What the documents look like
Douyin storefront shelf operations rely on four recurring record types during inventory procurement and supplier data work: product qualification pages, experience score breakdowns, shipping violation appeals, and store announcements. These materials update daily or per order. A single supplier's qualification page may appear in different versions at different times, and a single order's shipping appeal may reference several logistics and inventory records. The vector model and index step determines whether these materials can be located accurately after ingestion.
Compared with livestream operations, shelf operations focus on product cards and store experience scores. Retrieval needs often land on specific qualification numbers, supplier names, and appeal statuses. Semantic retrieval handles natural-language phrasing; full-text retrieval is more direct for numbers, model designations, and proper nouns. FastGPT fuses both recall paths through RRF and optionally applies ReRank for secondary ordering. This distinction matters when deciding which index to build for which material and which search mode to use.
Constraints at the vector indexes step
Knowledge bases linked for retrieval must use the same vector model. When selecting multiple knowledge bases, first verify the actual model identifier and input type. Bases with mismatched identifiers cannot be linked together. This constraint applies only to the vector model itself and does not extend to business registration sites or other external systems.
One source data block can associate with multiple indexes. Indexes and source content are verified separately. Index content should be complete and focused; retrieval coverage and index length are weighed against samples. Image retrieval also depends on whether image description indexes or image vector indexes were generated at ingestion time. Uploading an image on the query side does not automatically mean it can be retrieved.
Node output is an array whose length can be zero. Even when no content is found, the output path still completes. Minimum relevance takes effect only under semantic retrieval or when result reranking is used. It is a filter threshold and does not perform entity isolation or permission filtering. Retrieval itself does not constitute authorization. Form value collection, business verification, approval, database writes, and external synchronization each require their own downstream implementation.
Hypothetical drill sample
Source text for comparison: "The food business license copy submitted by Supplier A on March 1, 2026, valid until February 28, 2027, covers product category A. The copy is marked 'for platform qualification review only.'"
Draft sentence to be assessed: "Supplier A has obtained supply authorization for product category A, valid until February 28, 2027."
The source text states only the license copy, its validity period, and its covered category. It does not state supply authorization. The draft sentence equates the qualification material's validity period with a supply authorization period, which is an unsupported inference.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this trial | Reason for selection and comparison method |
|---|---|---|
| Linked knowledge bases | Link only bases using the same vector model identifier | Verify model identifiers and input types first, exclude mismatched ones, do not run cross-model retrieval comparisons |
| Search mode | Hybrid retrieval | Materials contain supplier names and qualification numbers; both semantic and full-text paths need coverage |
| Reference limit | Set to 2000 tokens as the starting point for this trial | This is a paper starting point; compare results against different values under the same question set |
| Minimum relevance | Set to 0.3 as the starting point for this trial | This value takes effect only under semantic retrieval or result reranking; adjust after comparing against source text |
| Question optimization | Enabled for multi-turn follow-up scenarios | Single-turn explicit questions can disable it; compare reference content differences between the two settings |
| Index construction | Segment each material by complete semantic units | Index content is complete and focused; verify coverage against source text segment by segment |
All values in the table are hypothetical starting points for this trial, not official defaults. The reason column explains why the starting point was chosen; the comparison method explains what value it is compared against.
Three common errors
- Treating retrieval results as authorization evidence. In the hypothetical sample, the draft sentence writes the license copy's validity period as a supply authorization period. The input is the source text and the draft sentence. The comparison object is whether the source text states supply authorization. The observable result is that the source text does not state that fact. Retrieving qualification material does not equal obtaining supply authorization.
- Linking knowledge bases with different vector models. The input is the list of knowledge base identifiers to be linked. The comparison object is each base's vector model identifier. The observable result is that bases with mismatched identifiers should be excluded. The documentation does not describe runtime results after linking mismatched bases; only verify identifiers and record observations.
- Treating minimum relevance as permission filtering. The input is a low-relevance record belonging to another entity. The comparison object is whether that record appears before and after filtering. The observable result is that this setting does not perform entity isolation. Permission judgment requires a separate system implementation.
How to verify the setup
- For the hypothetical sample source text and draft sentence, input the draft sentence to execute retrieval. Compare whether the returned references include the sentence in the source text about the license validity period. The observable result is that reference content matches the source text and does not contain supply authorization wording. If the reference is not hit, record it as unsupported, not as a negation.
- For linked knowledge base identifiers, input the list of model identifiers for bases to be linked. Compare whether the identifiers are consistent. The observable result is that bases with mismatched identifiers are excluded. Do not run cross-model retrieval to compare missed recalls.
- For the empty-result path, input a clearly labelled paper input of an empty array. Compare whether downstream nodes accept it normally. The observable result is that the output path completes with length zero. Do not claim that a fictional rule retrieval necessarily returns an empty array.
All three verification items address the primary task of this page, use the complete hypothetical sample given above, and describe expected results as paper reasoning that was not actually executed.