Douyin storefront operations: model connections for product questions

Review model connections for product questions in Douyin storefront operations. Check input mappings, source evidence and failure handling before use.

What the documents look like

Douyin storefront shelf operations center on product cards and the store experience score. The working materials for this category are product qualification pages, experience score detail sheets, shipping violation appeals, and store announcements. Qualification pages change as products are listed, delisted, or approach the end of a validity period. Experience score detail accumulates order by order. Shipping violation appeals arise from out-of-stock and no-stock situations. Announcements are issued by the store itself.

For product information and selection questions, the relevant material is the qualification page, because it carries the subject, the object, the validity range, and the status fields that a selection question depends on. Fields the page does not state remain unknown. A model connection does not add facts that the source material does not contain, and a retrieval hit does not convert an unstated model number into a supported one.

Constraints at the model connections step

Model access depends on AI Proxy. Both the App service and the Admin service must set AIPROXY_API_ENDPOINT and a non-empty AIPROXY_API_TOKEN; a missing value in either one causes startup validation to fail. AIPROXY_API_ENDPOINT takes the service root address and does not carry a /v1 suffix. The system needs at least one language model and one index model to operate. Model types are language, index, rerank, speech synthesis, and speech recognition. Image retrieval requires the corresponding image input and model capability. Rerank requires a rerank model that is present and enabled according to configuration. Retrieval and similarity scores do not perform permission or entity isolation, and a retrieval result is not an authorization. Libraries built on different vector models cannot be associated together; the identifiers must be checked first and non-matching libraries excluded. Model probing covers only enabled system models; disabled models are not probed and produce no history.

Hypothetical drill sample: a Douyin store merchant on 10 March 2026 reviews a product qualification page whose text reads, "The quality inspection report for this store's product A is valid from 1 January 2026 to 31 December 2026, and applies to models A-100 and A-200." The draft sentence to be assessed reads, "The quality inspection report for product A covers model A-300." The source text does not state A-300, so the draft sentence is unsupported. A separate handover request reads, "Please generate selection questions for A-300 based on this qualification page." That request falls outside the stated validity scope, remains a matter to be verified, and does not constitute authorized execution.

Configuration and implementation checks

Configuration itemHypothetical starting value for this pageReason and comparison object
AIPROXY_API_ENDPOINTHypothetically set to http://aiproxy:3000The document requires the root address; compare whether a /v1 suffix is appended
AIPROXY_API_TOKENHypothetically set to a non-empty administrator tokenThe document requires a non-empty value matching the server side; compare whether it is empty
Language modelHypothetically one language model enabledThe document requires at least one; compare whether one is enabled
Index modelHypothetically one index model enabledThe document requires at least one; compare whether one is enabled
Model probe intervalHypothetically set to 30 minutesThe document supports integers from 5 to 60 minutes; compare whether the value falls in that range
Retrieval scopeHypothetically limited to the product qualification pageRetrieval does not carry permission isolation; compare whether a separate authorization source exists

The values above are hypothetical starting points for this page and are not official defaults. The table lists only documented settings or implementation checks related to this page's feature.

Three common errors

  1. Treating a draft sentence as a confirmed conclusion. The sample source text states only A-100 and A-200, while the draft sentence states A-300. The input is the source text and the draft sentence; the comparison is the model number field; the observable result is that the model number is not stated, which must be recorded as unsupported.
  2. Treating a retrieval hit as authorized execution. The sample handover request asks for selection questions for A-300. The input is the request and the source text; the comparison is the object scope; the observable result is that A-300 is outside the stated scope, which must remain pending verification.
  3. Treating a similarity score as an entity or permission filter. The input is a retrieval result; the comparison is whether it carries a permission field; the observable result is that similarity provides no permission judgment, and an authorization source must be checked separately.

How to verify the setup

  1. Input the sample source text and the draft sentence; compare whether model number A-300 appears in the source text; when it does not appear, record the draft sentence as unsupported and do not substitute a similarity score.
  2. Input the sample handover request and the source validity range; compare whether the requested object falls within 1 January 2026 to 31 December 2026 and within A-100 and A-200; when it falls outside, record it as pending verification and do not execute generation.
  3. Input a retrieval result; compare whether the result carries a permission identifier; when no permission identifier is present, record the gap, do not treat the retrieval result as authorization, and do not claim that retrieval under an invented rule necessarily returns empty.