What the Data for This Category Looks Like
The core data for this category comes from content platform content data, advertising revenue sharing systems, financial systems, and creator account backends. Daily processed documents include incentive rule documents, settlement detail tables, creator appeal records, and payment lists. Data update cycles are typically monthly or aligned with event cycles. Document fields include creator unique identifiers, settlement cycles, revenue sharing ratios, appeal statuses, payment amounts, and more. There is no unified fixed format, and it will adjust based on platform event rules.
Constraints on Re-ranking and Hybrid Retrieval
Data sources are scattered, so hybrid retrieval must support recall and integration of cross-system data to avoid fragmented search results. Document types include rule text, structured settlement details, appeal records, and payment lists. The re-ranking link must adapt to field weights across different document types, prioritizing matching fields related to revenue metrics. Data updates follow monthly or event cycles, so retrieval does not need strong real-time performance, but must use the latest data for the corresponding cycle. This scenario also requires accurate identification of abnormal fields, so search result sorting must prioritize content related to dispute points, reducing interference from invalid information.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
usingReRank | Enabled | This scenario requires filtering redundant search results. Re-ranking improves the sorting priority of revenue-related content, meeting the needs of precise Q&A for customer support and pre-sales. |
similarity | 0.72–0.85 | Adapts to field matching accuracy for settlement details and rule text. Avoids overly strict thresholds causing loss of valid results or overly loose thresholds introducing irrelevant data. Calibrated based on actual testing. |
limit | Top 10 entries | Controls the basic number of results returned per single retrieval. Combine with re-ranking to retain the top 5 entries for display, aligning with the reasonable upper limit for information presentation. |
searchMode | hybrid | Enables both vector recall and keyword retrieval, adapting to hybrid retrieval needs for multiple document types, and covering different retrieval logic for rule text and structured data. |
Three Common Misconfigurations
- Enabling the re-ranking model results in no online search results, but normal results in knowledge base testing. The cause is inconsistent
similaritythreshold configuration between online deployment and test environments, or the re-ranking model’s interface access permissions not being granted to online service nodes. - Re-ranking model configuration fails after offline deployment upgrade. The cause is failure to load the offline dependency package for the corresponding re-ranking model, or the configured model address being inaccessible in the offline environment.
- Re-ranking model test returns a request error. The cause is failure to configure reasonable request timeout parameters, or incorrect entry of interface authentication information in configuration items.
How to Confirm Successful Configuration
- Navigate to the backend configuration page in FastGPT v4.17.0, click the test button for the re-ranking model, and verify that normal sorted results are returned.
- Import settlement details and incentive rule documents for this category, initiate a retrieval with re-ranking enabled, and confirm that returned results include revenue-related content.
- Compare returned results from online retrieval and knowledge base testing to ensure consistent configuration parameters with no obvious differences.
- Check service logs to confirm no timeout or permission error messages for re-ranking model requests.
The values provided are common starting points and should be evaluated using local test 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.