Case Ledger Summary and Report Generation for Urban Sanitation and Urban Management Law Enforcement: Workflow Orchestration

Case Ledger Summary and Report Generation for Urban Sanitation and Urban Management Law Enforcement: Workflow Orchestration

What Data for This Category Looks Like

Data for this category comes from urban management law enforcement platforms, urban operation grid platforms, video surveillance systems, and public complaint work orders. Data updates occur daily. Daily documents include inspection records, case filing approval forms, on-site photos, rectification orders, penalty decisions, and case closure reports. Core fields include case number, violation type, responsible entity, disposal progress, rectification results. Some data includes multimedia attachments.

Constraints on Workflow Orchestration

Workflow configurations must include multi-format data access nodes to handle multi-source heterogeneous data, adapting to text, images, and other case materials. Use scheduled trigger workflow nodes for daily updated batch case data to prevent omissions from manual triggers. The accuracy of core fields such as responsible entity and violation type directly impacts law enforcement compliance. Add a field verification link to the workflow to ensure all required fields are complete. Configure data association nodes to bind cases to on-site photos, automatically linking evidence materials to matching case ledgers. This configuration guide uses FastGPT v4.17.0.

Configuration Settings

Configuration ItemRecommended SettingRationale
Trigger ModeScheduled trigger at 2 AM daily, supports manual trigger for testingData update frequency is daily; scheduled triggers ensure daily ledger updates
variablesPre-set case number and disposal status as global variables, with a maximum length of 4000 tokensGlobal variables simplify multi-node calls; token limits adapt to large model context windows
nodeIdAssign a unique identifier to each tool node, configure nodeId in the order of inspection → filing → rectification → case closureEnsures tools execute sequentially according to case transfer logic, avoiding call confusion
Multi-source Data AccessPrioritize accessing structured law enforcement platform data, then supplement unstructured complaint work order contentStructured data accounts for a higher proportion of this category; prioritizing processing improves summary efficiency
Field VerificationBlock case data missing responsible entity or violation type, set timeout threshold to 600 secondsMissing fields affect report accuracy; timeout threshold ensures smooth data processing

Three Common Configuration Mistakes

  • Some tools fail to run during workflow execution, and execution order is disorganized. The root cause is failing to configure a unique nodeId for each tool node, or failing to set node execution order according to business logic.
  • Fixed prompt text appears at the end of generated content during workflow testing. The root cause is failing to turn off the default output suffix in the system prompt, or failing to clear the extra output configuration of the workflow.
  • Data appears blank after workflow runs, and the interface can be called normally. The root cause is failing to mount a persistent storage directory during deployment, and failing to retain workflow and knowledge base configurations after container restart.

How to Verify Correct Configuration

  • Manually trigger a workflow test, review execution logs for each tool node, and confirm nodes start and complete calls in the preset order.
  • Import a test case with complete core fields, run the workflow, and cross-check the generated ledger and report to confirm all core fields are correctly extracted.
  • Check the workflow trigger configuration, simulate scheduled triggering or new data submission, and confirm the workflow starts automatically.
  • View the system configuration page, confirm the persistent storage directory is properly mounted, to prevent configuration loss after deployment restart.

The values provided here 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.