What the documents look like
Cross-border return refurbishment and resale handles reverse logistics and item condition. This differs from first-leg replenishment in overseas warehouse restocking management. Store service and internal training answer operational questions from four document types: return inspection sheets, refurbishment records, scrap sheets, and resale listing sheets. Sources include overseas warehouse WMS, TikTok return center, Amazon return reports, and item inspection photos. Update frequency is daily or per batch.
Inspection photos and inspection sheets may be stored separately. Whether an image index exists depends on whether an image description index or image vector index was generated at ingestion time. Retrieval results differ accordingly.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Libraries with different vector models cannot be associated together. Check vector model identifiers first and exclude those that do not match. Do not run cross-model retrieval to compare missed recalls.
Retrieval searches the entire library. A collection is used only for classification management and does not affect search results. One retrieval combines semantic search, full-text search, hybrid search, image retrieval, question optimization, and reranking according to input content and search parameters. The final result passes through similarity filtering and citation limit trimming to produce cited content. Cited content is output as an array and its length can be 0. Even when nothing is found, this output path still completes.
Minimum relevance is a filtering threshold. It takes effect only in semantic search or when result reranking is used. It does not perform permission or entity isolation. Retrieval itself does not constitute authorization. Operational permissions, review status, and effective scope in store handover require separate verification.
Hypothetical drill sample: The source text for verification reads: "Return inspection sheet: subject is the overseas warehouse inspection team, object is batch B-0715 Bluetooth earphones, status is appearance scratches pending re-inspection, record date is July 15." "Refurbishment record: the same batch has completed housing replacement, refurbishment completion date is July 18, no resale approval recorded." "Resale listing sheet: batch B-0715 is included in the July 20 pending listing scope, authorization field is blank." The draft sentence to be judged is: "Batch B-0715 has completed refurbishment and been approved for resale." This draft sentence requires item-by-item comparison with the above source text on subject, batch, status, and authorization fields.
Configuration and implementation checks
| Configuration item | Relevant setting or check for this page | Relationship to the sample |
|---|---|---|
| Associated knowledge bases | Associate only return inspection, refurbishment record, scrap sheet, and resale listing libraries that use the same vector model | Check each library's vector model identifier first, exclude inconsistent ones |
| Search mode | Compare semantic, full-text, and hybrid search according to the test question | Batch number B-0715 is an exact identifier, suitable for full-text or hybrid search testing |
| Citation limit | Documented unit is token, controls single-retrieval cited content volume | This hypothetical trial starts at 600 tokens, because individual entries in the four document types are short; compare with 300 tokens for content completeness |
| Minimum relevance | Filtering threshold effective only in semantic search or when result reranking is used | This hypothetical trial starts at 0.3, compare with 0.5 for reduction of irrelevant fragments |
| Question optimization | Used for coreference resolution and question expansion, adds one model call before formal retrieval | Compare original question with optimized question, check whether batch subject was altered incorrectly |
| Result reranking | Requires a ReRank model and must be enabled per settings, outputs a 0-1 score | When no rerank model is configured, this path does not execute and the score is unavailable |
Three common errors
- Treating a retrieval hit as authorized execution. In the sample, the authorization field on the resale listing sheet is blank. Retrieving that sheet only shows the batch is included in the pending listing scope. It does not support the conclusion that resale has been approved. Check input is the draft sentence and the three source texts. Compare whether the authorization field has an explicit record. When the observed result is a blank authorization field, judge the statement as unsupported.
- Associating libraries with different vector models together. Check input is each knowledge base's vector model identifier. Compare whether identifiers match. When the observed result is mismatched identifiers, exclude that library and record it. Do not proceed with cross-model retrieval.
- Merging refurbishment completion and resale approval into one status. Check input is the refurbishment record and the resale listing sheet. Compare the values of the same batch on the refurbishment completion field and the authorization field. When the observed result is refurbishment completed and authorization field blank, judge the approval status as pending verification.
How to verify the setup
- Input the draft sentence "Batch B-0715 has completed refurbishment and been approved for resale" and the three source texts. Compare four fields: subject, batch, refurbishment completion status, and authorization field. When the observed result is a blank authorization field and no approval record, judge the sentence as unsupported and preserve the evidence gap.
- Input the question "B-0715 batch return inspection status" under the condition that only same-vector-model libraries are associated, and execute retrieval. Compare whether the returned cited content contains the inspection sheet source text. When the observed result is that cited content contains the field "appearance scratches pending re-inspection," the condition is met. If cited content length is 0, check whether data training is complete and record the empty result. Do not claim the rule necessarily returns an empty array.
- Input an image query containing inspection photos. Compare whether the current vector model supports image input and whether an image vector index was generated at ingestion time. When the observed result is that both are present, the image retrieval path can execute. When either is missing, record that this path did not execute. Do not infer that image-to-image search necessarily fails.