What the documents look like
Fresh-food weighing and sorting happens inside warehouse fulfillment, and the core records revolve around weight and specification. Source systems include the WMS, electronic scales, the order system and quality-inspection photos. Day-to-day documents include sorting task sheets, weighing labels, short-weight compensation forms and quality-inspection records. These materials update per order or per day.
In cross-border material and multilingual retrieval work, one batch of sorting tasks may correspond to weighing labels and compensation notes in different languages. Citation tracing requires that each answer can be returned to a specific task sheet, label or quality-inspection record. Frequent updates mean version checking is part of citation work; a historical weighing value cannot be treated as the currently valid record.
Constraints at the citation tracing step
The knowledge base search node outputs cited content as an array, and its length can be zero. Even when nothing is retrieved, the output path still runs. Tracing therefore cannot assume that every search returns a result.
When associating knowledge bases, only knowledge bases that share the same vector model can be selected together for vector search. Knowledge bases with different vector models cannot be associated jointly. During checking, inspect the vector model identifier first and exclude those that do not match. Do not run cross-model retrieval to compare missed recalls.
Minimum relevance is a filtering threshold that takes effect only in semantic retrieval or when result reranking is used. This value does not perform permission or entity isolation, and retrieval itself is not authorization. Hybrid retrieval merges multiple result paths through RRF. The rerank model is enabled according to configuration. Image retrieval requires the corresponding image input and model capability. These optional paths do not all execute on every request.
The citation limit controls, in tokens, the maximum amount of content cited per search. This parameter is unrelated to the thinking budget; the thinking budget only controls model thinking intensity.
Configuration and implementation checks
The table below lists officially documented settings or implementation check items relevant to this feature and the primary task, using a hypothetical exercise sample.
| Configuration item | Hypothetical starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Select only two libraries with the same vector model identifier | Check the vector model identifier field and exclude libraries with different identifiers |
| Search mode | Hybrid retrieval | Compare with semantic retrieval used alone, and observe whether number-type queries are hit |
| Minimum relevance | Hypothetical starting point 0.3 | Compare with 0.5, observe changes in the number of returned items, and confirm the threshold applies only to semantic retrieval or reranking |
| Citation limit | Hypothetical starting point 2000 tokens | Compare with 1000 tokens, observe whether cited content is truncated, and confirm the unit is tokens |
| Question optimization | Enabled | Compare with the disabled state on follow-up retrieval results, and observe whether coreference resolution takes effect |
| Result reranking | Enabled | Compare with the disabled state on candidate ordering, and observe whether the rerank score is used for filtering |
Three common errors
- Treating retrieval output as authorized execution. The knowledge base search node outputs a citation array; that output only represents retrieved content and does not represent any business approval or authorization status. A short-weight compensation form pending review does not demonstrate a lack of operating permission, and retrieving that form does not mean compensation has been approved.
- Forcing association of knowledge bases with different vector models. Only knowledge bases with the same vector model can be associated together. During checking, inspect the vector model identifier and exclude those that do not match. Do not invent missed recalls or redundant results after joint association.
- Treating minimum relevance as a permission or entity filter. This value takes effect only in semantic retrieval or result reranking, and it does not exclude unrelated businesses or unauthorized records. Retrieval results still require review against the valid version.
How to verify the setup
Hypothetical exercise sample: a front warehouse sorting task sheet reads: "Task sheet number SF-2024-001, product is imported cherries, specification 2 kg pack, sorter has completed weighing, actual weight 1.95 kg, quality-inspection record shows appearance intact, short-weight compensation form status is pending review." A draft sentence to be judged reads: "This task sheet has completed short-weight compensation approval."
- Verification one: input the task sheet text above and the draft sentence. Compare the phrase "has completed approval" in the draft with the "pending review" status field in the original text, and observe whether the two contradict each other. The expected phenomenon is that the draft sentence conflicts with the original status; pending review does not constitute completed approval.
- Verification two: input the task sheet text above. Check whether the citation output array contains that original content. Compare the citation entry with the original text on subject, object and status fields, and observe whether the citation corresponds item by item. The expected phenomenon is that the citation entry should match the original text; if the array is empty, record the gap.
- Verification three: input the draft sentence and the task sheet text. Check whether the vector model identifiers are the same. Compare the vector model fields of the two knowledge bases, and observe whether any identifier mismatch exists. The expected phenomenon is that libraries with different identifiers cannot be associated jointly; exclude them and record the actual observation.
All three verifications use the hypothetical original text and draft sentence above and do not claim to have been tested. For empty-result downstream handling, a clearly labelled paper input [] can be used to check the downstream design. Do not claim that a fictional rule retrieval necessarily returns [].
This page addresses only fresh-food weighing and sorting / cross-border material and multilingual retrieval / citation tracing. During operational handover, the authorization status of materials, operations and requests cannot be treated as executed merely because retrieval or a form was used.