questions and cannot trigger multi-round follow-up questions. Cause: No context retention parameter is set, or the context length configuration is insufficient to retain historical conversation information for subsequent follow-ups.
- Phenomenon: Timeout errors occur during node calls. Cause: The node timeout threshold is set too low, failing to adapt to the processing duration of time-consuming stages such as on-site evidence collection and responsibility determination.
How to verify correct configuration
- Trigger a test case workflow and initiate multi-round consultations, confirm that historical conversation information is retained and used for subsequent interactions.
- After configuring the hiding rule for the specified
nodeId, initiate a test and confirm that the output of this node does not appear in the final reply. - Adjust the node timeout threshold to 600 seconds, simulate calls for time-consuming stages, and confirm no timeout errors occur.
- Verify the
variablesmapping configuration, confirm that fields from different data sources have been correctly mapped to workflow nodes.
The values provided 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.