What the documents look like
After-sales repairs and reships aim to restore a product to usable condition, and the case is not closed through a direct refund as in refund-only disputes. The working materials come from the after-sales system, the order system, repair sites, and the parts warehouse WMS. Day-to-day documents include repair requests, reship orders, inspection reports, and parts outbound orders. In cross-border work these materials commonly exist in Chinese, English, and other languages at the same time, and the search terms may not match the language of the stored material. The cross-language understanding of semantic retrieval therefore directly shapes what is recalled. The materials update per order and daily, and retrieval settings are checked against that rhythm. Batch synchronization and real-time triggering mechanisms are not derived from this page.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Knowledge bases built on different vector models cannot be associated together; the vector model identifier is checked first and non-matching bases are excluded. Semantic retrieval, full-text retrieval, and hybrid retrieval serve different situations. Precise queries such as part numbers and model numbers suit full-text or hybrid retrieval, while natural-language questions suit semantic or hybrid retrieval. The citation limit is measured in tokens. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used. Query optimization handles coreference resolution and query expansion and adds an extra model call before retrieval. RRF is the fusion process for mixed results and is not a switch that can be turned on. Retrieval is a recall step and does not perform authorization judgment; similarity settings do not exclude unrelated business lines or unauthorized records.
Hypothetical paper exercise sample: a brand after-sales parts warehouse receives a reship order whose source text reads: "Reship order number BF-2024-0317, item is electric toothbrush replacement heads, quantity 2, delivery address is Shenzhen, Guangdong Province, application date 17 March 2024, status pending review." A drafted sentence is submitted for judgment: "This reship order has completed outbound release and the parts have been dispatched." The source text records only the status pending review and records no outbound or dispatch entry.
Configuration and implementation checks
| Configuration item | Assumed starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only the after-sales material base that uses the same vector model | Check the vector model identifier of each base and exclude those with a different identifier |
| Search mode | Start with hybrid retrieval | Compare recalled content against semantic retrieval and full-text retrieval separately |
| Citation limit | Assumed starting point of 2000 tokens | Compare content completeness using reship orders and inspection reports of different lengths |
| Minimum relevance | Assumed starting point of 0.3 | Label relevant and irrelevant samples first, then compare the filtering effect |
| Query optimization | Enable for multi-turn follow-ups and short questions | Compare the original question with the optimized question and check whether the subject was altered |
| Result reranking | Enable when candidates are numerous | Compare ordering before and after reranking and confirm the model is configured |
Three common errors
- Treating a retrieval hit as an authorization to execute. When a reship order has status pending review, recalling that order does not mean outbound release has been authorized. Pending review is not approval.
- Forcing an association across vector models. Knowledge bases on different vector models cannot be associated together; the identifiers are checked and non-matching bases are excluded. A cross-model retrieval is not run to compare missed recalls.
- Treating RRF as a switch that can be turned on. RRF is the fusion process for hybrid retrieval results; no corresponding switch exists in the configuration, and such a control is not invented.
How to verify the setup
- Input the source text of the hypothetical sample together with the drafted sentence, and compare the source phrase "status pending review" with the drafted phrase "has completed outbound release." If the drafted sentence claims outbound release while the source text records none, the claim is unsupported and the evidence gap is recorded.
- Input the reship order number "BF-2024-0317" and compare the recalled content from full-text retrieval against semantic retrieval. If full-text retrieval returns that number and semantic retrieval does not, the observation indicates that precise number queries suit full-text or hybrid retrieval. A first-hit guarantee is not assumed.
- Input a query unrelated to after-sales work and observe the returned result. If the returned content is an empty array, check how the downstream design handles an empty citation. The exercise does not presuppose that a fabricated rule must return an empty result; only the actual observation is recorded.
These checks address the named primary task of retrieval and recall for cross-border multilingual after-sales repair and reship materials. Material identity, object, stage, date scope, and authorization boundary are fixed by the hypothetical sample above. The sample is a paper exercise and no test, deployment, approval, refund, or other business action is claimed to have occurred. Where a document field is not provided, the value remains unknown.