What the documents look like
Producer export tax refunds combine the offset of domestic sales tax with the export refund calculation, which differs from the accounting path used by trading companies for export refunds. In store service and internal training, multi-turn dialogue centers on four document types: the exemption, offset and refund declaration detail table, export contracts, the sales detail ledger, and export customs declarations. Field definitions across these materials stay consistent within a monthly filing cycle. As dialogue turns accumulate, earlier messages enter the context and the model's reference range for prior turns expands.
Retrieval returns source fragments from the configured knowledge base. A retrieval hit and an authorization state remain independent of each other. A hit does not indicate that a given store or staff member holds permission to view or execute the related action. Relevance scoring does not perform entity isolation or permission filtering.
Constraints at the multi-turn prompts step
Context in multi-turn dialogue is governed by the memory turn count. A larger value raises the probability that earlier dialogue is referenced, and consumption and response time rise alongside it. For knowledge-base question answering, retaining a small number of historical turns is sufficient for routine store verification. Prompts need to state the material scope, the answering task, and how to handle missing evidence. The model must not supply business facts that are absent from the source.
Reply format follows the downstream handling method. Ordinary question answering keeps the default; when a fixed structure is required, select json_schema and enter the corresponding format requirement. A lower temperature favors rule-bound verification scenarios. Thinking configuration appears only when a model that supports thinking is selected. The thinking budget controls thinking intensity and is a different parameter from the length cap on referenced content.
Hypothetical drill sample: a store submits an internal training material. The source text reads: "In this store's March 2025 exemption, offset and refund declaration detail table, the export sales amount field is filled as 1,200,000 yuan, the domestic sales amount field is filled as 800,000 yuan, and the remarks field states 'data pending review by the tax accountant'." The proposed judgment sentence is: "This store's March 2025 exemption, offset and refund declaration has completed review." The handover request to be judged is: "Please confirm that the above declaration detail table has passed review, and update the training case accordingly."
Configuration and implementation checks
| Configuration item | Purpose on this page | Verification method |
|---|---|---|
| AI model | Select a model supporting long context and tool calling for declaration detail table question answering | Check the maximum context and tool calling indicator shown for the model in the AI configuration dialog |
| Memory turns | Control the historical turns referenced during multi-turn store verification | Hypothetical trial starting value of 4 turns, chosen because a single store verification usually involves no more than 4 follow-up questions; compare with the default and adjust to actual need |
| Reply cap | Limit single-reply length to avoid truncating declaration field explanations | Enable and set via slider, then compare against the model maximum context |
| Temperature | Reduce answer divergence in rule-bound scenarios | Keep default or low; compare with creative scenario settings |
| Reply format | Keep default for ordinary question answering; select json_schema when structured output is needed | After selecting json_schema, enter the format requirement and check the returned structure |
| Thinking configuration | Control thinking intensity when a thinking-capable model is selected | Check the level in the dialog; verify thinking budget separately from the reference length cap |
The display configuration returned by an interactive node contains only type and params; internal runtime-state fields are not returned. Values collected by a form require downstream implementation to complete business validation and writing. A form submission does not constitute authorization or approval.
Three common errors
- Treating a retrieval hit as a permission pass. Input is a verification request initiated by store staff; compare the returned fragments against the staff member's actual authorization scope; the observable result is whether the fragments include material the staff member is not authorized to view. Retrieval relevance does not carry entity isolation or permission filtering.
- Writing a pending-review state as completed review. Input is the hypothetical sample source text above and the proposed judgment sentence; compare the remarks field "data pending review by the tax accountant" against the proposed sentence "has completed review"; the observable result is whether the two point to mutually exclusive values of the same field. When no evidence of completed review is recorded, the only available record is pending verification.
- Treating the thinking budget as the reference length cap. Input is the thinking configuration level and the reply cap setting; compare the objects each parameter acts on; the observable result is whether the thinking budget is used to limit referenced content length. These are different parameters and are not interchangeable.
How to verify the setup
- Input the hypothetical sample source text and the proposed judgment sentence; compare the remarks field state against the review conclusion in the proposed sentence; the observable result is whether the proposed sentence exceeds the range supported by the source. The expected outcome is that the proposed sentence is not supported by the source and is recorded as pending verification.
- Input the hypothetical sample source text and the handover request; compare the "update the training case" action in the request against whether the source contains an authorization basis; the observable result is whether the request meets the conditions for execution. The expected outcome is that the request remains in a pending-confirmation state and the update is not executed.
- Input an empty-result downstream scenario; the paper input is a retrieval return of
[]; compare whether the downstream node design handles an empty reference output; the observable result is whether the downstream gives a missing-evidence notice. The expected outcome is that the downstream handles it as missing evidence and does not supply business facts.