What the data for this use case looks like
Data sources for creator onboarding and verification scenarios mainly include creator backends, enterprise credit information platforms, account history systems, and contract management systems. Daily processed documents include onboarding application forms, identity qualification scans, verification audit records, cooperation agreement texts, and more. Data updates are primarily triggered by individual applications; some public qualification data is synchronized daily. Data fields include applicant account identifiers, qualification file identifiers, audit statuses, cooperation periods, and additional items. These include both structured fields such as audit numbers and credit codes, and unstructured text such as application descriptions and qualification explanations.
Constraints on reranking and hybrid retrieval
The multi-source, heterogeneous data structure requires hybrid retrieval to support both structured field matching and unstructured text recall. This prevents missed qualification material checks that occur when relying solely on a single retrieval method. The real-time nature of data updates requires the retrieval pipeline to support dynamic loading of the latest audit records and qualification files. Static cached datasets cannot be used. The volume of associated data per individual application is limited. The total number of recall results must be controlled to avoid information overload for audit staff. Additionally, the potential consequences of fraudulent verification require the reranking step to prioritize recalling high-risk audit statuses, abnormal qualifications, and other critical data. This ensures the highest priority is given to core audit evidence.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Used to match core associated fields between qualification materials and audit records, filtering low-relevance historical account data |
limit | Top 10 entries | Controls the total number of recall results per single retrieval, matching the volume of associated data for individual onboarding applications |
searchMode | hybrid | Enables hybrid retrieval mode, matching both structured fields such as enterprise credit codes and unstructured text such as application descriptions |
usingReRank | Enabled | Performs reranking on multi-source recall results, prioritizing recall of core data such as high-priority audit statuses and abnormal qualifications |
Three common misconfigurations
- Symptom: The interface shows the rerank status as false, and retrieval results are not sorted by audit priority. Troubleshooting: The
usingReRankparameter is not configured correctly, or the service startup verification failed because the required environment variablesAIPROXY_API_ENDPOINTandAIPROXY_API_TOKENfor the App/Admin server are not configured. - Symptom: Multi-source recall results cannot match the corresponding creator's qualification materials. Troubleshooting: The creator account ID is not bound as an associated field in the hybrid retrieval configuration, causing cross-data source matching to fail.
- Symptom: The reranking function fails to start after deployment on an arm architecture. Troubleshooting: An amd architecture reranking model image was used, and the deployment package adapted for arm architecture was not selected.
How to confirm proper configuration
- Verify that the App/Admin server environment variables
AIPROXY_API_ENDPOINT(AI Proxy service root address) andAIPROXY_API_TOKEN(AI Proxy administrator Token) are correctly configured, have no empty values, and meet the requirements of FastGPT v4.17.0 and later versions. - Submit a retrieval request for a test onboarding application, and check whether the recall results are sorted according to audit priority, such as audit records taking precedence over regular application text.
- Validate the matching logic across multiple data sources, confirming that both structured fields such as enterprise credit codes and unstructured text can be correctly recalled.
- Review the service startup logs to confirm there are no startup errors or parameter validation failure prompts for the reranking module.
The values provided 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.