What the documents look like
Semi-managed sellers on Temu maintain overseas inventory and ship orders themselves, rather than only supplying goods to the platform. That difference shapes the material a retrieval setup has to serve. The working corpus for this page is the product declaration form, the overseas inventory table, the price declaration, and the platform fulfillment order. These materials sit close to whether a listing can be sold and whether a shipment runs late, so a retrieval result that points at the wrong record or the wrong status sends the operator's judgment onto the wrong document.
The brief marks update frequency as daily and per-order, with the confidence level noted as roughly accurate. Update frequency does not change how the retrieval feature itself is configured on this page, so it is mentioned only as given and no batch, full-sync, real-time, or transaction-triggered mechanism is inferred from it. The documents differ in shape: declaration and price records carry status fields and effective ranges, inventory records carry location and in-transit states, and fulfillment orders carry per-order identifiers and times. A retrieval question can arrive in one language while the stored passage sits in another, which is why semantic retrieval is relevant here.
Constraints at the retrieval step
The knowledge base search node can be added repeatedly, has external input, has static configuration, and triggers execution. Its knowledge base input accepts one or more knowledge bases that use the same vector model. Its reference output is an array whose length can be zero, so the output path runs through even when nothing is found.
Search mode matters for this corpus. Semantic retrieval compares vector distance and supports cross-language matching, so a Chinese question can reach an English passage. Full-text retrieval suits identifiers, model numbers, proper nouns, and error codes. Hybrid retrieval uses vector and full-text recall together and merges them through RRF, which is a fusion step in the retrieval process rather than a switch to turn on. Rerank performs a second ordering pass and returns a score from 0 to 1; it depends on the question being reasonably complete, and the documented flow usually applies question optimization before search and rerank.
The minimum relevance value is a 0-1 threshold that applies only under semantic retrieval or when result reranking is used. It filters low-relevance results and is not the final ordering rule. The reference limit is measured in tokens, not top-k items, because chunk lengths vary widely in mixed knowledge bases. Question optimization performs coreference resolution and question expansion before retrieval and adds one model call, which usually helps multi-turn retrieval and adds latency.
Retrieval and similarity scores carry no permission or entity isolation. A hit is not an authorization. The same-vector-model requirement applies to the knowledge bases associated with the search node; it does not extend to any external system such as a business registry.
Hypothetical paper exercise sample. An operator is checking a draft product declaration. The source text reads: "Subject: Xingyu Trading (hypothetical name); object: folding storage rack; declaration status is pending review; effective scope: March 2026 batch." The overseas inventory table for the same batch records the batch as "in transit." The sentence to be judged reads: "This batch of folding storage racks has completed declaration and can be listed for sale." The sentence disagrees with the source on declaration status, and the conditions needed for listing are not stated in the source.
Configuration and implementation checks
| Configuration item | Hypothetical trial starting point | Reason and comparison object |
|---|---|---|
| Associated knowledge bases | Only declaration and inventory bases sharing one vector model | Check the vector model identifier first, exclude bases with a different model |
| Search mode | Hybrid retrieval | Compare against semantic-only and full-text-only results |
| Reference limit | Hypothetical starting point of 2000 tokens | Compare completeness across declaration passages of different lengths |
| Minimum relevance | Hypothetical starting point of 0.4 | Label relevant and irrelevant samples first, then compare |
| Question optimization | Enabled | Compare against the unoptimized question for subject distortion |
| Result rerank | Enabled | Compare candidate ordering against the unranked order |
These values are hypothetical trial starting points for this exercise, not official defaults.
Each row is either a documented setting or a named implementation check. The vector model identifier is a documented constraint on the knowledge base input. Search mode, reference limit, minimum relevance, question optimization, and result rerank are documented parameters. The comparison objects are checks the operator performs, not automatic behaviors.
Three common errors
- Reading "pending review" as a completed declaration. Input is the source text above and the draft sentence. Compare the declaration status field. The observable result is whether the draft sentence matches the source value; here it does not.
- Treating a retrieval hit as authorization. Input is the inventory passage recording the batch as "in transit." Compare the retrieval output against the authorization field. The observable result is whether an authorization conclusion appears where the source states none.
- Associating knowledge bases that use different vector models. Input is the model identifiers of the two bases. Compare whether the identifiers match. The observable result is exclusion of the non-matching base with the observation recorded; no cross-model retrieval is executed to compare recall.
How to verify the setup
- Input the declaration source text and the draft sentence. Compare the declaration status field. If the draft sentence and the source take different values on the same field for the same subject and period, the sentence is unsupported. A pending status does not by itself show a lack of operating permission.
- Input the inventory passage recording the batch as "in transit." Compare the retrieval output against the authorization field. If the output states no authorization, the matter stays pending verification. The retrieval result does not confer permission.
- Input the identifiers of two knowledge bases using different vector models. Compare the identifiers. If they differ, exclude the non-matching base and record the observation. For the empty-reference path, check the downstream design against the explicit paper input
[]; this page does not claim that a rule query must return[].
Each check states the input, the comparison, and the observable result. None of these checks has been run; they describe expected observations. Where the source is silent, the gap stays open rather than being filled with a constructed authorization or effective clause.