What the documents look like
Cross-border product compliance happens before listing and import. The central evidence is product safety and label material, not payment risk. Everyday documents include product test reports, English labels, MSDS files and platform prohibited-item lists. Sources include platform policy centers, testing laboratory reports, destination-country regulation libraries and supplier material. Updates are irregular; each new listing can bring a new version. These materials often differ in subject and period. One test report covers a specific model and a specific test item. Retrieval also faces multiple languages: a Chinese question may need to reach English label text or English report content. Semantic retrieval supports cross-language understanding, so query wording and data chunking need to be considered together.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Knowledge bases using different vector models cannot be associated together. When this situation appears, check the identifiers first, exclude those that do not match, and record the actual observation. Do not run a cross-model search to compare results.
Search runs against the whole knowledge base. A collection is used only for classification and management. One retrieval combines semantic search, full-text search, image search, question optimization and reranking according to the input and parameters, then produces reference content after similarity filtering and reference-limit trimming. Reference content is output as an array and its length can be 0, which means the output path still runs even when nothing is found. The minimum relevance value takes effect only in semantic search or when result reranking is used. It is a filtering threshold and does not perform permission or entity isolation. A retrieval result does not constitute authorization, and it does not mean a material has been approved or a handover has been cleared for execution.
Hypothetical paper exercise sample: a batch of children's water bottles is being prepared for listing. The material is one English test report whose original text reads "Sample: Model CB-100; Test item: phthalate content; Result: pass; Report date: 2025-03-12". A separate supplier English label draft reads "Suitable for children over 3 years". The draft sentence to be assessed is "This model has completed phthalate testing, and the label age marking is consistent with the report". The report covers only the phthalate item for CB-100 and its issue date. It does not state a conclusion about checking the label age marking. The label-consistency part of the draft sentence is not supported and needs separate checking.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason for selection and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only compliance material bases that use the same vector model | Check the vector model identifier of each base, exclude those that do not match, and do not compare across models |
| Search mode | Start with hybrid search | Model CB-100 is an exact identifier; hybrid search uses semantic recall and full-text recall together, then compare with semantic-only and full-text-only results |
| Reference limit | Set one starting value for this exercise | Compare test reports and label fragments of different lengths, observe whether reference content is truncated, then adjust |
| Minimum relevance | Label relevant and irrelevant samples first | This value takes effect only in semantic search or when result reranking is used; observe filtering against the labeled samples |
| Question optimization | Enable for multi-turn follow-up scenarios | Compare the original question with the optimized question, check whether the subject has been changed incorrectly, then assess latency in short-question scenarios |
| Result reranking | Enable when a rerank model is available | Reranking produces a 0-1 score; observe ranking changes against that score |
Three common errors
- Treating a retrieval hit as authorization or approval. In the hypothetical sample, the report shows pass. A retrieval hit on that report only means the content was recalled. It does not mean the label marking has been checked and passed, and it does not mean listing has been approved. Check method: input the report original text and the draft sentence, compare the model, test item, result and date stated in the report against the scope claimed by the draft sentence. They match only when the claim falls inside the stated scope.
- Treating minimum relevance as a permission or entity filter. That value is a filtering threshold and does not exclude unrelated business records or unauthorized records. Check method: input a query that is semantically close to compliance material but belongs to another business, observe whether the returned content still contains that record, and confirm that filtering works only by relevance.
- Treating optional retrieval paths as mandatory on every request. Image search requires image input and the corresponding model capability. Reranking requires an available model and must be enabled by configuration. Check method: input a text-only query, observe whether image description or image vector recall paths appear, and confirm that the paths match the input and the available capability.
How to verify the setup
- Use the report original text from the hypothetical sample as input, and compare whether the returned content contains the four fields CB-100, phthalate content, pass and 2025-03-12. When the returned content contains all four fields and is not truncated, treat that item as a hit. When any field is missing, record the gap and do not infer a failure.
- Use the draft sentence as input, and compare whether the returned content states a conclusion about checking the label age marking. When the returned content does not state that conclusion, judge it as unsupported, keep the evidence gap, and do not judge it as a conflict.
- Use a clearly defined paper input of an empty array to check the downstream design, and observe whether the downstream path still runs when the reference length is 0. This check addresses path continuity. It does not mean that a fictional rule search necessarily returns an empty array.