What the documents look like
Brand after-sales repair service centers on warranty responsibility and physical repair outlets, which separates it from e-commerce platform after-sales work that mainly processes refunds. The daily materials are warranty cards, repair work orders, inspection reports and exchange approvals. These materials come from the after-sales system, store orders and repair outlet feedback. The public brief records an update frequency of per order or daily, and that frequency does not change the retrieval behavior described on this page.
The materials differ in state. A warranty card carries a validity range. A repair work order carries a stage status. An inspection report carries a conclusion field. An exchange approval carries an authorization boundary. Staff training and store service need customer service agents and outlet staff to find the same explanations for warranty scope, spare-part coordination and exchange or return approval in one knowledge base. The retrieval step only returns relevant fragments. It does not decide whether those states hold.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. The output is an array of references, and its length can be zero, which means the output path still runs when nothing is found. Search modes are semantic search, full-text search and hybrid search; hybrid search merges results through RRF, and result reranking uses a ReRank model. The minimum relevance value is a filter threshold that takes effect only in semantic search or when result reranking is used. The reference limit is measured in tokens. When question optimization is enabled by configuration, it performs coreference resolution and question expansion and adds one model call before retrieval. Image retrieval requires image input and matching model capability. Reranking requires a model and must be enabled by configuration. Knowledge bases that use different vector models cannot be associated together; check the vector model identifier first and exclude those that do not match.
Hypothetical drill sample: the source text of an internal training material from a brand after-sales center reads: "Warranty card number BX-2024-0317, product model A2, purchase date March 10, 2024, warranty period twelve months, covering mainboard failure. Repair work order WX-2024-0912 has status pending inspection, the store has received the item, and no inspection report has been issued." A draft sentence to be judged reads: "This warranty card already covers the current repair, and the work order can proceed directly to exchange approval." The comparison object is the source text above. The judgment concerns whether the subject, object, state and validity range in the source text support that draft sentence.
Configuration and implementation checks
| Configuration item | Assumed starting point for this page | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Warranty card base and work order base | Both use the same vector model; check the identifier before associating |
| Search mode | Hybrid search | Model and number need full-text hits, warranty scope needs semantic recall |
| Reference limit | 3000 tokens as the assumed trial starting point | Compare content completeness across long and short work order and warranty card fragments |
| Minimum relevance | 0.4 as the assumed trial starting point | Label relevant and irrelevant samples first, then compare filtered results |
| Question optimization | Enabled for multi-turn follow-up | Compare original and optimized questions, check whether the subject was altered |
| Result reranking | Enabled when candidates are numerous | Check the relation between rerank score and question completeness |
Three common errors
- Treating retrieval recall as an authorization decision. Input the draft sentence "the work order can proceed directly to exchange approval," compare the source text where the work order status is pending inspection and no inspection report has been issued, and observe whether the draft sentence exceeds the authorization boundary in the source text. A retrieval hit on warranty card content does not mean exchange approval has been granted.
- Treating minimum relevance as a permission or entity filter. Input the same query, compare work order records from different stores, and observe whether a low relevance threshold excludes unrelated stores. That value is a filter threshold and does not perform permission isolation.
- Treating warranty card scope as confirmed warranty for the current failure. The card states only mainboard failure and a twelve-month period. The source text has no inspection conclusion for this repair and no repair date, so whether the failure and the period fall inside the scope cannot be confirmed. Those fields remain to be verified.
How to verify the setup
- Input the warranty card, the pending-inspection work order and the draft sentence, then check the current failure, repair date, warranty scope and exchange approval basis separately. The source text has no inspection conclusion for this repair, no repair date and no exchange authorization, so the claims that warranty covers the repair and that it can proceed directly to approval remain unsupported. Do not supply missing process premises.
- Input a query containing model A2 and number BX-2024-0317, compare the recalled content from full-text search and semantic search, and observe whether the number and model are hit. The expectation is that full-text or hybrid search hits the exact number; a first-position hit is not guaranteed.
- Input an explicit paper empty reference array [] and check whether the downstream design has a branch that accepts an empty result. This checks the design only. The actual empty query result remains untested, and a reference length of zero is not assumed.
This page covers only brand after-sales repair service, store service and internal training, and knowledge base retrieval and recall. During operational handover, the authorization state of materials, operations and requests cannot be treated as granted by retrieval or by a form. The public technical facts used to identify relevant content are: the knowledge base search node can associate one or more knowledge bases using the same vector model; search modes are compared against test questions rather than assuming one mode suits all materials; the reference limit is measured in tokens and is tested with materials of different lengths before adjustment; minimum relevance takes effect only in semantic search or with result reranking, and thresholds are adjusted after labeling relevant and irrelevant samples; question optimization performs coreference resolution and question expansion, and original and optimized questions are compared to check whether the subject was altered.