What this category's data looks like
This category supports internal office and employee service workflows for government public service entities including social insurance handling agencies and human resources and social security bureau business divisions. Data primarily comes from social insurance handling systems, personal rights and interests records, labor relations and work injury identification systems, and the electronic social security card platform. The update frequency is daily. Commonly processed documents include benefit application forms, payment period certificates, retirement approval forms, work injury identification materials, and unemployment insurance benefit application materials. Fields cover core business content such as insured person identity information, payment period, work injury grade, and unemployment registration status.
What constraints these characteristics impose on workflow orchestration
This category’s data sources span multiple independent business systems. Workflow orchestration must be configured with cross-system data pull nodes to ensure complete access to pension, work injury, and unemployment-related information. Daily updated data requires timed synchronization steps to be added to the workflow, to avoid using expired payment records or identification results. Diverse business document types require targeted field extraction rules, to match the fixed formats and field requirements of different materials. Incorrect benefit verification can lead to fund risks and public complaints. Workflows must include qualification verification and result review nodes to reduce the probability of incorrect or missed distributions.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Preset variables for insured person ID, payment period, work injury grade, and unemployment registration status based on business fields | Matches the core data fields required for benefit verification, and facilitates reuse across workflow nodes |
| Maximum context size | First 6 chat records | Covers the complete conversation chain for user inquiries, avoids loss of critical context, and supports multi-turn consultation scenarios |
| Single search limit | First 8 recall results | Balances query efficiency and information completeness, and meets the requirements of multi-dimensional verification for social insurance data |
| Timeout duration | 600 seconds | Reserves sufficient time for cross-system data pull and benefit calculation, to avoid mid-execution interruptions |
nodeId | Name nodes by their function, such as "qualification verification node" or "benefit calculation node" | Simplifies workflow debugging and rapid localization of abnormal nodes, improving operational efficiency |
Three common configuration mistakes
- Symptom: The workflow cannot handle subsequent conversations, and only responds to the first query. Cause: No context storage node is configured in the workflow, or
variablesare not bound to chat history fields. - Symptom: The text content extraction node returns empty results. Cause: No field extraction rules are configured for social insurance-specific documents, and the fixed formats of materials such as benefit application forms cannot be matched.
- Symptom: Workflow execution times out and interrupts. Cause: No reasonable timeout duration is set, and cross-system social insurance data pull exceeds the preset time limit.
How to confirm configurations are correct
- Trigger the first benefit verification-related inquiry, and check if the workflow correctly pulls the preset
variablesfield data. - Initiate 3 consecutive related inquiries, and confirm that the workflow can retain and call previous conversation context content.
- Simulate cross-system data pull operations, and verify that the timeout duration setting meets actual business execution requirements.
- View workflow operation logs, and confirm that each node executes in the preset order with no abnormal error messages.
The values provided are common starting points and should be evaluated against the reader's own operational 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.