What the documents look like
Brand after-sales repair work turns on warranty responsibility and offline repair outlets, which separates it from e-commerce platform after-sales work that only processes refunds. Store service staff handle four material types at once: warranty cards, repair work orders, inspection reports and exchange approvals. Judging warranty scope, coordinating repair spare parts and approving returns or exchanges are the most time-consuming steps. These materials are produced per order and updated daily, so a multi-turn conversation must keep the subject, period and field values consistent across them to support store service and internal training questions.
Constraints at the multi-turn prompts step
Prompts for multi-turn dialogue need to state the material scope, the answering task and how to behave when evidence is missing. History records require checking which context is actually carried in, and distinguishing a new session from a continued session input. Question optimization in continuous knowledge-base dialogue requires checking reference resolution and question expansion, without assuming every short question qualifies. Model and length checks require confirming the model's supported context and reply settings, then testing long documents combined with follow-up questions. Reply format follows what downstream steps consume; selecting json_schema requires filling in the corresponding format requirement and verifying the returned structure.
Hypothetical drill sample: the original text of a store work order record in a brand after-sales system reads "Work order number A-1001, send-in date 2 March 2025, purchase date registered on the warranty card 10 January 2025, inspection report conclusion 'mainboard moisture damage, not human-caused', exchange approval status 'pending review'." A proposed draft sentence reads "This work order has passed exchange approval and an exchange can be arranged." This sample is used to check whether the prompt answers according to the original status.
Configuration and implementation checks
| Configuration item | Relevant role on this page | How to check |
|---|---|---|
| AI model | Determines context length and multimodal capability | Compare the maximum context and tool-calling information shown in the dialog |
| Memory turns | Controls how many prior turns are carried in | Hypothetical starting point of 3 turns, compared against the work order's cross-turn follow-up needs |
| Reply limit | Restricts the length of a single reply | Compare against the need to present a long inspection report passage in full |
| Temperature | Affects answer stability | Use a lower value for service scenarios, compared against rule-clear scenarios |
| Reply format | Determines answer structure | When a downstream node reads fixed fields, select json_schema and fill in the format requirement |
| Multimodal recognition | Reads image and similar inputs | Compare model capability against the options available in the configuration dialog |
Three common errors
- Treating "pending review" as already approved. In the sample the exchange approval status is "pending review," while the draft sentence states "has passed exchange approval." The two values are mutually exclusive on the same field, which is a contradictory statement.
- Treating a larger memory-turn count as always better. A larger count carries in more content, which may increase consumption and affect response speed, so it must be compared against the actual scope of the work order's cross-turn follow-ups.
- Treating similarity as a permission filter. A relevance score does not carry entity or permission isolation, and retrieval results cannot substitute for the authorization judgment on exchange approval.
How to verify the setup
- Input the sample original text and the draft sentence, then compare whether "pending review" and "has passed exchange approval" are mutually exclusive on the same field. A contradictory statement indicates the prompt does not constrain answers to the original status.
- Input the sample original text and one follow-up question, then compare whether the carried-in history turns cover the work order subject and date. If the send-in date or work order number is missing from the history, the memory-turn setting does not cover the required context.
- Input the sample original text and a request that requires fixed fields, then compare whether the returned structure includes fields such as work order number and approval status. If the returned structure lacks the agreed fields, the reply format configuration has not taken effect.