What this category’s data entails
This category of data originates from defect management systems, test reports, code commit records, and user feedback. Update frequency follows a daily or per-version release cycle. Daily maintained documents include defect tickets, regression test checklists, repair verification records, and defect statistical reports. Each document includes standardized fields such as defect ID, associated version number, reproduction steps, priority, repair status, and verification result. The data structure is gradually updated with version iterations.
Constraints for Multi-turn Dialogue and Prompts
Data for this category flows through the defect lifecycle, with numerous structured fields and associated version information. Multi-turn dialogue must limit context scope to avoid interference from irrelevant data. Features updated per version require prompts to bind current version parameters, ensuring dialogue results match defect data for the corresponding version. Historical dialogue includes large volumes of defect ticket and regression checklist content, so the total length of messages must be controlled to prevent exceeding the model’s context threshold. variables must pass key fields such as version number and defect status, ensuring prompts can accurately match corresponding business data.
The following configurations are formulated for FastGPT v4.17.0.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
messages | First 20 conversation entries | Matches the single-processing volume of historical documents for this category, avoids context overload |
variables | Bind current version number and defect status fields | Accurately associates defect data for the corresponding version, aligns with business update rhythm |
chatId | Bind unique identifier of workflow conversation | Ensures multi-turn dialogue context association, prevents conversation breaks |
| Maximum context token count | 8000–12000 token | Adapts to the core data volume of single-turn dialogue for this category, calibrated via actual testing |
| Log storage toggle | Enable full conversation logging | Retains basis for exception troubleshooting, meets traceability requirements after business errors |
Three Common Misconfigurations
- Workflow dialogue displays failure while the model backend has response logs. The workflow node returns the "session verification failed" status code. This occurs when a valid
chatIdparameter is not included in the request, preventing context association. - Historical conversation content cannot be reused when calling a node. Each query returns entirely new results. This happens when historical
messagesare not bound to the input parameters of the current node. - No logs are available after application dialogue exceptions. The system does not generate corresponding error logs. This occurs when session log storage configuration is not enabled, making it impossible to trace the exception trigger path.
How to Verify Correct Configuration
- Initiate a test dialogue, enter a query containing a known defect ID, check if the returned result includes fields such as the corresponding defect’s version and status.
- Review workflow node configurations, confirm that the
chatIdparameter is bound to the session unique identifier to avoid context breaks. - Trigger an exception scenario, such as entering defect ticket content that does not meet formatting requirements, check if corresponding log entries are generated.
- Initiate two consecutive dialogues, check if the second query can reuse the context information from the first query and associate historical defect data.
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 2026-10-19.