What the documents look like
After-sales repairs and reships aim to restore a product to working condition, and cases close through completed repair or delivery of the replacement part. This differs from refund-only disputes, which close through a direct refund. The working document set for this category includes repair requests, reship orders, inspection reports, and parts outbound orders. These documents originate from the after-sales system, the order system, repair sites, and the parts warehouse WMS. The brief states an update frequency of per order and daily, so indexed content changes with document status and a one-time index build does not stay aligned with the source text.
Cross-border materials and multilingual retrieval mean the same batch of records can appear in different languages. Semantic retrieval offers cross-language understanding, for example a Chinese question matching an English knowledge point, and that capability has a direct role here. The vector model itself does not decide document status or authorization.
Constraints at the vector indexes step
Knowledge bases associated for retrieval must use the same vector model. When selecting more than one knowledge base, verify the model identifier and input type first, exclude those that do not match, and do not run cross-model retrieval to compare missed recalls. One source data block can be linked to multiple indexes, and index content is checked separately from source content. Indexes should be built from complete and focused information, and retrieval coverage against index length is weighed with samples. Whether image retrieval works depends on whether an image description index or image vector index was generated at ingestion, and on model capability at query time. Uploading an image on the query side does not fill a missing index on the ingestion side. After a model or index change, compare cited source text using the same question set, and do not promise an outcome from a vector score alone. Semantic recall and relevance scores do not perform permission or entity isolation, and a retrieval result is not the same as business authorization.
Hypothetical drill sample: the source material reads, "Reship order BS-2026-0417, item is a power adapter of a certain model, application date April 17, 2026, status awaiting confirmation by the parts warehouse, applicant notes the receiving address is outside the country." A draft sentence reads, "This reship order has been confirmed by the parts warehouse and outbound completion is done." The fact to be judged is whether parts warehouse confirmation and outbound completion hold.
Configuration and implementation checks
| Configuration item | Setting or check for this page | Relation to the sample |
|---|---|---|
| Associated knowledge bases | Select one or more knowledge bases with the same vector model | If sample materials sit in several libraries, verify the model identifier matches first |
| Search mode | Semantic retrieval, full-text retrieval, or hybrid retrieval | The reship order number is an exact query, so the full-text path can be checked |
| Index content | Build indexes from complete and focused information; check index and source separately | Check whether the reship order source and its index agree |
| Image index | Confirm whether an image description index or image vector index was generated at ingestion | The sample has no image input, so this item is recorded as not involved |
| Citation cap and minimum relevance | Citation cap is controlled by tokens; minimum relevance applies only in semantic retrieval or with reranking | This hypothetical trial start is a citation cap of 2000 tokens and minimum relevance of 0.4, chosen because the sample question is clear and candidates are few, compared against cited source text before and after adjustment for the same question set |
| Result reranking | With a rerank model available and enabled per settings, candidate text is reordered | The sample does not enable it, recorded as not configured |
Three common errors
- Treating a retrieval hit as an authorization state. In the sample the reship order status is awaiting confirmation by the parts warehouse. Retrieving that order only means the content was recalled. Parts warehouse confirmation and outbound completion still need a downstream system record or manual check, and the retrieval step does not produce that fact.
- Associating knowledge bases that use different vector models. If sample materials were ingested separately with different model identifiers, verify the identifiers first and exclude those that do not match, do not continue with cross-model retrieval, and do not infer missed recalls or redundant results from it.
- Treating a similarity score as an entity or permission filter. Minimum relevance is a filter threshold and does not distinguish applicant, receiving region, or authorization scope. The overseas receiving address in the sample is not automatically excluded or included by score level.
How to verify the setup
- Input the sample source material and the draft sentence, and compare "has been confirmed by the parts warehouse and outbound completion is done" in the draft against "status awaiting confirmation by the parts warehouse" in the source. The condition is met when retrieval recalls the reship order source and the check conclusion is recorded as pending verification, without judging the draft sentence as holding.
- Input the same question set and compare cited source text before and after adjusting the citation cap and minimum relevance. The condition is met when the cited content still contains the reship order number and the status field, and does not lose the fields needed for judgment because of parameter changes. If the citation is an empty array, carry the check into downstream design for empty results, and do not claim that an invented rule necessarily returns empty.
- Input a query that contains an image and compare the ingestion index record with query-side model capability. The condition is met when an image description index or image vector index was generated at ingestion and the model supports the corresponding input, so the image path participates in recall. If either condition is missing, record that path as not in effect, and do not infer image-search results.