What the documents look like
Multi-store matrix operations keep four recurring materials: the store authorization list, the price control table, the diversion complaint form, and the monthly sales report. Compared with single-store advertising, cross-store authorization and price order carry the main weight, while single-store traffic efficiency sits lower. These materials come from platform merchant back offices, ERP channel pricing, brand anti-counterfeit systems, and dealer reports, and they update on daily and monthly cycles. In store service and internal training, a support agent or channel operator answers questions about authorization status, price ranges, and complaint progress from these materials. Prompts and multi-turn dialogue have to be organized around the same documents.
Two features of this material shape the prompt work. First, authorization is scoped by subject and channel, so a fact about one store does not transfer to another. Second, complaint records carry a status field, and a status such as pending review is a stage, not a conclusion. A prompt that asks the model to fill gaps will produce statements the source documents do not support.
Constraints at the multi-turn prompts step
Multi-turn context comes from the history actually carried into the request. A new session and a continued session take different inputs, and the prompt has to state the material scope, the answering task, and how to handle missing evidence, so the model does not write business facts on its own. When a knowledge base supports continuous dialogue, verify reference resolution and question expansion rather than assuming every short question needs them. Model context length and reply settings need testing together with long documents and follow-up questions. Reply format follows downstream needs; when json_schema is selected, fill in the corresponding format requirement and verify the returned structure.
Hypothetical paper exercise. The store authorization list reads: "Authorized store A, authorization period 1 January 2025 to 31 December 2025, authorization scope limited to the Tmall platform." A diversion complaint form reads: "Complaint target is store B, complaint status is pending review, complaint date 10 March 2025." A proposed draft sentence reads: "Store B has been confirmed for diversion and its authorization will be terminated." Question: does the draft sentence match the materials? The authorization list covers only store A and its scope. The complaint form states only that store B is pending review. Neither document records that store B has been confirmed for diversion or that any authorization has been terminated. The draft sentence lacks supporting evidence and remains unverified.
Configuration and implementation checks
The settings below relate to this page's task. Numeric values are starting points for this hypothetical exercise, not official defaults.
| Configuration item | Starting point for this hypothetical exercise | Reason and comparison method |
|---|---|---|
| AI model | A model documented as supporting multimodal input and tool calling | Compare the maximum context and tool-calling capability stated for the model, and confirm it can read authorization list and complaint form text |
| Memory rounds | Set to 3 rounds | Support and knowledge base Q&A applications usually keep a small number of history rounds; compare whether a follow-up question carries the earlier authorization scope |
| Temperature | Set low | Support, knowledge base Q&A, and rule-bound scenarios suit a low value; compare answer stability across repeated runs |
| Reply limit | Enabled with a medium length | The task needs complete explanations; compare whether a reply is cut off before the required content |
| Reply format | Keep default | Ordinary support Q&A keeps the default; change it only when a downstream step reads a fixed format |
| Hide AI output | Off | The answer is shown directly to the user; compare whether the output is visible |
Two implementation checks belong with this table. First, confirm whether the selected model's configuration window displays multimodal recognition options at all; the window shows only options the model supports. Second, confirm that the prompt states the material scope and the missing-evidence rule, and compare the drafted answer against the source wording rather than against a general expectation.
Three common errors
- Treating "pending review" on the complaint form as a confirmed diversion. Input the complaint form text, compare the complaint status field, and observe that pending review is not a confirmed finding. Terminating authorization on that basis has no support in the material.
- Applying store A's authorization scope to store B. Input the authorization list text, compare the authorized subject and authorization scope fields, and observe that the two subjects differ. The scope cannot be transferred.
- Treating a retrieval hit as authorization. Input the quoteList returned by the knowledge base, compare whether it contains the authorization list text, and observe that a retrieval match is not an authorization action. Business steps such as termination require a downstream implementation, which this page does not describe.
How to verify the setup
- Input the authorization list text and the proposed draft sentence from the hypothetical exercise. Compare whether the draft sentence stays within the authorized subject and scope in the source. The check fails when the draft contains "store B has been confirmed for diversion."
- Input the complaint form text and the proposed draft sentence. Compare whether the complaint status is "pending review." The check fails when the draft contains "its authorization will be terminated," because pending review is not a basis for termination.
- Input a follow-up question such as "until when is store A authorized?" Compare whether the answer cites the authorization period field. The check fails when the answer omits the period or supplies a different date. All three checks are paper comparisons and have not been run.