What the documents look like
Livestream after-sales work concentrates after a single broadcast ends. Refund requests and reshipment orders arrive in the same window, and customer service staff need to explain product parameters, host commitments and after-sales rules consistently. The source material comes from platform after-sales records, customer service instant messaging, warehouse management systems and logistics tracking, with updates after each broadcast and daily. The task on this page is narrow: for product information and selection questions, every cited parameter, commitment wording and after-sales rule in an answer must trace back to a specific document version and a specific field. The object of tracing is the citation source. A retrieval result does not grant authorization and does not replace business review.
Two industry facts shape this step. First, refund requests and reshipment orders cluster in one period, so several documents describe the same order from different angles; a citation that cannot be tied to a version is hard to reconcile. Second, host commitments are strongly tied to the live session, and the same product may have different commitment wording across sessions. The knowledge base search node can associate one or more knowledge bases that share the same vector model, and outputs citations as an array whose length may be zero. An empty array means the output path still runs; it does not establish that retrieval failed or that the business process stopped.
Constraints at the citation tracing step
Semantic search relies on vector distance. Full-text search suits numbers, model codes and proper nouns. Hybrid search combines multiple recall paths through RRF. A ReRank model produces a 0-1 score used for filtering. The minimum relevance value is a filter threshold that takes effect only in semantic search or when result reranking is used; it does not perform permission or entity isolation. The citation limit is measured in tokens, which differs from top k. Question optimization adds one model call before retrieval, and whether to enable it depends on observed effect. Image retrieval requires image input and matching model capability, and reranking requires a model enabled by configuration. Optional paths shown in the document flow diagram do not mean every request executes all of them. Knowledge bases with different vector models cannot be associated together; check the vector model identifier first and exclude those that do not match, rather than running a cross-model retrieval to compare missed recalls.
Hypothetical drill sample, clearly labelled as a paper exercise: after a livestream session ends, customer service receives a refund request. The buyer states that during the product explanation the host promised "seven-day no-reason return and the gift ships with the main item." The material text available for comparison reads: "Product A model X1 in this session; after-sales rules follow the platform seven-day no-reason policy; gift B ships in the same order as the main item, and the gift is not accepted for refund separately." A draft sentence awaiting review reads: "The gift in this order may be refunded separately, and the main item is handled under seven-day no-reason return." The material does not state an authorization clause for separate gift refunds. The draft sentence and the source text take different values on the gift handling field, so the matter is pending verification and cannot be judged as a denial or a conflict.
Configuration and implementation checks
| Check item | Documented setting or implementation check | Relation to this page's sample |
|---|---|---|
| Associated knowledge bases | Only knowledge bases with the same vector model can be associated | Verify the vector model identifier first and exclude non-matching ones; do not run a cross-model retrieval comparison |
| Citation output | The array length may be zero; the empty-result path still runs | Use the paper input [] to check downstream handling design; do not claim a fictional rule must return [] |
| Search mode | Semantic, full-text and hybrid search; hybrid combines through RRF | Model X1 is an exact code, so full-text or hybrid search fits |
| Minimum relevance | A 0-1 threshold effective only in semantic search or reranking | For this exercise the starting value is set at 0.5, because the sample question carries an explicit model code; compare against the unfiltered result |
| Question optimization | Adds one model call before retrieval | The sample question has a complete subject and predicate, so enabling it depends on observed effect |
| Citation limit | Controls citation content volume in tokens | For this exercise the starting value is set at 2000 tokens, compared against the sample material length before adjustment |
Three common errors
- Treating a retrieval hit as authorized execution. Input the sample refund request, compare the retrieval output against the refund operation permission field, and if the system performs a refund while no authorization clause is recorded, that is an overreach. The observable result is a refund action in the operation record with no authorization basis.
- Treating minimum relevance as an entity or permission filter. Input the sample model X1 query, compare whether the returned citations include other model codes or unauthorized records, and if an unrelated model appears and is treated as a valid source, that is misuse. The observable result is a citation list containing content that is not model X1.
- Writing a pending review state as a completed termination or an approval. Input the sample draft sentence on gift refunds, compare the gift handling field against the source text, and if the draft states a separate refund as an established rule while the material does not record it, that is an unsupported inference. The observable result is a value mismatch between the draft sentence and the source text on the same field.
How to verify the setup
- Input the sample material text and the draft sentence, and compare the values on the gift handling field. The condition is met if the draft is revised to "the gift ships in the same order as the main item, and a separate refund is pending review," without adding clauses the source text does not state.
- Input the sample model X1 query, and compare whether the citation list contains only X1-related material and whether each citation traces to a specific document version. If a non-X1 model appears or a citation cannot be traced, record the gap.
- Input the paper empty array [], and compare whether the downstream answer step handles it according to the empty-citation design. If the downstream step treats the empty array as a retrieval failure or automatically triggers a business action, record that observation without inferring a specific error cause.
These checks observe and record; they do not guarantee a first-hit result, full recall, or that an unrelated query returns nothing. Missing evidence stays missing, a pending request is not an approval, and an unsigned termination is not a completed termination.