What the documents look like
Fresh-food weighing and sorting happens inside the warehouse fulfillment step, and the central facts are weight and specification. Source systems named in the brief are WMS, electronic scales, the order system and quality-inspection photos. The daily documents are sorting task sheets, weighing labels, underweight compensation forms and inspection records, with updates per order and per day. In store service and internal training, a multi-turn conversation repeatedly refers back to these materials. A sorter asks about the specification on a task sheet, an inspection supervisor follows up on the review status of a weighing label, and a service agent checks the handling progress of an underweight compensation form. Each document has its own subject, object, status and validity scope, so a prompt must state the material scope and leave evidence gaps open rather than fill them.
Constraints at the multi-turn prompts step
Multi-turn dialogue depends on the context carried by history. A new session and a continued session take different inputs. For a continued session, the chatId retrieves the session from the database, the last element of the messages array is used as the user question, and the remaining messages are ignored. The prompt must state the answering task and the material scope, and must not let the model write business facts that are not in the materials. Question optimization is checked for reference resolution and question expansion only in the knowledge-base continuous-dialogue setting, and short questions are not all covered. For model and length, the supported context and reply ceiling need to be checked against long documents combined with follow-up questions. The reply format follows what the downstream step consumes; when json_schema is selected, the matching format requirement is filled in and the returned structure is verified. Retrieval is a fetch process and does not perform authorization checks; a similarity score is not a permission or entity filter.
Hypothetical paper exercise sample, for checking only and not a real record. Sorting task sheet text: "Task sheet A-0417, item is loose apples, specification requires a single-portion net weight of 500 grams, sorter Zhang San, status is pending sorting, validity scope is limited to 17 April of the current day." Weighing label text: "Label T-0417-08, corresponding task sheet A-0417, weighed value 480 grams, review status is not reviewed." Draft sentence to be judged: "Task sheet A-0417 has completed sorting, and the 480-gram weight meets the specification requirement." Comparing this draft with the source text: the task sheet status is pending sorting, the weighed value of 480 grams is below the 500-gram specification requirement, and the review status is not reviewed, so the draft sentence is not supported.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Memory turns | Set to 2 turns for this exercise | Store service and training settings keep a small number of history turns; compare with 0 turns and observe whether a follow-up can cite the task sheet number from the previous turn |
| Reply ceiling | Opened and set to a short length for this exercise | Short answers are wanted; compare with an unlimited length and observe whether the reply is cut off early |
| Temperature | Set to a low value for this exercise | A rule-based checking setting needs stable answers; compare with a higher value and observe whether the same input gives consistent answers |
| Top_p | Left off or at default for this exercise | Temperature has already been adjusted, and the two parameters are not adjusted together |
| Reply format | Left at default for this exercise | No downstream step currently reads a fixed format; if a later node needs a fixed structure, json_schema is selected and the format requirement is filled in |
| Hide AI thinking | Opened for this exercise | Store service and training show only the final answer; during debugging it can be temporarily turned off to observe intermediate thinking |
These values are hypothetical starting points for this exercise and are not official defaults. The final values for memory turns, reply ceiling, temperature and Top_p need to be decided after comparing actual model capability and dialogue results. The multimodal recognition option depends on model capability, and when the dialog does not show the matching option, that configuration is not provided.
Three common errors
- Writing a pending-sorting status as completed sorting. The input is the task sheet A-0417 source text and the draft sentence "Task sheet A-0417 has completed sorting." Comparing the task sheet status field, the source text says pending sorting and the draft says completed, and the two values are mutually exclusive on the same field. The observable result is that the draft contradicts the source text and needs correction.
- Judging the 480-gram weighed value as meeting the 500-gram specification requirement. The input is the weighing label T-0417-08 source text and the phrase "meets the specification requirement" in the draft. Comparing the weighed value with the specification requirement, 480 grams is below 500 grams. The observable result is that this judgment is not supported.
- Treating a not-reviewed status as reviewed. The input is the review status field in the weighing label source text, "not reviewed," and the reviewed conclusion implied by the draft. Comparing the review status field, the observable result is that the draft lacks supporting evidence and the item remains to be verified.
How to verify the setup
- Check that history is carried in. The input is task sheet A-0417 and weighing label T-0417-08 from the hypothetical sample, with the follow-up question "what is the weighed value on this task sheet" sent in a continued session. Compare whether the reply cites 480 grams. The observable result is that history carry-in works when the reply cites that value, and when the reply does not cite it, the chatId consistency needs to be checked.
- Check the reply format and structure. The input is the draft sentence from the hypothetical sample, sent after json_schema is selected and the format requirement is filled in. Compare whether the returned content matches the filled structure. The observable result is that the format configuration works when the structure matches, and when the return is plain text, whether the format configuration was saved needs to be checked.
- Check the empty-result handoff. The input is a paper empty quote list []. Observe whether the downstream node handles it as designed for an empty result. Compare whether the downstream output contains unsupported business facts. The observable result is that the handoff design is usable when the downstream does not add business facts. The retrieval check records only actual observations and does not guarantee a first-hit or full recall. Libraries using different vector models cannot be associated together, so identifiers are checked first and non-matching ones are excluded.