What this category of data looks like
Data for this category originates from the 12345 citizen hotline platform, contractor business systems, internal knowledge bases, public feedback and evaluation data, and local hotline management regulations. It is updated daily. Daily generated documents include request registration forms, dispatch records, handling responses, return visit records, delay applications, return explanations, and knowledge base entries. Core fields include request number, request type, responsible unit, processing node status, response content, and return visit evaluation results. There is no fixed unified statistical unit; data only flows through individual ticket instances.
What constraints these characteristics impose on workflow orchestration
The daily update requirement of the data means workflow configurations must include scheduled synchronization nodes, to ensure pulled dispatch and return visit data are the latest from the current day. Multiple types of business documents mean workflows need differentiated input and output rules configured per request processing node, to fit field requirements for stages including registration, dispatch, response, and return visit. The complexity of core processing links means workflows must include built-in branch judgment logic, covering request type identification, responsible unit matching, ticket return and re-dispatch, and abnormal flow paths for unsatisfactory return visit items. Multi-system data sources mean workflows must include cross-data source call nodes, to keep ticket information aligned in real time with contractor business systems.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | An array of objects containing request number, request type, and contractor unit fields | Pass core processing information for individual tickets to loop nodes |
| Timeout reminder threshold | 1200 seconds | Matches the standard response cycle for ticket handling, reserving sufficient processing time |
| Context length limit | 800–1200 characters | Adapts to the standard word count requirements for hotline response content |
| Branch trigger rule | Triggered by the request status field | Distinguishes between different ticket nodes such as pending dispatch, in progress, and responded |
nodeId | Unique identifier bound to the ticket return processing node | Accurately trigger re-dispatch flow processes for abnormal tickets |
| Knowledge base recall upper limit | Top 5 entries | Provides sufficient policy basis without redundant response content |
Three common mistakes
- The symptom is that after passing an array<string> type ticket array to a loop node, only some elements trigger AI conversations, while the remaining elements have no execution logs or empty fields. The cause is that the loop body does not correctly map the array index field in
variables, causing the node to fail to traverse all ticket data. - The symptom is that the workflow cannot be exported as a deployment file after configuration, and the interface prompts that node configuration is abnormal. The cause is that no unique
nodeIdis set for each business node, causing the system to fail to generate a valid deployment package. - The symptom is that AI-generated ticket responses do not combine historical tickets or local hotline management regulations, with vague content that does not meet actual processing requirements. The cause is that no knowledge base recall step is configured in the workflow, and policy entries are not passed to the AI conversation as context.
How to confirm correct configuration
- Manually trigger a test ticket, check whether the loop node traverses all incoming array elements, and verify that the fields of each element are loaded correctly.
- Simulate a timeout scenario, confirm whether the system triggers a reminder or abnormal branch after the set threshold.
- Call test tickets with different statuses, confirm whether the branch judgment node switches the correct flow path based on the request status.
- View the input parameters of the AI conversation, confirm that knowledge base entries or historical ticket data have been correctly passed to the context.
The values provided 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.