What the data for this category looks like
Content review rule operation data comes from content review backends, user complaint records, public regulatory policies, and review sample libraries. Daily documents include review rule clauses, violation handling guidelines, appeal review records, and quality inspection reports. Data update frequency adjusts with policy changes or syncs quality inspection results daily. The document structure includes fields such as rule number, effective period, associated violation types, and corresponding handling actions. Supplementary data includes annotation samples, historical handling cases, and other supporting information.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Since data sources are scattered across multiple backends and database tables, use a designated retrieval collection to distinguish review-related data from other business content. Frequent updates require the retrieval pipeline to support regular vector database refreshes to avoid using expired rules. Documents include main rule clauses and auxiliary samples, so set retrieval priorities for the two types of content. Review scenarios have high requirements for result rigor, so restrict recall of low-match content to prevent irrelevant or incorrect rules from being used for judgments.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
collectionIds | Configure separately for review rule collections and sample library collections | Accurately limit the retrieval scope to avoid mixing in non-review irrelevant data |
similarity | 0.75–0.85 | Balance recall coverage and precision to meet the rigor requirements of review scenarios |
limit | Top 5–10 entries | Control the context length returned by retrieval to avoid exceeding model token limits |
usingReRank | Enabled | Perform secondary sorting on recall results to raise the priority of core rule clauses |
datasetSearchUsingExtensionQuery | Enabled | Optimize the semantic expression of queries to adapt to matching requirements for review-specific terminology |
searchMode | Semantic Retrieval | Adapt to unstructured text matching scenarios for review rules |
Three common misconfigurations
- Failing to specify
collectionIdscauses irrelevant content recall: The symptom is that non-rule documents are returned for review-related questions. Verification and troubleshooting step: Check whethercollectionIdshas been configured. - Failing to configure the
similaritythreshold causes irrelevant result triggers: The symptom is that knowledge base results are still returned when the query is unrelated to review rules. Verification and troubleshooting step: Check whether a minimum relevance limit forsimilarityhas been set. - Failing to enable
usingReRankcauses priority confusion: The symptom is that auxiliary explanatory content appears before rule clauses, reducing review judgment efficiency. Verification and troubleshooting step: Check whetherusingReRankhas been enabled.
How to confirm configurations are correct
- Check the FastGPT v4.17.0 service startup logs to confirm that
AIPROXY_API_ENDPOINT(the root address of the AI Proxy service, do not append paths such as /v1) andAIPROXY_API_TOKEN(a non-empty administrator token matching the AI Proxy server configuration) have been correctly configured, with no startup verification failure prompts. - Initiate a test retrieval, pass the specified
collectionIds, and verify that only content from the corresponding review-related knowledge base is recalled. - Adjust the
similarityparameter threshold, and verify that irrelevant content with low matching scores is no longer recalled. - After enabling
usingReRank, verify that core rule clause content is sorted before auxiliary explanatory content.
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.