What the documents look like
Retail packaging reporting for supermarkets and convenience stores centers on single-use plastic bag records and environmental compliance, not on membership marketing or checkout promotions. The working materials are plastic bag procurement ledgers, sales vouchers, semi-annual reports, and self-discipline commitment documents. These come from the Ministry of Commerce reporting system, POS plastic bag sales, procurement systems, and store ledgers. Day-to-day comparison work involves matching procurement ledgers against sales vouchers on quantity, period, and entity relationship. The most time-consuming steps are counting usage, checking sales vouchers, and reporting recycling status. Materials form on two rhythms: semi-annual and daily. Retrieval therefore faces ledgers, vouchers, and report texts from the same store across different periods.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. A collection is only for classification management and does not affect search results; the smallest search unit is the knowledge base. Semantic retrieval relies on vector distance, full-text retrieval relies on keyword hits, hybrid retrieval merges multiple result paths through RRF, and reranking performs a second sort on candidate texts and produces a 0-1 score. The citation limit controls how much content each search cites, measured in tokens. The minimum relevance value takes effect only during semantic retrieval or when result reranking is used. Question optimization performs coreference resolution and question expansion, adding one model call before retrieval. Retrieval results only provide cited content; they do not constitute authorization, approval, or write actions. Form value collection, business verification, database writes, and external synchronization are separate stages.
Hypothetical paper exercise sample: a store compliance role prepares to write a handover note into the knowledge base for later comparison. The source text has three sentences: "This store's plastic bag procurement ledger for the first half of 2024 records a procurement quantity of 12,000 bags, corresponding to a sales voucher summary sales quantity of 11,800 bags, with the period being January to June 2024. The semi-annual report has been submitted to the Ministry of Commerce reporting system, and the submission status is pending review. The self-discipline commitment document has been signed, with a signing date of July 3, 2024." The draft sentence to be judged is: "This store's plastic bag procurement and sales quantities for the first half of 2024 are consistent, the semi-annual report has passed review, and the self-discipline commitment has taken effect." This draft sentence mixes in review-passed and effective status that the source text does not state.
Configuration and implementation checks
The table below lists only official documented settings or implementation check items relevant to this feature and the primary task, using the sample above.
| Configuration item | Hypothetical starting point for this exercise | Reason for choice and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only the same-vector-model knowledge base holding this store's ledgers and vouchers | Knowledge bases with different vector models cannot be associated together; check the vector model identifier first and exclude those that do not match |
| Search mode | Hybrid retrieval | Ledger numbers and periods are exact fields, and natural-language questions also need coverage; compare semantic and full-text result paths |
| Citation limit | Set to a token amount that can hold the three source sentences of the ledger | Test with actual materials of different lengths to see whether content is complete, then adjust; do not preset a fixed number |
| Minimum relevance | Label relevant and irrelevant samples first, then set a threshold | This value takes effect only during semantic retrieval or result reranking; use labeled samples to compare filtering effects |
| Question optimization | Enable for follow-up questions containing coreference; for clear questions, compare the original question with the optimized question | Check whether the subject was changed incorrectly, and observe the extra time cost from the additional model call |
| Result reranking | Use when a reranking model is available and enabled according to settings | The reranking score is 0-1 and can be used for filtering; compare candidate ordering before and after reranking |
Three common errors
- Treating a retrieval hit as authorization or completed approval. In the sample, the semi-annual report submission status is pending review. Retrieving that sentence only shows the material exists. Pending review does not equal review passed, and it does not demonstrate a lack of operating permission. To check, input the draft sentence and the source text, compare whether "pending review" and "review passed" are mutually exclusive values of the same field, and observe whether the draft sentence introduces a status the source text does not state.
- Confusing signing, cooperation reached, and contract effectiveness. In the sample, the self-discipline commitment has been signed with a signing date of July 3, 2024, and the source text does not state an effectiveness clause. To check, compare the draft sentence "has taken effect" with the source text "has been signed," observe whether the source text provides an effectiveness condition, and record a lack of support when it is missing.
- Using minimum relevance or a similarity score as a substitute for permission or entity isolation. A similarity score is a relevance measure and does not perform permission or entity filtering. To check, input the same question, compare whether returned citations come only from authorized knowledge bases, observe whether records from other entities are mixed in, and record the gap when authorization information is missing.
How to verify the setup
- For the sample draft sentence "This store's plastic bag procurement and sales quantities for the first half of 2024 are consistent," input this sentence into the associated knowledge base for retrieval, compare whether the returned citations include the ledger source text's 12,000 bags and the sales voucher's 11,800 bags, and observe whether the citations present both values and the same period. The condition is met when the cited content can support a judgment about the quantity difference.
- For the sample draft sentence "the semi-annual report has passed review," input this sentence for retrieval, compare the submission status field in the returned citations, and observe whether only "pending review" appears. If only pending review appears, the draft sentence lacks support and the evidence gap must be recorded.
- For empty-result handling, use a clearly labeled paper input of an empty array to check the downstream design, compare whether the downstream node follows the path where citation length is 0, and observe whether the output path still executes. Do not claim that a fictional rule retrieval will necessarily return an empty array.
Knowledge bases with different vector models cannot be associated together; check the identifier first, exclude those that do not match, record actual observations, and do not fabricate runtime results after joint association. Image retrieval requires an image input and corresponding model capability. Reranking requires a model and must be enabled according to settings. Optional paths shown in the overall document flow diagram do not mean every request executes all of them.