What the documents look like
Group-buy leader operations manage community nodes and commission, and do not perform cold-chain quality inspection. The working materials for an operating review are the leader agreement, the commission table, the pickup list and the community announcement. These materials update daily or per group, and they sit in different places: the community group-buy backend, leader chat groups, order details and after-sales records.
An operating review and exception replay has to decide who is responsible for a specific commission line, a specific wrong or missed delivery, or a specific neighbor after-sales case within a defined period. That decision requires the agreement clauses, the commission rules, the pickup records and the announcement wording to be checked inside one retrieval scope. Because the materials are scattered, retrieval can easily mix content from different leaders, different periods or different fields.
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Bases with different vector models cannot be associated together. The operator should first check the model identifier and exclude those that do not match, and should not run cross-model retrieval in order to compare missed recalls. Search mode is compared across semantic retrieval, full-text retrieval and hybrid retrieval according to the test question, and no single mode is assumed to suit all materials. The reference limit is measured in tokens, and actual materials of different lengths are used to test whether the content is complete. The minimum relevance score takes effect only in semantic retrieval or when result reranking is used. Question optimization performs coreference resolution and question expansion, so the original question and the optimized question are compared to check whether the subject has been changed incorrectly. RRF is the fusion process for mixed results and is not an on/off switch. Image retrieval requires a corresponding image input and model capability, and reranking requires a model and must be enabled according to the setting. Retrieval and similarity scores do not carry authorization or entity isolation.
Hypothetical exercise sample: a platform leader operations team reviews a commission difference in June 2025. The source text to be checked reads: "Leader A's June 2025 commission table states that commission on valid orders for the month is settled at 3%, and returned orders do not count toward commission." "Leader A's June 2025 pickup list states that order T-0612 was picked up on 12 June, and order T-0618 was returned on 18 June." "Leader A's June 2025 community announcement states that commission on returned orders in June is offset in the following month." The draft sentence is: "Leader A's June 2025 commission was settled in full at 3%, and returned orders were not offset." The judgment object is Leader A, the period is June 2025, the fields are commission settlement and return offset, and the authorization boundary is limited to the platform leader operations team's internal review, with no external settlement execution.
Constraints at the retrieval step
The associated knowledge bases must share the same vector model. In this review, the leader agreement base, the commission table base, the pickup list base and the community announcement base are checked for a matching model identifier before association. A mismatch is recorded and the non-matching base is excluded. No claim is made about what a cross-model association would return, because the documented condition is only that such bases cannot be associated together.
Search mode is selected by comparing behavior on the test question. Commission amounts and order numbers benefit from keyword hits, while clause wording benefits from semantic recall, so hybrid retrieval is the starting comparison. The reference limit controls how many tokens of content are cited per search. It is not a top-k item count. Materials of different lengths, such as a short announcement line and a long commission table section, are used to compare whether the cited content stays complete.
The minimum relevance score is a filter threshold, not a final ranking rule, and it applies only in semantic retrieval or with result reranking. It is compared first against labeled relevant and irrelevant samples. A relevance score is not a category, entity or permission filter, and raising it does not exclude unrelated businesses or unauthorized records. Retrieval is not authorization.
Question optimization runs before retrieval and adds a model call. It is compared by checking whether the subject and period in the optimized question still match the original. If the subject changes to another leader or the period changes, that is recorded as an optimization deviation. Reranking is a second ordering pass over candidates and produces a score between 0 and 1; it is compared by observing whether the ordering changes and how the score filters results.
Image retrieval is an optional path. It requires an actual image input and a model that supports image description or image vectors. It is not assumed to run on every request. Empty reference output is a documented possibility: the reference content is returned as an array whose length can be zero, and the downstream output path still completes.
Configuration and implementation checks
| Configuration item | Hypothetical trial starting point | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Leader agreement base, commission table base, pickup list base, community announcement base | The four bases use the same vector model; check the identifier before associating |
| Search mode | Hybrid retrieval | Commission amounts and order numbers need keyword hits; clause wording needs semantic recall |
| Reference limit | 1200 tokens | Trial starting point for this exercise; compare content completeness using commission table and announcement fragments of different lengths |
| Minimum relevance score | 0.35 | Trial starting point for this exercise; compare filtering effect against labeled relevant and irrelevant samples first |
| Question optimization | Enabled | Used for coreference resolution; compare whether the subject in the original and optimized question stays the same |
| Result reranking | Enabled | Second ordering when candidates are numerous; compare ordering changes by rerank score |
Three common errors
- Forcing association of bases with different vector models. The input is the leader agreement base and the commission table base. If their vector model identifiers differ, the comparison of identifiers should exclude the non-matching base, and the actual observation is recorded. Cross-model retrieval is not executed in order to compare missed recalls.
- Treating the minimum relevance score as a permission or entity filter. The input is a commission question about Leader A. If the retrieval result contains Leader B's commission table, comparing the subject field should mark it as irrelevant. Raising the relevance score does not exclude unauthorized records.
- Treating the draft sentence "settled in full, not offset" as fact. The input is the draft sentence and the three source texts. After comparing the same subject, the same period and the same fields, the announcement states that returned commission is offset the following month. The draft sentence's "not offset" does not match the announcement wording and should be judged as unsupported.
How to verify the setup
- Input the draft sentence and the three source texts from the hypothetical sample, and compare Leader A, June 2025, and the commission settlement and return offset fields. If the retrieval result hits the 3% clause in the commission table, the T-0618 return record in the pickup list, and the following-month offset wording in the announcement, and the draft sentence does not match the announcement wording, the check condition is met.
- Input a follow-up commission question about Leader A, and compare the original question with the retrieval terms after question optimization. If the optimized subject is still Leader A and the period is still June 2025, the check condition is met. If the subject is changed to another leader or the period is altered, record it as a question optimization deviation.
- Input a paper empty-result scenario in which retrieval returns reference content of length 0. Compare whether the downstream node still completes its output path. If the downstream accepts the empty array and records the gap, the check condition is met. No claim is made that a fictional rule search necessarily returns an empty array.