What the documents look like
Complaint and regulatory reply work faces a platform or a regulator, so the material must carry formal evidence and remediation wording. This differs from after-sales repair or reshipment communication, where the exchange stays between the shop and the buyer. The daily documents are complaint tickets, regulator inquiry letters, order evidence, and remediation reports. Sources include the 12315 platform, platform complaint centers, customer service chats, and the order system. Updates are irregular and per case, and the feature on this page does not depend on a batch synchronization mechanism.
In this setting, multi-turn dialogue carries the continuous follow-up of order fulfillment and after-sales questions. Which prior turns are brought into context, and how a new session differs from a continued session, decide whether an answer cites order facts already present in the current complaint case. The update frequency of source material does not change the prompt configuration itself, so it is not expanded here.
Constraints at the multi-turn prompts step
The prompt must state the material scope, the answering task, and how to handle missing evidence. The model must not write in business facts that the material does not contain. The history record must be checked against the context actually brought in, separating a new session from a continued session. Where a knowledge base needs continuous dialogue, check pronoun resolution and question expansion; short questions do not all qualify. Model and length settings must be checked against the supported context and reply settings, testing long documents combined with follow-up questions. Reply format follows the downstream consumer; when json_schema is selected, fill in the matching format requirement and verify the returned structure.
Hypothetical drill sample
Material text for checking (hypothetical, not a real record):
"Complaint ticket A-001. The complainant claims order D-100 was signed for on March 2, 2025, and the outer packaging was damaged. Ticket status is awaiting supplementary evidence. Regulator inquiry letter R-007 requires the shop to explain its after-sales handling process within a specified period."
One draft sentence to be judged (hypothetical): This shop confirms order D-100 was refunded as agreed, and the complainant's claim does not hold.
The subject, object, and status needed for the judgment sit in the same material: the ticket status is awaiting supplementary evidence, and the material records no refund record or handling conclusion. The draft sentence goes beyond the material scope and is unsupported.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| Memory turns | Keep a small number of history turns | Customer service and knowledge base question answering applications usually keep a small number of history turns; compare with a single-turn answer that carries no history, and observe whether the current ticket's earlier text is cited |
| Temperature | On the low side | Customer service and knowledge base question answering suggest a low value; compare answer stability against a higher setting |
| Reply limit | Enabled with a moderate cap | Lower it when a short remediation note is needed; compare against no limit to see whether the reply is cut off |
| Reply format | Default | Ordinary customer service question answering keeps the default; change to json_schema only when a downstream process reads a fixed structure |
| Multimodal recognition | Decided by model capability | Enable image recognition when the model supports images; compare against leaving it off to see whether a screenshot is read |
| Hide AI thinking | Turned off temporarily during debugging | During application debugging, turn it off temporarily to observe intermediate thinking content |
These are starting points for this hypothetical exercise, not official default values. The configuration dialog shows available items according to the current model's capability; a model that does not support multimodal recognition does not offer that option.
Three common errors
- Treating retrieval similarity as a permission or entity filter. Similarity is a ranking reference and does not exclude unrelated business or unauthorized records. Check the retrieval scope identifier and the authorization boundary, and observe whether the returned content matches the target ticket.
- Treating the display configuration returned by an interaction node as already executed. The interaction node returns type and params and waits for user input; a form collecting values does not mean business verification, approval, or a database write has completed. Compare whether the returned interactive field and the chatId of the follow-up request are consistent.
- Treating the thinking budget as the citation token limit. The thinking budget controls model thinking intensity and has no relation to knowledge base citation length. Compare the reasoning_effort setting and the actual reply length setting, and record them separately.
How to verify the setup
- Enter the hypothetical material text above together with the draft sentence, and compare whether the draft sentence goes beyond the ticket status and refund facts recorded in the material. If the answer rewrites "awaiting supplementary evidence" into "refund completed," the answer does not meet the requirement; if the answer states that the material records no refund record, it meets the requirement.
- Enter a hypothetical chatId and a continued-session request, and compare the difference in history turns brought in between a new session and a continued session. If the continued session cites earlier text from the same ticket and the new session does not, the behavior matches the expectation; if the content brought in by the two cannot be distinguished, record it as pending verification.
- Enter a hypothetical empty-citation paper input [] and compare whether the downstream design handles an empty result as empty. If the downstream treats the empty result as having content and continues generating a business conclusion, it does not meet the requirement; if the downstream preserves the empty state, it meets the requirement.
All of the above is a paper check. No actual request was executed, and this does not constitute a test, deployment, or approval conclusion. The first hit of a retrieval result, full recall, or an empty return for an unrelated query is not guaranteed. Libraries across different vector models cannot be associated together; check the identifier only, exclude those that do not match, and record the actual observation.