What the documents look like
On-demand retail fulfillment processes online orders by the minute, which sets it apart from periodic store inventory counting. Pick lists, out-of-stock reports, and delivery exception forms are generated per order, and product and marketing copy drafting has to search for usable evidence within these materials. Douyin on-demand retail, the Meituan or JD Daojia back office, store inventory, and rider tracking form the main data sources, and order and shortage records directly determine how far the copy can go. The typical parties are supermarket home-delivery stores, rider dispatch, and pickers, and the copy drafter needs to retrieve product specifications, substitution rules, and delivery wording from these documents.
For copy drafting, the material that matters most is the order record, the pick list, and the out-of-stock report, because these establish the product identity, the substitution object, the effective time, and the scope of validity. Delivery exception forms constrain what can be written about delivery status. The minute-level update frequency affects how current any retrieved statement is, and a draft that treats a single order's shortage handling as a general store rule reaches beyond what the materials support.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model, and knowledge bases with different vector models cannot be associated together. Retrieval first performs semantic, full-text, or hybrid recall, optionally fused through RRF and reordered by ReRank, then filtered by similarity and trimmed by the reference limit, and outputs a reference content array whose length can be 0. The minimum relevance value takes effect only under semantic retrieval or when result reordering is used, and it is a filtering threshold that does not perform permission or entity isolation. Question optimization is used for coreference resolution and question expansion and adds one model call. Image retrieval requires image input and the corresponding model capability, and reordering requires a model and must be enabled according to the settings.
Hypothetical paper exercise sample: the source material reads, "Starting 14:00 today, this store applies out-of-stock substitution to a 500 ml bottle of a certain brand of soda water; the substitute is the same specification in lemon flavor; the substitution requires the picker to check and confirm on the pick list; the delivery exception form must be reported back within 30 minutes after the rider picks up the goods." The draft sentence to be judged is "All beverages at this store can be substituted with lemon flavor, effective immediately upon ordering." The subject to verify is "500 ml bottle of a certain brand of soda water," the object is "same specification in lemon flavor," the state is "out-of-stock substitution starting 14:00," and the scope of validity is limited to this store, this day, and this single product. The draft sentence expands the subject and the effective scope, and the material does not support it.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Associate one store fulfillment document base | Check that its vector model identifier matches; exclude those that do not match, and do not perform cross-model retrieval |
| Search mode | Test semantic retrieval and full-text retrieval first | Compare the recalled content of the two modes against the test question, and do not presume one mode suits all materials |
| Reference limit | Set to 2000 tokens | This value is a starting point for this exercise; test content completeness with actual materials of different lengths and then adjust |
| Minimum relevance | Set to 0.4 | This value is a starting point for this exercise; label relevant and irrelevant samples first and then tune the threshold |
| Question optimization | Off initially | Compare the original question with the optimized question and check whether the subject has been altered incorrectly |
| Result reordering | Not enabled initially | Enable after a model is available and the setting is turned on, then compare the ordering change |
Three common errors
- Writing the out-of-stock substitution for the "500 ml bottle of a certain brand of soda water" as a substitution for all categories. The input is the draft sentence and the source material, the comparison is the subject scope, and the observed result is that the draft sentence covers products the material does not state.
- Treating the minimum relevance value as a permission or entity filter. The input is retrieval requests from different stores, the comparison is the returned content, and the observed result is that records from unrelated stores can still enter the reference array.
- Treating an out-of-stock report pending review as an approved substitution. The input is the status field of the report, the comparison is the status value, and the observed result is that the draft sentence uses substitution wording that has not been approved.
How to verify the setup
- Input the hypothetical source material and the draft sentence, and compare the subject, object, state, and scope of validity. The condition is met only when the draft sentence holds within "500 ml bottle of a certain brand of soda water," "same specification in lemon flavor," "starting 14:00," and "this store, this day." Anything beyond that is recorded as unsupported.
- Input the same test question through semantic retrieval and full-text retrieval respectively, compare the reference content arrays, and observe the recall difference between the two modes. When the array length is 0, check the downstream design against an explicit paper input of [], and do not claim that a fictional rule necessarily returns empty.
- Input a retrieval request containing an image, first check whether image input and the corresponding model capability are present, and then compare whether image description or image vector results appear. When the conditions are absent, record it as not executed, and do not infer a failure cause.
This page addresses only on-demand retail store fulfillment, product and marketing copy drafting, and knowledge base retrieval and recall. Whether a specific promotional sentence in product copy is supported by the material cannot be turned into a corporate identity certification tutorial.