What the documents look like
Creator sales campaigns center on external creator fulfillment and commission settlement rather than internal brand scheduling. Store service and internal training teams work from four recurring materials: creator cooperation agreements, commission setup forms, sample shipment forms, and livestream performance reports. These materials refresh per livestream and weekly, and store staff need to turn cooperation terms, sample status, and settlement wording into conversational material that supports follow-up questions.
Compared with brand self-broadcasting, the conversational material here more often concerns the fulfillment status of an external party. In training scenarios, staff ask consecutive questions about whether a sample was sent, whether a commission rate was confirmed, and whether performance data has been returned. The multi-turn prompt task is to have the model answer from the existing materials and keep anything the materials do not state as pending verification.
Constraints at the multi-turn prompts step
Prompts must state the material scope, the answering task, and how to handle missing evidence. The model must not supply commission rates, settlement times, or authorization states that the agreement does not record. For history, when continuing a conversation, check the context actually carried in, and distinguish the input differences between a new session and a continued session. Question optimization applies only to knowledge-base continuous-conversation scenarios, where coreference resolution and question expansion are checked; short questions are not all covered.
For model and length, check the context length and reply cap the selected model supports, and test long documents combined with follow-up questions. Choose the reply format according to downstream needs; when selecting json_schema, fill in the corresponding format requirements and verify the returned structure.
Hypothetical drill sample: the source text reads, "Creator A and Brand B signed a creator cooperation agreement on March 1, 2026, agreeing a campaign commission rate of 20%; the sample shipment form shows the sample was sent on March 3, 2026; the livestream performance report shows the livestream completed on March 10, 2026, with transaction amount pending verification." The draft sentence to be judged is, "Creator A's commission has been settled in full at 20%." Compared with the source, the agreement records only the commission rate, not that settlement is complete. The draft sentence lacks settlement-completion evidence, so it must be marked pending verification and must not be output as a completed fact.
Configuration and implementation checks
| Configuration item | Hypothetical test starting point | Reason and comparison method |
|---|---|---|
| Memory turns | Keep a small number of history turns | Store training dialogue needs to reference earlier cooperation terms; compare with a single-turn answer that keeps no history and observe whether follow-ups correctly cite prior text |
| Reply cap | Set according to training instruction length | Complete operating instructions must be produced; compare with a truncated reply and observe whether the instruction is complete |
| Temperature | Low | Store service and internal training are rule-defined scenarios; compare with a higher value and observe whether answers stay stable |
| Reply format | Plain text | No downstream node currently reads a fixed structure; compare with json_schema and confirm whether the returned structure meets downstream needs |
| Multimodal recognition | Enable according to model capability | Check when materials contain image-type screenshots; compare with the disabled state and observe whether image content is read |
| Hide AI output | Keep off | Training scenarios need staff to see the answer; compare with the enabled state and confirm whether output can still be processed by downstream nodes |
These values are hypothetical test starting points, not official defaults. Each item must be compared against a control value and the observation recorded.
Three common errors
- Treating the commission rate recorded in the agreement as settlement-completion evidence. The source states only the rate, not the settlement status, so a draft sentence outputting "settled in full" supplies a business fact. Check method: input the agreement source text and the draft sentence, compare whether the agreement records a settlement-completion field, and mark it pending verification if not recorded.
- Treating the shipment form's sent status as a received status. The source shows only a send date, not a receipt record. Check method: input the shipment form source text and a draft sentence about receipt, compare whether a receipt field exists, and keep it unsupported when missing.
- Treating a commission setup form pending review as an effective configuration. Pending review does not equal approval. Check method: input the setup form status field and the draft sentence, compare whether the status value is effective, and do not output it as effective when the status is pending review.
How to verify the setup
- Input the agreement source text, the shipment form source text, and the draft sentence "Creator A's commission has been settled in full at 20%" from the hypothetical sample. Compare whether the agreement records a settlement-completion field. If the agreement records only the rate and not the settlement status, the model output should be marked pending verification and must not be output as a completed fact.
- Input the shipment form source text from the hypothetical sample and the draft sentence "The sample has been received." Compare whether the shipment form records a receipt record. If it has only a send date and no receipt field, the model output should remain unsupported.
- Input the commission setup form status field from the hypothetical sample and the draft sentence "The commission setup is effective." Compare whether the status value is effective. If the status is pending review, the model output should be marked pending verification and must not be output as an effective configuration.
The above is a paper check, not an actual run. Retrieval and similarity do not handle permission or entity isolation, and retrieval results do not constitute authorization. For empty-result handling, use the paper input [] to check the downstream design, without claiming that a fictional rule retrieval necessarily returns empty. Libraries across different vector models cannot be associated together; first check identifiers and exclude those that do not match.