What the documents look like
Douyin storefront operations earn traffic through product cards and the store experience score, and the working rhythm differs from live-room operations. For inventory procurement and supplier records, the documents that enter the knowledge base are product qualification pages, experience-score details, shipping-violation appeals, and store announcements. Their sources are the Douyin store workbench, the Douyin e-commerce learning center, selected-alliance data, and logistics interfaces. Updates arrive daily and per order. In retrieval, these materials are organized into recallable fragments by subject, object, status, and validity scope.
A knowledge base is built from libraries, collections, and data. The smallest search unit is the library; collections only classify data and do not affect search results. The knowledge base search node can associate one or more knowledge bases that use the same vector model. A knowledge base search returns cited content as an array, and that array can have length 0, which means the output path still completes when nothing is found.
Hypothetical paper exercise sample. A merchant knowledge base holds a "Supplier Supply Record" whose source text reads: "The supplier for this record is Supplier A; the supply object is the summer mat category; the record status is submitted and pending review; the validity scope is 1 June 2025 to 31 August 2025." A second document, a "Store Announcement," reads: "This store suspends sales of summer mat category products from 10 June 2025." A proposed draft sentence reads: "Supplier A's summer mat supply record has passed review and supply may continue in July 2025." The phrase "has passed review" differs from the source status "submitted and pending review," so it remains to be verified.
Constraints at the retrieval step
Search modes are semantic retrieval, full-text retrieval, and hybrid retrieval. Hybrid retrieval merges multiple result paths through RRF, which is a fusion process, not a switch. The minimum relevance value is a filter threshold that takes effect only in semantic retrieval or when result re-ranking is used; it does not perform permission or entity isolation, and retrieval is not authorization. Question optimization performs reference resolution and question expansion and adds one model call before retrieval. Image retrieval requires image input and the corresponding model capability. Re-ranking requires a model and must be enabled by configuration. Optional paths shown in the documented flow do not mean every request executes all of them.
For this task, the material to check is the supply record's subject, object, status, and validity scope. A retrieved fragment carries the same status field wording as the source. Whether supply may continue is a separate business decision that needs its own downstream implementation for approval, database writes, and external synchronization. The announcement's effective date and the draft's supply period are compared as dates, not as a permission grant.
Configuration and implementation checks
| Configuration item | Value or check for this page | Basis and note |
|---|---|---|
| Associated knowledge bases | Associate the inventory procurement and supplier records library used for this task; check that each library's vector model identifier matches | The node can associate one or more knowledge bases using the same vector model |
| Search mode | Compare semantic, full-text, and hybrid retrieval on terms such as "Supplier A" and "summer mat category" in the sample | No single mode is assumed to suit all materials |
| Citation cap | Set a hypothetical trial starting value of 2000 tokens, then compare against the actual content length of shorter records | The unit is tokens; test content completeness with records of different lengths |
| Minimum relevance | Mark relevant and irrelevant fragments in the sample first, then set a hypothetical trial starting value of 0.4 and compare filtering effects | Takes effect only in semantic retrieval or with result re-ranking |
| Question optimization | Compare the draft sentence against the source on subject, object, status, and validity scope | Used for reference resolution and question expansion; check whether the subject was altered |
| Result re-ranking | When enabled by configuration, compare the re-rank score against the minimum relevance value | Re-ranking requires a model and must be enabled by configuration |
Three common errors
- Treating "submitted and pending review" as "has passed review." In the sample, the source status is submitted and pending review while the draft says it has passed review. Same subject, same object, same field, mutually exclusive values: that is a contradiction. Writing "under review" would be unsupported rather than contradictory.
- Treating a retrieval hit as authorization to execute. The sample record's validity scope ends 31 August 2025. Finding that record does not permit continued supply; supply, approval, database writes, and external synchronization each need their own downstream implementation.
- Associating knowledge bases that use different vector models. The node requires the same vector model. Check the identifier first, exclude non-matching libraries, and record what is observed. Do not infer missed recall, redundancy, or any runtime result from the association itself.
How to verify the setup
- Input the sample "Supplier Supply Record" source text and the draft sentence, compare "submitted and pending review" against "has passed review," and observe whether the retrieval result recalls that record fragment. The condition is met when the recalled content contains the source wording of that status field. If only the announcement fragment is recalled, record that the field is not covered.
- Input the sample "Store Announcement" source text and the draft sentence about continuing supply in July 2025, compare the announcement's effective date against the draft's supply period, and observe whether the announcement fragment is recalled. The condition is met when the recalled content contains "This store suspends sales of summer mat category products from 10 June 2025." If it is not recalled, record the item as pending verification.
- Input a paper-level empty result
[]and check the downstream node's design for handling cited content of length 0, observing whether the output path continues. The condition is met when the downstream design accepts an empty citation. This is a paper check and no actual test is claimed.