What the documents look like
Channel diversion review covers regional and price order. It does not cover rebate amounts, which belong to rebate accounting. The material sources are the anti-counterfeit code system, e-commerce platform prices, distributor shipment records and market inspections. In the store service and internal training setting, multi-turn prompts carry the job of turning complaint forms, anti-counterfeit code records, penalty notices and investigation photos into a checkable question-and-answer sequence. Materials update weekly or irregularly, so any evidence quoted in a conversation needs a stated time range. A single inspection result does not stand in for a whole quarter.
The most time-consuming steps are tracing the goods source code, comparing low-price shops and executing penalties. Each step produces a different document with a different status, and the conversation has to keep those statuses apart. A shipment record, an inspection photo and a signed penalty notice are not interchangeable evidence.
Constraints at the multi-turn prompts step
The prompt has to state the material scope, the answering task and the handling of missing evidence, so the model does not write business facts that no document supports. History records need checking against the context actually carried in, and a new session has to be distinguished from a continued session. Where a knowledge base conversation runs across turns, check reference resolution and question expansion rather than assuming every short question works the same way. Model and length settings need checking against the supported context and reply settings, then tested with long documents combined with follow-up questions. Reply format follows what the downstream step consumes; when json_schema is chosen, the format requirement is filled in and the returned structure is verified.
A clearly labelled hypothetical drill sample follows. The material text is: "In March 2024, a dealer in Region A shipped 200 units to a store in Region B, anti-counterfeit code range 100001–100200; in April 2024 an inspection photo shows goods with the same code range on the store shelf in Region B, priced 15% below the suggested retail price for Region A." The draft sentence to be judged is: "The Region A dealer diverted 200 units to the Region B store in March 2024, this constitutes diversion, and a penalty should be executed." The draft sentence merges the shipment record, the inspection price and a penalty conclusion into one statement. The penalty notice is not signed, and the penalty is at the pending review stage. The draft sentence treats a pending penalty as an executed one.
Configuration and implementation checks
| Configuration item | Value or check on this page | Relation to the sample |
|---|---|---|
| AI model | Select a model with the required context length; check the maximum context shown in the dialog | The sample contains several materials and needs room for follow-ups |
| Memory rounds | Hypothetical trial starting value 4 rounds, compared with the 3-round question and answer in the sample | Starting reason: the sample dialogue is short, so observe whether earlier text is dropped |
| Reply cap | Hypothetical trial starting value 800, compared with the length of the sample draft sentence | Starting reason: the draft sentence is short, so observe whether truncation occurs |
| Temperature | Hypothetical trial starting value low, compared with stable restatement of the sample | Starting reason: review question and answer needs stability |
| Reply format | Keep default; when a downstream step reads a fixed structure, choose json_schema and fill in the format requirement | The sample draft sentence is free text |
| Multimodal recognition | Enable image recognition only when the model supports it and the sample contains investigation photos | The sample contains an inspection photo link |
These values are hypothetical trial starting points for this page, not official defaults. Retrieval and similarity do not handle permission or entity isolation, and a retrieval result does not constitute authorization. The same vector model association requirement for a knowledge base does not extend to business registration sites or other external systems.
Three common errors
- Treating a retrieval hit as penalty authorization. In the sample, the inspection photo and the shipment record support only a pending verification. The penalty notice is not signed, so finding the material does not make the penalty executable.
- Treating the merged statement in the draft sentence as verified fact. The sample draft sentence writes shipment, price and penalty conclusion together, while the penalty sits at pending review. Review is not approval.
- Associating knowledge bases that use different vector models. If the sample involves several bases, check the identifiers first and exclude those that do not match. Do not run a cross-model retrieval to compare missed recall.
How to verify the setup
- Input the sample material text and the draft sentence. Compare whether the draft sentence presents the pending penalty as executed. The condition is met when the reply keeps the gap that the penalty notice is unsigned, and does not state that a penalty has been carried out.
- Input the sample three-round question and answer, then ask "Has this batch been penalized?" Compare whether the reply cites the signature status. The condition is met when the reply states that the penalty is pending review, and no penalty conclusion appears without a supporting document.
- Input the paper input [] for the empty-result handoff. Compare whether the downstream design handles an empty reference. The condition is met when the reply states that no reference was returned, and does not present a fabricated rule as a retrieved result. This checks the downstream design only; it does not claim that any real query returns an empty list.