What the documents look like
Group-buy leader operations revolve around node management rather than cold-chain inspection. The leader agreement sets out cooperation and commission terms; the commission table is updated by group and by day; the pickup list corresponds to arrivals and collections for each group and each order; community announcements are addressed to neighbours. These materials originate from the platform back office, leader community groups, order details and after-sales records, and the routine handling rhythm is daily or once per group.
Product questions and selection questions typically ask about the currently effective agreement terms of a given leader, the commission basis for a given group on a given day, the item details of a given pickup list, or the scope of application of a given announcement. The update frequency is high, and the value of the same field may change across dates. When retrieval does not constrain date and subject, an expired basis can easily be returned.
A knowledge base consists of three levels: library, collection and data. The smallest search unit is the library; collections only serve to classify and manage data. Leader agreements, commission tables, pickup lists and community announcements can each sit in a different collection, but retrieval runs against the whole library. When several material types are mixed in one library, the subject, date and scope carried in the content itself are what distinguish them.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Libraries with different vector models cannot be associated together. Before configuration, check the vector model identifier of each library, exclude those that do not match, and do not run cross-model retrieval to compare recall differences.
Semantic retrieval relies on vector distance and suits natural-language phrasing. Full-text retrieval relies on keyword hits and suits numbers, models and proper nouns. Hybrid retrieval uses both paths and merges the results through RRF. RRF is a fusion process, not a separate switch that can be turned on. Result reranking requires a rerank model and must be enabled according to the settings; the rerank score is 0-1, and the minimum relevance value takes effect only under semantic retrieval or when result reranking is used.
Question optimization adds one model call before retrieval, for coreference resolution and question expansion. It is more visible in multi-turn follow-ups and short questions, and it also adds latency. The reference limit is measured in tokens and controls the maximum amount of content cited per search. The node output is an array, whose length can be 0; when nothing is retrieved, the output path still runs through.
The retrieval step does not perform authorization judgement. Whether content hit inside a library may be used for a particular leader or a particular commission requires downstream business verification. The retrieval result itself does not constitute a basis for permission, approval or settlement.
Configuration and implementation checks
The following is set around a hypothetical paper exercise sample. The values are starting points for this exercise, used for comparison against control values, and are not official defaults.
Hypothetical paper exercise sample: in a platform's group-buy leader operations knowledge base, the original text of a Leader Agreement material reads: "This agreement applies to the community group-buy cooperation of leader Zhang from 1 March 2025 to 31 December 2025. Commission is calculated at 5% of the paid amount of orders whose pickup was completed in the current month. During the agreement period, the pickup list is the version generated per group per day." The draft sentence to be judged is: "Leader Zhang's commission for April 2025 is calculated at 8% of the paid amount of that month."
| Configuration item | Hypothetical value for this exercise | Reason for selection and comparison object |
|---|---|---|
| Associated knowledge bases | Associate only the group-buy leader operations library whose vector model identifier matches | First check the vector model identifier of each library and exclude mismatches |
| Search mode | Hybrid retrieval | Compare against semantic retrieval alone and full-text retrieval alone, observing hit differences on number-type questions |
| Reference limit | Starting point 2000 tokens | Test with agreement and commission materials of different lengths for content completeness, comparing against 1000 and 4000 |
| Minimum relevance | Starting point 0.3 | First label relevant and irrelevant samples, compare against 0.2 and 0.5, and observe the remaining entries after filtering |
| Question optimization | Enabled | Compare the original question with the optimized question and check whether subject and date were altered incorrectly |
| Result reranking | Enabled | Compare candidate ordering before and after reranking, and check the score range together with the minimum relevance value |
Three common errors
- Associating libraries with different vector models together. The input is two group-buy leader operations libraries with different vector model identifiers. Compare the identifier field of each library and observe whether they match. When the identifiers do not match, exclude that library and record the actual observation; do not infer the runtime result of associating them together.
- Using a retrieval hit in place of an authorization judgement. The input is the draft sentence for Leader Zhang's April 2025 commission in the hypothetical sample. Compare the rate in the draft sentence with the 5% in the agreement original text, and observe whether both refer to the same subject, the same period and the same field. A different rate value constitutes a contradiction in the same field. Retrieving the agreement does not mean the draft sentence has been approved.
- Treating a pending-review status as already effective. The input is a leader agreement handover request marked "pending review". Compare the status field in the request with the conditions required for the agreement to take effect, and observe whether signing and effectiveness records exist. Pending review does not show that operating permission is missing, and it is not equivalent to the agreement having taken effect. The missing effectiveness evidence remains a gap.
How to verify the setup
- Subject and period check. The input is the Leader Agreement original text and the draft sentence in the hypothetical sample. Compare the agreement's applicable subject "leader Zhang" and period "1 March 2025 to 31 December 2025" with the draft sentence's "April 2025", and observe whether the subject and period fall within the valid range of the agreement. When the draft sentence's rate of 8% does not match the original text's 5%, judge it as a contradiction in the same field; the draft sentence is not supported by the original text.
- Empty-result handling check. The input is an explicit paper retrieval result of
[]. Compare how the downstream design handles a reference array of length 0, and observe whether the output path runs through and whether the downstream distinguishes an empty reference. Do not claim that a fictional rule retrieval necessarily returns[]; the empty result is only checked against downstream handling as an input. - Retrieval scope and authorization boundary check. The input is a leader commission material that needs verification. Compare whether this material lies within the library scope of this retrieval and whether access rights exist, and observe whether the material appears in the retrieval output. When the material is missing or access is not permitted, record the gap. A retrieval hit does not mean authorization has been granted; business verification, approval and settlement require separate system implementation.