What the documents look like
Cold-chain receiving for fresh goods at store level uses four document families: cold-chain temperature records, arrival acceptance sheets, rejection notes, and supplier delivery notes. Compared with fruit procurement, this category tracks transport temperature and the arriving batch. Origin price inquiry sits outside this task. Materials update per batch and per day, and they originate from vehicle temperature control, the WMS, the store receiving system, and quality inspection photographs. Those traits shape how vector indexes are built. A temperature record carries timestamps and numeric readings. An acceptance sheet carries a batch number and line items. A rejection note carries a reason and a quantity. A delivery note carries a supplier and a document number. Semantic density and key fields differ across the four families, so index content and recall paths need separate treatment. Retrieval only locates candidate source text. Authorization, approval, database writes, and external synchronization each require their own downstream implementation.
Within the inventory procurement and supplier records task, one practical point matters at the start: a knowledge base used for retrieval must share the same vector model. Confirm the deployed model identifier and the input type it accepts before associating any knowledge bases. A single source data block may map to several indexes, so index content and source text are checked separately. Image retrieval depends on whether an image description index or an image vector index was generated at ingestion time; uploading an image at query time alone does not settle it. Vector model quality, data quality, and retriever precision all affect results. Retriever precision is comparatively easy to address, which leaves data quality and query term quality as the main optimization targets.
Constraints at the vector indexes step
Mixed retrieval combines semantic recall and full-text recall, then merges the result sets through RRF. RRF is a fusion process; the documentation does not describe it as a standalone switch. Reranking requires a ReRank model and must be enabled per configuration. Image retrieval requires image input and matching model capability. The optional paths drawn in the overall search flow do not all execute on every request.
The minimum relevance value applies only under semantic retrieval or when result reranking is used. It is a filter threshold. It does not act as a permission filter or an entity isolation mechanism, and a similarity setting does not exclude unrelated businesses or unauthorized records. The quote limit is measured in tokens, not in a guessed item count. When no content is found, the output link still completes: the reference output is an array whose length may be zero.
Configuration and implementation checks
Hypothetical drill sample: on 12 March 2025, a store receiving system generates an arrival acceptance sheet. The acting party is a fresh-goods warehouse distribution function delivering to a store. The object is batch A chilled pork. The status field reads "accepted, core temperature 3.2 degrees Celsius, sampling passed." On the same day, a rejection note draft exists for the same acting party and the same object, with a status field reading only "awaiting quality inspector confirmation." A candidate assertion sentence reads: "This batch has completed acceptance and may enter inventory settlement."
| Configuration item | Hypothetical trial starting point | How to check |
|---|---|---|
| Vector model identifier | Use the actual deployed model identifier | Compare whether associated knowledge bases share one model identifier |
| Index content | Keep acting party, object, status, and date for each material | Compare field by field against the acceptance sheet source text |
| Quote limit | Start at a level covering one item from each of the four material families | Compare against the actual token volume of the sample, then adjust |
| Minimum relevance | Start at 0.3 | Compare against the rerank score distribution; treat as a filter threshold only |
| Search mode | Semantic retrieval and full-text retrieval used together | Check that numbered fields are hit through full-text retrieval |
| Image index | First confirm whether an image description index was generated at ingestion | Check whether the inspection photograph already has a corresponding index |
These values are starting points for this hypothetical trial. The reason is that the sample materials are short, so recall coverage is observed first before any adjustment. They are not official default values.
Three common errors
- Associating knowledge bases that use different vector models. The error is ignoring the same-model requirement. Check: read the model identifier of each knowledge base, compare them, and if they differ, exclude the non-matching one and record that. Do not run a cross-model retrieval to compare missed recall.
- Treating a retrieval hit as authorization. The error is reading a recall result as business permission. Check: input the candidate assertion sentence, compare the retrieval output against the status field of the acceptance sheet, and if the status is "awaiting quality inspector confirmation," record it as pending verification rather than completed acceptance.
- Describing RRF as an independent switch that can be turned on. The error is confusing a fusion process with a configuration item. Check: inspect the configuration interface for such a switch, and if none exists, record that the documentation does not provide one. Do not add a control item.
How to verify the setup
- Verification one: input the hypothetical acceptance sheet source text together with the candidate assertion sentence "This batch has completed acceptance and may enter inventory settlement." Compare the status field "accepted" against the candidate assertion sentence. The check condition is met only when the retrieval references the source text of that status field. If the retrieval references the rejection note draft instead, record it as a mismatch of evidence.
- Verification two: input the rejection note draft source text "awaiting quality inspector confirmation." Compare that status against "completed acceptance" for mutual exclusivity. Record a contradiction only when the same acting party, the same object, the same period, and the same field carry clearly exclusive values. When only a pending-review status exists, record it as unsupported.
- Verification three: input a quality inspection photograph query. Compare whether an image description index or an image vector index was generated at ingestion. Record that the photograph can participate in image retrieval only when the corresponding index is confirmed to exist. If no index was generated, record it as a gap. Do not claim that uploading at query time will produce a hit.
For empty-result handling, a paper input of an empty array can be used to check the downstream design. Do not claim that a fabricated rule will necessarily return an empty array. After any model or index adjustment, compare referenced source text using the same question set. Do not promise an outcome from a vector score alone.