Multi-store management: multi-turn prompts for after-sales questions

Review multi-turn prompts for after-sales questions in Multi-store management. Check input mappings, source evidence and failure handling before use.

What the documents look like

Multi-store matrix operations depend on four document families: store authorization lists, price control tables, cross-store complaint forms, and monthly sales reports. These materials update daily and monthly. In order fulfillment and after-sales support, a single consumer may place an order in one store and raise a question in another, so a request can touch authorization scope, price consistency, and shipping attribution at the same time. The practical difficulty is that any answer must cite the correct store's records and must not apply one store's price or authorization status to a different store.

The multi-turn prompts step exists to write down the material scope, the answering task, and the handling of missing evidence, so the model responds according to what the authorization list and price control table actually record. Daily and monthly updates create a second difficulty: the more history a conversation carries, the more likely an answer cites an old value that a later update has replaced. Memory turns control how many earlier chat rounds the AI references at most. A value that is too small cannot use prior context; a value that is too large brings in more content and can raise consumption and slow responses. Customer service and knowledge-base question answering normally keep only a small number of history turns. The response limit controls the maximum length of a single reply; a low setting can cut the reply short, and a high setting increases consumption. A lower temperature suits customer service and rule-bound scenarios. The response format is changed only when a downstream process needs to read a fixed structure, and selecting json_schema requires filling in the corresponding format requirement. In multi-turn dialogue, when chatId is a non-empty string the system takes the session from the database and uses the last item of the messages array as the user question while ignoring the remaining messages; when chatId is not passed, the context feature is not used.

Constraints at the multi-turn prompts step

The authorization list and price control table are the two documents that decide whether a draft sentence or a handover request can be supported. A statement about authorization must match the subject recorded in the authorization list. A statement about price must match the store that the price control table records. When a record is absent, the correct outcome is a missing-evidence outcome, not a denial and not a conflict.

Hypothetical paper exercise sample. The material text provided for comparison reads: "The store authorization list records that Store A is an authorized store, with authorization valid until December 31, 2026; Store B is not listed in the authorization list. The price control table records that the suggested retail price of the product at Store A is 199 yuan, and Store B has no record." One draft sentence to be judged reads: "Store B is an authorized store, priced at 199 yuan." This draft sentence is inconsistent with the records in the authorization list and the price control table and is judged unsupported. The sample is a paper exercise only; no test, approval, or business action has been performed.

Retrieval and similarity scores do not perform authorization or entity isolation. A relevance score is not a category, entity, or permission filter, and it does not exclude unrelated businesses or unauthorized records. Retrieval is not authorization. Knowledge bases that use different vector models cannot be associated together; identifiers must be checked first and non-matching bases excluded. Forms collect values; business verification, approval, database writes, and external synchronization require their own downstream implementation.

Configuration and implementation checks

Configuration itemHypothetical trial starting value for this exerciseComparison method
Memory turnsKeep a small number of history turnsCompare against the document note that customer service applications normally keep a small number of turns; compare whether different turn counts cause an expired price record to be cited
TemperatureLowerCompare against the document note that customer service and rule-bound scenarios suggest a lower value; compare whether repeated answers to the same question stay stable
Response limitSet according to the required answer lengthCompare against the document note that a low setting truncates; compare whether a long explanation is output completely
Response formatKeep defaultChange to json_schema only when a downstream process needs a fixed structure, fill in the format requirement, then check the returned structure
Multimodal recognitionDecide according to model capabilityThe dialog shows options according to model capability; when the model does not support a type, the corresponding option is not provided
Hide AI thinkingDecide according to debugging needWhen enabled, the user sees only the final answer; during debugging it can be temporarily disabled to observe intermediate thinking content

The values in the table are hypothetical trial starting points for this exercise, chosen according to the document notes. The comparison object is the actual output of the same workflow under different values. They are not official default values.

Three common errors

  1. Accepting the draft sentence "Store B is an authorized store" at face value. The authorization list records that Store B is not listed, and the price control table has no record for Store B. The check compares whether the subject of the draft sentence matches the subject recorded in the authorization list, and observes whether the draft sentence states an authorization status that the list does not contain.
  2. Answering a Store B after-sales question with Store A's price record. The price control table records only Store A's suggested retail price of 199 yuan, with no record for Store B. The check compares whether the store the question points to is the same subject as the store that owns the price record, and observes whether the answer applies Store A's price to Store B.
  3. Treating an old price carried in a chatId session as the current valid value. The price control table updates daily and monthly, and an excessive number of history turns can cause an answer to cite a value that has been replaced. The check compares the price cited in the answer with the current price control table record, and observes whether a value inconsistent with the latest record appears.

How to verify the setup

  1. Input the hypothetical material text above together with the draft sentence "Store B is an authorized store, priced at 199 yuan," and compare the subject of the draft sentence with the records in the authorization list and price control table. The expected phenomenon is that the draft sentence is judged unsupported, and no conclusion about Store B's authorization or price is output.
  2. Input an after-sales question that points to Store B's price, and compare the store the question points to with the store that owns the price control table record. The expected phenomenon is that the answer states Store B has no price record and does not cite Store A's 199 yuan.
  3. Within a chatId session, ask follow-up questions in sequence and compare the price cited in the answer with the current price control table record. The expected phenomenon is that the answer cites a value consistent with the latest record, and an old value under the history turn setting is not treated as the current value.

The above is a paper comparison and has not been executed. A pending request is not approval, an offered option is not execution, and an unsigned termination is not a completed termination. Where a document field is not provided, it remains unknown.