What data for this category looks like
Data for this category mainly comes from risk control systems, audit records, user behavior logs, and report evidence. Daily generated documents include ban records, appeal materials, review opinions, and user notifications. Common fields include account ID, violation type, ban duration, appeal submission time, review conclusion, and others. Data update frequency is mostly daily or real-time. Single data volume is moderate, with no complex nested structures. Core fields are mostly enumeration or text types, which facilitate structured storage and retrieval.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Dispersed data sources and frequent updates require the retrieval pipeline to support high-frequency incremental synchronization. This ensures that recalled ban records, appeal materials, and other content are the latest versions. Core fields include enumeration and text content such as account ID and violation type. Both structured field precise matching and full-text semantic retrieval must be supported to cover different retrieval needs. Single data is associated with multiple types of documents. Results need to be aggregated by account dimension after recall to avoid repeatedly pushing multiple redundant records for the same account. Semantic differences in unstructured appeal materials are large. The semantic matching logic for recall must be adjusted to ensure that relevance to appeal reasons and review opinions meets standards.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Matches appeal reasons and review opinions related to account bans. This interval filters low-relevance historical records, avoids mistakenly recalling irrelevant violation content, and is compatible with the semantic matching logic of FastGPT v4.17.0 |
limit | Top 8 entries | Recalls up to 8 associated records per request, covers the full process of account ban operations, and controls context length to not exceed the model input limit |
searchMode | hybrid | Combines structured field matching and full-text semantic retrieval, adapts to the retrieval needs of multiple types of data for this category, and balances accuracy and coverage |
usingReRank | Enabled | Reranks recalled results, prioritizes returning records with higher relevance to the current appeal reason and review conclusion, and improves response relevance |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands retrieval terms based on user appeal content, covering synonyms and synonymous expressions of violation types, and improves recall coverage |
collectionIds | Specify the collection ID of the exclusive knowledge base for ban appeals | Limits the retrieval scope to only datasets such as ban records and appeal materials exclusive to this category, avoiding mixing in irrelevant data from other categories |
Three Common Misconfigurations
- Symptom: Knowledge base search works correctly during debugging, but relevant ban records are not recalled during AI conversation. Cause:
datasetSearchUsingExtensionQueryis not configured, so synonymous retrieval terms for user appeal content cannot be covered, causing the model to fail to associate with the corresponding documents. - Symptom: Retrieval results include a large number of violation records unrelated to the current account. Cause:
collectionIdsis not set correctly, and the retrieval scope covers the entire platform knowledge base, mixing in irrelevant data from other accounts. - Symptom: Retrieved results have too low relevance, including a large number of irrelevant records not related to account bans. Cause: The
similaritythreshold is set too low, failing to filter low-relevance non-target documents.
How to Confirm Configuration is Correct
- Submit test account appeal content, and verify whether retrieved results include the account's ban records, appeal materials, and review opinions.
- Adjust the
similarityparameter, observe changes in the relevance of returned results, and confirm that the threshold can filter irrelevant content. - Check the number of retrieved results, confirm that they meet the
limitsetting requirements, and ensure no redundant cross-account records appear. - Verify that when
usingReRankis enabled, result sorting prioritizes matching the core request of the current appeal.
The values listed above are common starting points, and should be validated 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.