What the documents look like
Fruit-store procurement keeps four document families in daily use: purchase orders, acceptance sheets, pesticide-residue test reports, and loss records. Their sources include wholesale-market quotations, supplier quotations, store sales, and inspection reports. Fruit procurement depends heavily on wholesale-market conditions and grade acceptance, and it does not follow a single headquarters standard-meal specification. Material updates occur daily or per batch, so any retrieved acceptance grade, quotation, or inspection conclusion carries a clear time boundary and batch boundary. During order fulfilment and after-sales question handling, staff check the acceptance conclusion for a delivery, the batch that a test report covers, and the responsibility recorded in a loss entry. Each of these checks depends on the subject, object, state, and validity scope written in the source material.
Constraints at the retrieval step
A 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 vector-model identifier is checked first, non-matching bases are excluded, and the actual observation is recorded. A cross-model search is not run to compare missed recalls.
Search modes are semantic retrieval, full-text retrieval, and hybrid retrieval. They are compared against the same test question, and no single mode is assumed to suit all materials. The citation limit is measured in tokens, so materials of different lengths are used to test whether content stays complete. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used; it is a filter threshold, not the final ordering rule. Question optimization performs coreference resolution and question expansion, so the original question and the optimized question are compared to check whether the subject was altered. Image retrieval requires corresponding image input and model capability. Reranking requires a model and must be enabled according to the settings. The optional paths shown in the overall process diagram do not mean that every request executes all of them. Retrieval and similarity scores do not carry permission or entity-isolation functions, and the same-vector-model requirement for associated bases does not extend to external systems.
Configuration and implementation checks
The table covers a hypothetical drill sample for this page and lists only officially documented settings or implementation checks tied to this function and the primary task.
| Configuration item | Hypothetical trial starting point | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only one base containing purchase orders, acceptance sheets, test reports, and loss records | Check the vector-model identifier of that base first, then exclude others whose model differs |
| Search mode | Hybrid retrieval | Compare recalled content for the same test question against semantic retrieval alone and full-text retrieval alone |
| Citation limit | Hypothetical starting point of 2000 tokens | Compare acceptance sheets and test reports of different lengths to see whether content is truncated |
| Minimum relevance | Hypothetical starting point of 0.5 | Label relevant and irrelevant samples first, then compare filter results against 0.4 and 0.6 |
| Question optimization | Enabled | Compare the original question with the optimized question and check whether the batch subject was altered |
| Result reranking | Enabled according to the settings | Where a reranking model exists, compare candidate ordering before and after reranking |
Three common errors
- Treating retrieval or a form as an authorization action. In the hypothetical drill sample, a procurement supervisor submits an after-sales question request. The material states: "The acceptance conclusion for this delivery is pending review, and a test report has been issued for the corresponding batch." The draft sentence reads: "This batch has passed acceptance and a refund is available." The input is this source text and this draft sentence, checked separately for the acceptance conclusion and the refund basis. A pending-review state does not support a passed-acceptance claim. An issued test report supplies no report conclusion and no refund authorization, so the refund claim is recorded separately as pending verification and the whole sentence is not treated as one field. A pending review does not demonstrate a lack of operating permission, and it does not mean a refund was executed.
- Treating minimum relevance as a permission or entity filter. The input is the same test question with the recall lists before and after minimum relevance is enabled. The comparison is whether the filtered-out content consists of irrelevant fragments. The observable result is that a threshold change alters only the relevance filtering result and does not alter the accessible scope. A similarity setting does not exclude unrelated businesses or unauthorized records.
- Forcing knowledge bases with different vector models into one association. The input is two base identifiers with different vector-model identifiers. The comparison is whether the identifiers match. The observable result is that non-matching identifiers are excluded and recorded, and no runtime outcome of a forced association is inferred.
How to verify the setup
- Check the draft sentence against the hypothetical drill sample source text. The input is "The acceptance conclusion for this delivery is pending review, and a test report has been issued for the corresponding batch" together with the draft sentence "This batch has passed acceptance and a refund is available." List the acceptance state, the test-report conclusion, and the refund basis separately. The source text gives only a pending-review state and an issued report; it gives no passed conclusion and no refund basis. The two claims in the draft are each unsupported.
- Check empty-result handling with an explicit paper input. The input is a paper input in which the cited-content array has a length of 0. The comparison is whether the downstream chain still runs. The observable result is that the output chain runs and the citation length is 0. No claim is made that a fictional rule search necessarily returns an empty array.
- Compare the three search modes with the same test question. The input is the same test question and the same knowledge base. Compare the cited content returned by semantic retrieval, full-text retrieval, and hybrid retrieval, and record the actual content of each mode and whether differences appear. No necessary difference is assumed, and no first-hit match or complete recall is guaranteed.