What the documents look like
An MCN manages long-term account compliance for many creators across multiple brand engagements, so the material is spread out rather than tied to a single campaign. Four document types sit together: creator signing contracts, training records, violation handling forms and account schedules. The language of each document follows the creator and the platform location, so a single knowledge base can hold Chinese and English text side by side. Semantic retrieval is what carries cross-language matching here; the dataset engine documentation states that semantic retrieval supports cross-multilingual understanding, for example a Chinese question matching an English knowledge point.
A single contract may contain several signing parties and several validity periods, and a single violation handling form may sit in a pending-review, handled or appealed state. Material updates happen daily or weekly. The text visible on the retrieval side and the actual business state on the operations side do not stay aligned automatically, and retrieval does not carry that state.
Constraints at the vector indexes step
Knowledge bases associated for retrieval must use the same vector model. This is a stated input requirement of the knowledge base search node: one or more knowledge bases with the same vector model can be selected for vector search. When knowledge bases use different vector models they cannot be associated together. During implementation, check the model identifier first, exclude the ones that do not match, and record what was actually observed. Do not run a cross-model retrieval to compare missed recalls.
One original data block can be associated with multiple indexes. In the MongoDB dataset.datas table, the indexes field records the corresponding vector IDs as an array, so one group of data can correspond to multiple vectors. Indexes and original content are checked separately. Index content is built from complete and focused information, and retrieval coverage against index length is weighed with samples. Image retrieval depends on whether an image description or image vector index was generated at ingestion time; uploading an image at query time is not sufficient on its own.
Semantic recall and relevance scores do not carry permission or entity isolation. A retrieval action is not authorization.
Hypothetical drill sample: a creator signing contract ledger at an MCN contains one record whose original text reads "Signing entity: Xinglan Culture Media Co., Ltd.; creator account: @lingstyle; contract period: 1 March 2025 to 28 February 2026; status is pending review." The same ledger contains a training record whose original text reads "Training subject: @lingstyle; training date: 10 April 2025; languages: Chinese, English." A proposed handover request states: "Please confirm that the contract for @ling_style has taken effect, and arrange the account schedule on that basis." The request requires a judgment: pending-review status is not evidence that the contract has taken effect, and the existence of the training record does not fill that gap either.
Configuration and implementation checks
The table below lists only settings or implementation checks that are stated for this feature and this task. The values are starting points for this hypothetical trial, used to compare the same group of questions before and after, and are not official defaults.
| Configuration item | Hypothetical trial starting point | Reason and comparison method |
|---|---|---|
| Vector model of associated knowledge bases | Single base, single model; check the identifier first | The node requires associated bases to share a vector model; compare whether the model identifiers match |
| Index-to-original correspondence | One original block, multiple indexes | Check the indexes array against the original data block, record by record |
| Index content length | Build from complete and focused information | Use the same group of questions to compare recalled original text, observing the balance of coverage and length |
| Image index | Generate image description or image vector at ingestion | After an image is uploaded at query time, check whether the corresponding index exists at the ingestion side |
| Reference limit | Counted in tokens; starting point for this trial undecided | Chunk lengths differ widely in mixed knowledge bases; compare cited original text with the same group of questions |
| Minimum relevance | A 0-1 value; starting point for this trial undecided | Takes effect only in semantic retrieval or with result reranking; compare results before and after filtering |
RRF is the result fusion process after hybrid retrieval, not a standalone switch. Reranking requires a model and must be enabled by configuration. The optional paths in the overall flow do not mean every request executes all of them.
Three common errors
- Treating pending-review status as an effective contract. The input is the contract ledger text above. The comparison is between the field value "status is pending review" and the phrase "the contract has taken effect." The observable result is that these are different fields describing different facts; pending review does not show that the contract has taken effect, and it does not show a lack of operating authority.
- Treating the existence of a training record as supporting evidence that the contract has taken effect. The input is the training record text above. The comparison is between the training date and the contract period. The observable result is that the training record only shows that training occurred and does not state contract effectiveness; the claim is unsupported.
- Treating a semantic recall score as a basis for permission or entity isolation. The input is the same retrieval request. The comparison is between the recalled results and the authorized scope. The observable result is that a relevance score reflects semantic similarity only and does not exclude unauthorized records; retrieval does not constitute authorization.
How to verify the setup
- Input the contract ledger text above together with the proposed handover request. Compare "status is pending review" with "the contract has taken effect" in the request. The observable result is that the two do not agree, so the judgment is pending verification and the schedule arrangement is not executed.
- Input the training record text above. Compare the training date with the contract period. The observable result is that the training record does not state an effectiveness fact, so the judgment is unsupported and the evidence gap is kept open.
- Input the same retrieval request. Compare the recalled results with the authorized scope. The observable result is that a relevance score does not carry entity isolation, so retrieval does not constitute authorization, and business verification and authorization execution require a separate system implementation.
For empty-result handling, a paper input of [] can be used to check the downstream design; do not claim that a fictional rule retrieval necessarily returns []. After adjusting a model or index, compare cited original text using the same group of questions, and do not promise an effect from a vector score alone.