What the Data for This Category Looks Like
Data for this category originates from call transcripts of government service hotlines and state-owned enterprise service hotlines, as well as ticket body and title fields submitted offline. Data updates trigger in real time, with one entry generated each time a user places a call or submits a ticket. A single entry includes four core fields: appeal text, ticket number, submission time, and initial classification tag (null value). The length of the appeal text ranges from 100 to 5000 characters. All other fields are stored in string or number format. FastGPT v4.17.0 supports the standard access format for this type of data.
What Constraints These Characteristics Impose on the "Workflow Orchestration" Link
The wide range of appeal text lengths requires workflows to support dynamic adaptation to input text of varying lengths, to avoid truncation that causes classification failure. Real-time updated data sources require workflow nodes to set appropriate trigger timing to match the callback interface for ticket submission. The multi-field input structure requires workflows to explicitly extract specified fields as input for the classification model, to avoid mixing irrelevant fields that interfere with classification results. The initially empty classification tag field requires workflows to automatically write classification results upon completion, without requiring additional manual intervention steps.
How to Configure
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Timing | Bind to the Webhook callback for ticket submission | Matches the real-time updated data source characteristics, ensures classification trigger is synchronized with ticket generation |
| Input Field Extraction | Extract the appeal text field from variables | Focuses on core classification basis, excludes irrelevant fields that interfere with classification results |
| Classification Call Node | Call the built-in ticket classification node, process 1 entry at a time | Adapts to the processing logic of single ticket data, avoids resource overload |
| Result Writing Field | Write the classification tag field from variables | Matches the initially empty classification tag field, automatically completes result backfill |
| Timeout Threshold | 300 seconds | Adapts to the response time requirements of hotline tickets, avoids long-term blocking of the workflow |
| Classification Confidence Threshold | 0.7–0.9 | Calibrated based on actual testing, balances classification precision and recall rate |
Three Common Mistakes
- Phenomenon: After calling an externally configured application, the target application does not record conversation logs. Cause: The workflow node did not enable the log retention switch, and did not pass the conversation context in
variablesto the target application. - Phenomenon: After passing global variables via a URL share link, the corresponding parameter value is not obtained in the workflow. Cause: Did not splice parameters in the link according to the required format, or did not enable the URL parameter receiving configuration in the workflow node.
- Phenomenon: After calling a custom Python code node, no ticket classification result is generated. Cause: The code function did not return the required classification tag format, causing the workflow to fail to parse the output result.
How to Confirm Proper Configuration
- Submit a test ticket, view the workflow run logs, confirm that the trigger node executes normally.
- Check the fields stored in
variables, confirm that the appeal text content of the test ticket has been correctly extracted. - View the classification result field, confirm that a label compliant with business classification rules has been generated.
- Verify the return data of the external call node, confirm that it has been correctly written to the specified field.
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.