What the documents look like
After-sales repairs and reships aim to restore a product to working condition. The case does not close through a direct refund, which distinguishes this category from refund-only disputes. This page covers one task inside that category: inventory procurement and supplier records. The retrieval objects are repair requests, reship orders, inspection reports and accessory outbound notes. The main data sources are the after-sales system, the order system, repair sites and the accessory warehouse WMS. Records update per order and daily. Those cadences describe how records arrive; they do not imply batch synchronization, real-time triggers or transaction-linked automation. Errors in this area can produce repeated complaints, overdue repairs and uncontrolled accessory cost, so retrieved reference content and authorization status require separate checks.
For procurement work, the practical consequence is that a retrieved document tells the reader what a record contains. It does not tell the reader whether a warehouse has approved a reship, whether an accessory has left stock, or whether a supplier quotation is currently binding. Those facts live in the source systems and in the state fields of the individual documents.
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 operator checks the model identifier first and excludes non-matching bases. A cross-model retrieval is not run in order to compare missed recalls.
The output of the node is reference content in array format, and its length can be zero. When no content is found, the downstream branch still executes. Search modes are semantic retrieval, full-text retrieval and hybrid retrieval. Hybrid retrieval merges multiple result paths through RRF; RRF is a fusion process, not a switch that can be turned on. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used. It is a filter threshold, not a sorting rule, and it does not perform permission or entity isolation. The reference cap is measured in tokens. Question optimization performs coreference resolution and question expansion. Image retrieval requires an image input and the corresponding model capability. Reranking requires a rerank model and must be enabled according to the configuration. Retrieval and recall do not constitute authorization, and a pending review status does not demonstrate that an operator lacks permission to act.
Hypothetical paper test case: a brand after-sales site submits an accessory reship order on the hypothetical date 10 March 2025. The hypothetical order number is BX-2025-0310-07. The subject is a brand after-sales site, the object is a door lock accessory of a given model, and the status is pending accessory warehouse review. The same batch contains an inspection report whose conclusion states that the accessory is damaged and a reship is recommended. A draft sentence under review reads: "The reship order has been approved by the accessory warehouse and can be released from stock." The source material contains no approval field and shows only the pending accessory warehouse review status. The draft sentence is therefore unsupported.
Configuration and implementation checks
The table below lists only settings documented in the official material or implementation checks relevant to this page's main task. The values are starting points for this hypothetical trial and are not official defaults.
| Configuration item | Hypothetical trial starting point | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only knowledge bases using the same vector model | Check the vector model identifier first, exclude bases on different models, and do not run cross-model retrieval |
| Search mode | Hybrid retrieval | Compare retrieved content against semantic retrieval and full-text retrieval on the same hypothetical question |
| Reference cap | Hypothetical starting point of 800 tokens | Test content completeness with accessory outbound notes of different lengths, compared against 600 and 1000 |
| Minimum relevance | Hypothetical starting point of 0.35 | Label relevant and irrelevant samples first, then compare filtering only under semantic retrieval or reranking |
| Question optimization | Enabled | Compare the original question with the optimized question and check whether the subject was altered |
| Result reranking | Enabled according to configuration | Confirm a rerank model is available, then compare reranked scores against the unranked order |
Three common errors
- Treating a retrieval hit as an authorization approval. Input: the draft sentence and the hypothetical reship order source text. Comparison: the source status field against the draft wording. The source carries only the pending accessory warehouse review status and no approval field, so the observable result is that the draft sentence is unsupported.
- Treating the minimum relevance value as a permission or entity filter. Input: the same hypothetical question run against records belonging to different subjects. Comparison: reference content before and after filtering. The observable result is that relevance affects filtering only and does not exclude unauthorized records.
- Treating RRF as a switch that can be enabled. Input: the hybrid retrieval description in the documentation. Comparison: the documented description against the configuration interface. The observable result is that RRF is a fusion process with no separate switch.
How to verify the setup
- Input the hypothetical reship order source text and the draft sentence "The reship order has been approved by the accessory warehouse and can be released from stock." Compare the source status field with the draft wording. If the source states only pending accessory warehouse review, the draft sentence is unsupported and the evidence gap is recorded.
- Input a hypothetical retrieval question and the identifiers of the associated knowledge bases. Compare the vector model of each base. If a base uses a different vector model, exclude it and record the actual observation. Do not run a cross-model retrieval.
- Input a hypothetical empty-result downstream scenario, using the explicit paper input [] to check the downstream design. Compare whether the output reference array length is zero. If the downstream branch still executes, the behavior matches the documented empty-reference output condition.
These checks describe expected observations on paper. They do not report a completed test, a deployment, an approval or any other business action.