What This Category of Data Entails
Data for this category originates from cloud database consoles, slow logs, monitoring metrics, and ticket systems. Daily produced documents include instance change orders, backup and recovery records, performance diagnosis reports, and parameter adjustment logs. Data updates run daily or after each instance change. Fields include instance ID, change time, backup size (unit: MB), slow SQL latency (unit: milliseconds), ticket status, and multi-tenant permission isolation tags. These tags separate database resources belonging to different customers.
Constraints for Re-ranking and Hybrid Retrieval
This category of data includes two types: structured monitoring metrics and unstructured ticket text. Hybrid retrieval must support both semantic matching and numeric filtering. Multi-tenant permission tags require tenant-level filtering during retrieval to prevent cross-tenant data leaks. Data updates trigger when instances change. The re-ranking step must prioritize sorting the latest change records and performance reports. This ensures timeliness for pre-sales and support scenarios. Business identifiers in fields (such as instance ID, slow SQL latency) can serve as auxiliary weight references for re-ranking. Sorting logic must be adjusted alongside semantic matching results. This avoids mixing irrelevant instance data caused by relying solely on text similarity.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
usingReRank | Enabled | Text data such as tickets and change orders for this category requires precise semantic matching. Re-ranking filters low-relevance initial recall results |
limit | Top 8 entries | Core documents for this category (such as slow SQL reports, backup records) have concentrated volumes. Excessive entries increase context processing overhead |
similarity | 0.72–0.80 | Fields for this category include business identifiers (such as instance ID). Low-match irrelevant instance data must be filtered. This range is a reasonable range calibrated through testing |
searchMode | Hybrid Retrieval | Data for this category includes structured monitoring metrics and unstructured ticket text. Hybrid retrieval balances semantic matching and numeric filtering |
| Re-ranker Model Selection | Use a model from the same vendor as the embedding model, such as Qwen/Qwen3-Reranker-7B | Models from the same vendor have higher semantic alignment, avoiding loading failures caused by cross-model compatibility issues |
Three Common Misconfigurations
- Symptom: Re-ranker model fails to start after configuration, and the console returns a model loading failure prompt. Cause: A re-ranker model compliant with platform specifications was not configured, or the model name was entered incorrectly, preventing matching.
- Symptom: Re-ranking result fields show false during the question answering workflow. Cause: The
usingReRankconfiguration item was not enabled, or the number of initial recall results did not meet the minimum threshold for triggering re-ranking. - Symptom: Existing configurations are overwritten after adding a re-ranker model with the same name. Cause: The platform uses model names as unique identifiers. Custom aliases were not used to distinguish model configurations for different scenarios.
How to Verify Successful Configuration
- Navigate to the model management page in FastGPT v4.17.0, and check if the re-ranker model status displays "Loaded".
- Submit a test query for database slow SQL troubleshooting, and check if the re-ranking score field is included in the retrieval result list.
- Adjust the
similarityparameter value, and verify if the matching degree of retrieval results changes along with the parameter. - Submit a test request that includes a tenant identifier, and confirm that retrieval results only return database-related documents for the current tenant.
The values provided here 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.