What This Category of Data Looks Like
Reference only; verify against the target FastGPT release and deployment documentation.
How These Characteristics Affect Workflow Orchestration
Data sources include multiple types of historical sessions and structured template libraries. Workflows must first configure classification nodes to match user questions to template tags. This prevents incorrect template calls across classifications. Data fields include applicable scenarios and effective dates. Add scenario verification nodes to workflows. These nodes filter expired or non-applicable response content. Data update frequencies are flexible. Configure workflows to support two data source update modes: manual refresh and scheduled synchronization. This maintains the real-time performance of the template library. Data is measured in entries and characters. Add content length limit nodes to workflows. This avoids overly long responses that reduce hotline response efficiency.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chat History Call Entries | First 6 entries | Matches the typical context length of hotline user consultations, avoids redundant information interfering with matching results |
| Data Source Refresh Cycle | Every 24 hours | Aligns with the daily update rhythm of template libraries, balances real-time performance and system resource consumption |
| Classification Matching Threshold | 0.75-0.85 | Calibrated based on the classification tag accuracy of the template library, reduces misclassification-induced template call errors |
variables Field Mapping | Map ticket ID, user question, standard response | Associates historical ticket data with current consultations, ensures accurate template matching |
nodeId Node Binding | Bind the ID of the preceding classification node | Ensures workflows call the template library under the correct classification based on classification results, prevents cross-category matching |
| Context Cache Duration | 300 seconds | Matches the typical interval between hotline users' secondary consultations, avoids multi-turn conversation failures caused by repeated context initialization |
Three Common Misconfigurations
- Phenomenon: When workflows process secondary consultations, they always use the template matched during the first consultation, and do not update classification results based on new questions. Cause: The workflow does not have a
variablescontext update node configured, and does not synchronize the latest user questions and classification tags. - Phenomenon: After setting the chat history call entries in the text content extraction plugin node, the expected historical session content is not returned. Cause: The plugin node is not bound to the correct
nodeIdcontext chain, so historical chat records cannot be retrieved. - Phenomenon: After manually triggering a data source refresh, the template content called by the workflow does not update. Cause: The trigger conditions for data source refresh are not configured correctly, so the workflow does not load the latest template library data.
How to Verify Correct Configuration
- Initiate a single-round consultation, verify that the response template returned by the workflow matches the current question's classification as expected.
- Launch three consecutive related consultations, verify that the workflow automatically updates classification results and matches the corresponding template.
- Manually trigger a data source refresh, verify that the template content called by the workflow matches the latest template library.
- Check workflow run logs, confirm that
variablescontext variables andnodeIdnode chains load normally.
The values provided here are common starting points. Test them against specific operational samples to determine appropriate settings.
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.