What the documents look like
Community group-buy leader operations centre on community nodes and commission settlement, and do not directly carry out cold-chain quality inspection. The working materials are leader agreements, commission tables, pickup lists and community announcements. They come from the group-buy back office, leader chat groups, order details and after-sales records. Updates follow a daily and per-group rhythm.
Order fulfilment and after-sales answering has to resolve two kinds of question: whether the pickup scope for a given group on a given day includes a particular product, and what state a particular after-sales request currently occupies. Retrieval results therefore have to be checked back against a specific group and a specific date. Because the same product name, leader name or date can appear across several documents, the retrieval step has to return the passage that carries the matching field, and a person still has to confirm the group, the date and the current status before treating anything as settled.
Constraints at the retrieval step
The knowledge base search node can link one or more knowledge bases that share the same vector model. Linking bases built on different vector models is not permitted, so the model identifier has to be checked and non-matching bases excluded before a run. Search modes are semantic retrieval, full-text retrieval and hybrid retrieval; hybrid retrieval merges the multiple result paths through RRF. The citation cap is measured in tokens. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used, and it acts as a filter threshold rather than a final ordering rule.
Question optimisation performs coreference removal and question expansion, and it adds an extra model call before retrieval. Image retrieval depends on an image input and on the capabilities of the configured models, and reranking depends on a rerank model being available and enabled. The overall retrieval flow lists several optional paths, and those paths do not all execute on every request. Retrieval and similarity scores do not perform permission or entity checks. Whether a material may be handed over, and whether a request has been authorised, have to be verified separately. A pending request is not an approval, and an offered option is not an execution.
Configuration and implementation checks
Hypothetical drill sample. Material text supplied for checking: a station's Leader Agreement clause 4 states that a leader may submit an out-of-stock registration before 18:00 on the pickup day; the pickup list for a group dated 12 June carries the columns product, quantity, pickup point and status; one after-sales record reads "pending review". Draft sentence to be judged: "The leader completed the out-of-stock registration on 12 June and received compensation." That sentence contains a subject, a date and two facts still to be checked.
| Configuration item | Hypothetical starting point for this drill | Reason for the choice and the comparison object |
|---|---|---|
| Linked knowledge bases | Link only the leader agreement base and the pickup list base that share one vector model | Compare identifiers against a base on another vector model; exclude the non-matching one |
| Search mode | Run semantic retrieval first, then run full-text retrieval | Compare the candidates returned for the same question under the two modes |
| Citation cap | Start at a token amount that can hold one agreement clause | Compare against the tokens a complete clause needs, and observe whether it is truncated |
| Minimum relevance | Label relevant and irrelevant samples first, then take a middle value for a trial run | Compare against the labelled results and observe whether irrelevant fragments are filtered out |
| Question optimisation | Enable for short questions and multi-turn follow-ups | Compare the original question with the optimised question and check whether the subject was altered |
| Result reranking | Enable when candidates are numerous and a rerank model is configured | Compare ordering before and after reranking and observe where the relevant clause lands |
Three common errors
- Treating a retrieval hit as authorisation. The input is an after-sales record reading "pending review", and the comparison object is the compensation clause in the agreement. Concluding that compensation has been granted turns a retrieval result into an approval decision. The record status should be logged as pending review, and whether compensation holds remains to be verified.
- Linking knowledge bases built on different vector models. The input is the model identifiers of the two bases, and the comparison is whether they match. Linking them after a mismatch is a configuration error. The non-matching base should be excluded and the actual observation recorded, without inferring a runtime outcome.
- Treating the optimised question as the source wording. The input is the original question and the optimised question, and the comparison covers subject, date and object. If optimisation changed the group name or the date, the judgement is wrong. The material text governs, and the difference should be recorded.
How to verify the setup
- For the draft sentence "The leader completed the out-of-stock registration on 12 June and received compensation", the inputs are the text of agreement clause 4, the header of the 12 June pickup list, and the after-sales record whose status is "pending review". Compare the date, the subject and the two facts in the draft sentence against matching fields in the materials. If the materials show only a pending review and no compensation record, the draft sentence is unsupported and remains to be verified.
- For empty-result handling, the input is a paper retrieval result array of []. Compare whether the downstream node runs through its output path as the documentation describes, and observe whether the downstream still executes when the citation content length can be 0. This observation does not mean that a fabricated rule necessarily returns an empty array.
- For cross-model linking, the input is the vector model identifiers of the two knowledge bases. Compare whether they match; if they do not, exclude the base rather than running a cross-model search to compare missed recalls. Record the identifier difference actually observed, and leave missing model information as unknown.
This page covers only community group-buy leader operations, order fulfilment and after-sales answering, and knowledge base retrieval and recall. Which materials, operations and requests sit in which authorisation state during an operations handover is a separate question, and retrieval or a form does not constitute authorisation to act.