What this category of data looks like
This category of data originates from enterprise ITSM systems, phone or online chat logs, internal asset systems, and official knowledge bases. Update cycles follow daily or real-time schedules. Daily generated documents include service request forms, incident tickets, processing records, and user satisfaction surveys. Fields cover ticket unique identifiers, submission time, handlers, problem categories, response duration, user ratings, and more. The data structure is relatively standardized, with few custom non-standard fields.
How these characteristics impact citation source and traceability
Data sources are scattered, and update cycles vary. Real-time chat logs and daily-updated ticket data require different index refresh frequencies. This prevents expired data from being used during traceability. Document fields are relatively fixed but cover multiple systems. Citation traceability must link cross-system unique identifiers such as ticket IDs and handlers. Without these links, original ticket entries cannot be accurately matched. There are significant differences in document length. Short chat logs and long processing reports need to adapt to different content length limits. This prevents loss of key context information during traceability.
This document is compatible with FastGPT v4.17.0.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Matches the average content length of IT service desk tickets, ensuring complete context is included during traceability |
| Single recall limit | Top 5 entries | Covers multiple types of documents associated with a single ticket, avoiding missing key processing records |
responseData | Return ticket ID, submission time, handler fields | Focuses on unique identifier fields required for cross-system traceability, simplifying downstream matching logic |
detail | Enabled | Allows returning the full content of original documents, facilitating troubleshooting process verification for test cases |
| Reranking switch | Calibrated based on actual testing | Optimizes recall order for long chat logs, improving traceability accuracy |
| Context cache duration | 24 hours | Matches the update cycle of daily updated tickets, avoiding use of expired data during traceability |
Three common misconfigurations
- Only citation identifiers are returned without specific content. The conversation interface only displays ticket ID links, with no details of original processing records. This occurs when the
detailparameter is not enabled or is set to disabled. - Retrieval results do not match the target ticket. Retrieved documents are associated with incorrect ticket IDs. This happens when the
responseDataconfiguration does not include unique identifier fields, leading to failed traceability matching. - Errors occur during workflow calls. After processing an HTTP request, the AI dialogue step returns a parameter error. This is caused by the field format returned by
responseDatanot meeting FastGPT’s required input specifications.
How to verify correct configuration
- Submit a simulated IT service desk ticket to trigger the retrieval and traceability process. Check that returned citations include the correct unique ticket identifier.
- Review the content length of retrieval results. Confirm that the
quoteMaxTokenvalue covers the core context of the target document. - Inspect parameter passing in the workflow. Confirm that fields returned by
responseDatameet the input requirements of the downstream AI dialogue step. - Trigger retrieval using documents with different update frequencies. Confirm that traceability results match the latest status of the documents.
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 2026-10-19.