E-commerce warehouse receiving: multi-turn prompts for after-sales questions

Review multi-turn prompts for after-sales questions in E-commerce warehouse receiving. Check inputs, failure paths and source evidence before use.

What the documents look like

Receiving and putaway is the first book-to-physical confirmation when goods enter the warehouse. Data comes from the WMS, ERP purchasing, supplier delivery notes and barcode scanning. The daily documents are the purchase arrival note, the receiving inspection sheet, the putaway task and the discrepancy report. Checking arrived quantities, printing barcodes and assigning storage locations are the time-consuming steps. Errors here produce inventory that does not match physical stock, later picking mistakes and supplier disputes. In this setting, multi-turn prompts carry order fulfilment and after-sales question answering, and every answer must rest on those documents and system fields. Where evidence is absent, the gap stays open.

For this page, the relevant facts are the document set, the account-versus-physical confirmation stage, and the consequence of mismatched stock. Update frequency does not change how prompts behave, so it is not treated as a configuration input here.

Constraints at the multi-turn prompts step

Multi-turn dialogue needs a controlled memory turn count. Customer service and knowledge-base question answering usually keep only a small number of earlier turns. The context actually carried into a session must be checked against the real conversation, and a new session must be distinguished from a continued one. A short question inside a continuing knowledge-base conversation may need reference resolution or question expansion; that treatment does not apply to every short question. The model maximum context and the reply cap together set the range for long documents combined with follow-up questions. Reply format follows what the downstream step needs; choosing json_schema requires filling in the corresponding format requirement and checking the returned structure. A retrieval similarity score is a degree of match, not a permission or entity filter, and retrieval results do not replace authorization.

Hypothetical drill sample. The purchase arrival note reads: "Supplier A delivered 100 units of product A on 10 March 2025, purchase order PO-20250301, receiving warehouse East China Warehouse No. 1." The receiving inspection sheet reads: "On 10 March 2025, 98 units of product A were actually received, a discrepancy of 2 units, the discrepancy reason awaits supplier confirmation, the inspector has signed." The draft sentence to be judged is: "All 100 units of product A have been inspected and put away, the discrepancy has been fully handled, and the supplier can be notified for settlement." Comparing the source text with the draft sentence, the actual receipt is 98 units and the discrepancy awaits confirmation; the phrases "all inspected and put away" and "discrepancy has been fully handled" lack support.

Configuration and implementation checks

Configuration itemHypothetical starting value for this trialReason and comparison method
Memory turnsHypothetical start of 3 turnsCustomer service applications keep a small number of earlier turns; compare against a continued-session follow-up asking for the discrepancy number, and observe whether prior text is cited
TemperatureHypothetical low startRule-bound order fulfilment answers need stable output; compare repeated requests for the same question
Reply capHypothetical start able to hold document field descriptionsMust cover arrival-note and inspection-sheet fields; compare against observed truncation
Reply formatHypothetical start kept at defaultNo downstream step reads a fixed structure; compare against a json_schema return structure check
Multimodal recognitionHypothetical start switched offThis task takes text documents as input; compare against the image-recognition condition
Thinking configurationHypothetical start at defaultSimple field checking does not need high thinking strength; compare against default output

Three common errors

  1. Treating a retrieval similarity score as a permission or entity filter. The score reflects degree of match only; it does not exclude unrelated business or unauthorized records, and the authorization scope must be checked separately.
  2. Treating values collected by an interactive-node form as business already executed. A form collects input values; business verification, approval, database writes and external synchronization each need their stated downstream implementation.
  3. Writing a pending discrepancy as fully handled. The inspection sheet states that the discrepancy reason awaits supplier confirmation, so the draft sentence "the discrepancy has been fully handled" lacks support.

How to verify the setup

  1. Input the purchase arrival note and receiving inspection sheet text given above, then compare the draft sentence "All 100 units of product A have been inspected and put away, the discrepancy has been fully handled" against the source facts of 98 units actually received and a discrepancy awaiting confirmation. The output meets the condition when it states that the sentence lacks support.
  2. Input the continued-session follow-up "What is the discrepancy number?" and compare whether, under the memory-turn setting, the earlier inspection-sheet information is cited. The output meets the condition when it either carries the prior text forward or states clearly that it was not brought in.
  3. Input an empty-result downstream case, with the paper input being []. Compare whether the downstream design handles it as an empty reference. The output meets the condition when it describes how the empty-reference case is carried forward, without claiming that a fictitious rule-based retrieval necessarily returns an empty list.