What the documents look like
Peak-sale warehouse and delivery scheduling turns on short-term peak capacity and the arrangement of people, vehicles and yard space. The working materials are the peak-sale forecast table, staff shift schedules, courier support plans and exception daily reports. The typical parties are e-commerce supply chain staff, warehouse managers and courier commercial contacts. In store service and internal training, a multi-turn conversation has to carry forward follow-up questions about shift definitions, vehicle coordination and exception reporting. Too few memory turns drops earlier constraints; too many pulls in expired scheduling data. The materials update per event and per day. This page does not depend on a batch synchronization mechanism; it checks only the context actually carried into a single conversation.
A prompt needs to state the material scope, the answering task and the handling of missing evidence, so the model does not write in business facts. History has to be checked against the context actually carried in, separating a new conversation from a continued one. Question optimization is checked only for reference resolution and question expansion in continuous knowledge-base dialogue, without assuming every short question qualifies. Model and length settings are checked against the context and reply settings the model supports, testing long documents combined with follow-ups. Reply format follows the downstream consumer; when json_schema is selected, the corresponding format requirement is filled in and the returned structure is verified.
Hypothetical exercise sample: the source material reads "This peak-sale forecast table covers 1 November to 3 November. The East China warehouse temporary staff shift schedule has been submitted and is pending review. In the courier support plan, the vehicle for route A is in an intended-coordination state. The exception daily report has not yet been generated." The draft sentence to be judged is "The East China warehouse shift schedule has been approved and the route A vehicle has been secured." The source contains the subject, object, state and effective range, but "pending review" is not approval, and "intended coordination" is not execution.
Constraints at the multi-turn prompts step
The prompt must name the material scope, the answering task and what to do when evidence is missing. The model must not fill in business facts that the source does not state. A draft that upgrades "pending review" to "approved" or "intended coordination" to "secured" departs from the source wording and its stated limitations.
History is checked against the context actually carried into the turn. A new conversation and a continued conversation are distinguished by their inputs. The documented historyPreview field shows the turns actually included, so the check compares that list against the intended scope rather than assuming a fixed count.
Question optimization applies to continuous knowledge-base dialogue, where reference resolution and question expansion are checked. Short questions are not assumed to qualify in every case.
Model and length settings are checked against the context and reply settings the model supports, including tests that combine long documents with follow-up questions. Reply format is chosen according to the downstream consumer. When json_schema is selected, the corresponding format requirement is filled in and the returned structure is verified.
The documented thinking configuration controls reasoning effort, not a citation token ceiling. Simple status checks can use the no-thinking option; complex scheduling follow-ups can use a higher effort level where the model supports it. Hiding AI output is used when a downstream node rewrites the result; the user-visible content and the node output are then checked separately.
Configuration and implementation checks
| Configuration item | Setting relevant to this page | How to check |
|---|---|---|
| Memory turns | Hypothetical trial starting point of 4 turns, because the sample involves shift, vehicle and exception follow-ups; compare context completeness against 2 and 8 turns | Inspect the turns actually carried in through historyPreview |
| Reply cap | Hypothetical trial starting point of 800, because a short handover note is needed; compare truncation against 400 and 1600 | Check whether answer is truncated |
| Temperature | Hypothetical trial starting point of 0.3, because this is a rule-defined scenario; compare wording stability against 0.7 | Compare consistency across repeated answers |
| Reply format | Ordinary handover notes keep the default; when a downstream reader is needed, select json_schema and fill in the format requirement | Check the returned structure |
| Thinking configuration | Simple status checks use no-thinking; complex scheduling follow-ups use standard thinking where the model supports it | Check choices together with the thinking fields |
| Hide AI output | Enable when a downstream rewrite is needed, passing the AI reply output to the following node | Check user-visible content against the node output |
Three common errors
- Treating "pending review" as approval. The draft sentence says the shift schedule "has been approved," while the source says only "has been submitted and is pending review." The input is the sample source and the draft sentence; the comparison is the state field; the observable result is that the two do not match.
- Treating "intended coordination" as execution. The draft sentence says the vehicle "has been secured," while the source says "intended-coordination state." The comparison is the object state; the observable result is that execution is not shown.
- Treating retrieval similarity as an authorization filter. The input is a quoteList carrying similarity; the comparison is whether an authorization field is present; the observable result is that a score does not carry entity or permission isolation.
How to verify the setup
- Input the sample source and the draft sentence, compare "pending review" against "approved," and treat the condition as met when the draft sentence keeps the item pending verification.
- Input the sample source and the draft sentence, compare "intended coordination" against "secured," and treat the condition as met when the output does not claim execution.
- Input an explicit paper empty result [] and check whether the downstream design handles the empty result, treating the condition as met when no record is fabricated. All three are paper expectations and were not actually run.