What the documents look like
Creator-led sales campaigns depend on external creators completing agreed sessions and on commission settlement. The working materials are creator cooperation agreements, commission setting sheets, sample shipment forms and livestream performance reports. Sources include selected alliance data, creator marketplace data, creator history and store transaction details. In cross-border and multilingual retrieval, one agreement may contain Chinese, English or mixed clauses, and a search phrase may not match the language of the stored text. Semantic retrieval is documented as offering cross-multilingual understanding, so a Chinese question can match an English knowledge point. Material updates follow each session and each week. The smallest search unit is the library; collections only classify data and are documented as unrelated to search results.
Constraints at the vector indexes step
Knowledge bases linked for retrieval must use the same vector model. Verify the actual model identifier and the input type before linking. One original data block can carry several indexes, and the index content is checked against the original text separately. Index content should be complete and focused; retrieval coverage and index length are weighed against samples. Image retrieval also depends on whether image descriptions or image vectors were generated at ingestion, so checking only the query side is insufficient. After a model or index change, compare cited original text using the same set of questions; do not promise an outcome from a vector score alone. The same-model requirement applies to linked knowledge bases and does not extend to business-registration sites or other external systems.
Hypothetical paper exercise sample: the source text reads, "Party A commissions Party B to complete two dedicated livestream sessions between 1 March 2025 and 31 March 2025; commission is calculated at fifteen percent of the actual settled amount; samples are sent out before 20 February." The draft sentence to be assessed reads, "Party B must continue to provide after-sales support after 31 March." The source text states no after-sales support obligation. The draft sentence is unsupported; it does not establish that Party B holds this obligation, and it does not establish that Party B lacks it.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Verification method |
|---|---|---|
| Linked knowledge bases | Link only knowledge bases that share one vector model | Check the actual model identifier and exclude those that do not match |
| Index content | Build focused indexes per agreement paragraph | Compare the index against the semantic scope of the original text |
| Image index | Confirm at ingestion whether an image description or image vector was generated | Inspect ingestion records and query-side model capability |
| Search mode | Semantic retrieval for cross-language phrasing | Compare cited original text across the same question set |
| Reference limit | Controlled by tokens, not top k | Observe the length distribution of returned references |
| Minimum relevance | Applies only under semantic retrieval or result reranking | Check the filter threshold against the returned ordering |
The reference limit is documented in tokens because chunk lengths vary widely in mixed knowledge bases, which makes top k unstable. Minimum relevance is a filter threshold and not a final ordering rule; after question optimization, hybrid retrieval, image retrieval or reranking, results may be fused from several recall paths and need not follow a single vector similarity order. Question optimization adds one model call before retrieval, so it can improve multi-turn retrieval while increasing total time. Reranking produces a 0-1 score that is usually more precise than a vector score and can be used for filtering. RRF is a documented fusion step across recall paths, not a switch.
Three common errors
- Extending the same-model requirement for linked knowledge bases to external systems. Input: the knowledge base linking configuration. Compare: the model identifier recorded for each library. Observable result: libraries whose identifiers do not match are excluded and no cross-model retrieval is executed; the page does not compare missed recall across models.
- Treating a similarity score as a permission or entity filter. Input: the minimum relevance setting. Compare: the business ownership of returned records. Observable result: relevance filters low-scoring content only; it does not exclude unrelated businesses or unauthorized records, because retrieval is not authorization.
- Treating a pending review flag as granted authorization. Input: the review marker in a handover request. Compare: signature, cooperation reached and contract effectiveness as three separate facts. Observable result: a pending review does not show that operating permission is missing, and it does not show that any action was executed.
How to verify the setup
- Check one: input the hypothetical source text and the draft sentence above. Compare whether the draft sentence exceeds the after-sales support scope stated in the source text. The observable result is that the draft sentence is unsupported, and the evidence gap is recorded.
- Check two: input the identifiers of knowledge bases that share one vector model. Compare the model field of each library. The observable result is that non-matching libraries are excluded and no cross-model retrieval is executed; the check records the actual observation rather than a predicted runtime outcome.
- Check three: input an explicit paper-form empty reference array and compare the downstream reference path design. The observable result is that the path still runs when the reference length is zero, as documented for the output of the knowledge base search node. The page does not claim that a fictional rule search necessarily returns an empty array.
These checks state expected conditions without claiming that any test, deployment, approval or settlement has occurred. Where the documents do not provide an error code or an observed result, the comparison method and the unknown are recorded as they stand.