What the documents look like
Short-video affiliate operations work from short-video scripts, affiliate product lists, commission plans and violation feedback. Compared with livestream selling, this category relies on long-term content exposure paired with product-link conversion, and real-time explanation is not a required step. Cross-border materials and multilingual retrieval therefore face two conditions at once: scripts and product titles often carry wording in several languages, while commission plans and violation feedback depend on exact identifiers and rule names. The supplied brief gives daily and weekly update frequencies; this page does not infer batch synchronization, full synchronization or transaction-triggered mechanisms from them.
The knowledge base treats the whole library as the smallest search unit, and collections serve only as classification management. Vector storage uses the PostgresSQL PG Vector extension, the index is HNSW, and the MongoDB dataset.datas table keeps the original data, where an indexes field records vector IDs; one data group can map to multiple vectors. Knowledge bases associated for retrieval must use the same vector model. That requirement is limited to knowledge base association and does not extend to external systems needing the same model. Semantic retrieval can match across languages, for example a Chinese question matching an English knowledge point, which corresponds to the cross-border script and product-list situation. Minimum relevance takes effect only under semantic retrieval or result reranking; it is a filter threshold and does not perform permission or entity isolation, and retrieval itself is not authorization.
Hypothetical drill sample: a content operator submits a pending handover request reading "include the Summer Affiliate Script - English Version in the cross-border materials library retrieval, for matching commission plan identifiers." Three source sentences for checking: first, "The Summer Affiliate Script - English Version was added to the library on 10 March 2025, with vector model identifier model-a." Second, "Commission Plan - Southeast Asia, identifier CP-2025-07, applicable period March to June 2025." Third, "This retrieval request is raised by the content operator and has not yet received written confirmation from the product distribution specialist." The request does not state authorization effective terms for the script or the commission plan; that field is not provided and remains unknown.
Constraints at the vector indexes step
The same-vector-model rule applies when associating knowledge bases for one retrieval. The supplied documents do not describe what happens when differently identified libraries are associated together, so the check is to compare identifiers and exclude non-matching libraries, then record the actual observation. A relevance score is not a category, entity or permission filter; raising or lowering minimum relevance does not exclude unauthorized commission plans. Retrieval returns candidate content and does not constitute authorization, approval or a database write.
Mixed retrieval combines semantic and full-text recall through RRF, and RRF is a fusion process for multiple result channels, not a toggle to be switched on. Reranking requires a rerank model and an enabled setting; image retrieval requires image input together with model capability and an index built at ingestion. The optional paths in the overall retrieval flow are not all executed on every request. The knowledge base search node outputs cited content as an array whose length can be zero, so the downstream link can proceed even when nothing is found. The citation limit is expressed in tokens rather than a top-k item count, and question optimization adds one model call before retrieval, which raises elapsed time.
Configuration and implementation checks
The table below follows the drill sample and lists documented settings or implementation checks. The values are starting points for this hypothetical trial and are not official defaults.
| Configuration item | Hypothetical starting point | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only the library whose vector model identifier is model-a | Compare character by character with the script source identifier; exclude libraries whose identifier differs and do not run a cross-model retrieval comparison |
| Search mode | Mixed retrieval | The script is natural language and the commission plan contains identifier CP-2025-07, so semantic and keyword matching are both needed |
| Question optimization | Set to enabled for this trial | Used to check short-question completion; compare cited source text against the same question set with the setting off |
| Minimum relevance | Trial starting value 0.35 | This value takes effect only under semantic retrieval or result reranking; compare with 0.5 and observe changes in the number of cited passages |
| Citation limit | Trial starting value 1200 tokens | Citation volume is controlled by tokens; compare with 800 tokens and observe whether key identifiers are truncated |
| Result reranking | Set to enabled for this trial | After mixed retrieval the candidate range is large; use rerank scores for filtering and compare ordering with the setting off |
Three common errors
- Treating minimum relevance as permission or entity filtering. Observable error: assuming that raising the value excludes unauthorized commission plans. Check: submit the same question set, compare cited source text before and after the threshold change, and observe whether unauthorized records are still recalled.
- Associating knowledge bases that use different vector models. Observable error: selecting the model-a library together with a library carrying another identifier and expecting normal retrieval. Check: first verify each library's vector model identifier, exclude those that do not match, and record the actual observation without inferring the runtime result of the combined association.
- Treating a retrieval result as executed authorization. Observable error: concluding from a retrieval hit that the script has received distribution specialist confirmation. Check: compare against the third source sentence, confirm the written confirmation field is absent, and record the status as pending verification.
How to verify the setup
- Verification one, against the first and second source sentences. Input: the script library identifier model-a and commission plan identifier CP-2025-07. Compare whether the vector model identifier of the associated library matches model-a. The condition is satisfied when the identifiers match, allowing the library into the retrieval scope; when they differ, exclude the library and record it. This check does not establish that the script is authorized for the commission plan, because the applicable-period field and the authorization effective terms are separate fields.
- Verification two, against the third source sentence. Input: the pending handover request. Compare whether a written confirmation field from the product distribution specialist exists in the materials. That field is not stated, so the judgment is unsupported and is not recorded as a denial or a conflict. The pending request remains pending and is not treated as approval.
- Verification three, against empty-result handling. Input: a paper-constructed empty citation array []. Compare whether the downstream design lets the output link proceed as documented. The condition is satisfied when the link can carry a zero-length citation; this does not assert that a fictional rule retrieval necessarily returns an empty array.
After any model or index adjustment, compare cited source text using the same question set, and do not promise results from vector scores alone.