What the documents look like
Cross-border standalone-site payment risk control operates around card network disputes and receiving accounts, which is separate work from parcel fulfillment order handling. The daily materials include payment chargeback notices, fraudulent order lists, invoices, and logistics delivery proof. Sources include Stripe or PayPal backends, Shopify orders, carrier signatures, and customer service email. These materials update daily and per order. Product data and selection Q&A must map fields such as product name, order number, amount, and dispute status from those materials onto product data and selection notes in the knowledge base. At this step, model connection and configuration determines whether Q&A can cite the correct document. It does not determine whether a dispute is upheld.
A chargeback notice, a fraudulent order list, and an invoice are distinct document types with distinct fields. A fraud list entry carries an order-level review status. A chargeback notice carries a card network dispute record. An invoice carries billing amounts and line items. A carrier signature proves delivery of a shipment, not the validity of a dispute. The knowledge base holds product data and selection notes that describe which product fits which device or use case, with effective dates. The Q&A task is to answer product and selection questions by citing those product documents. Model configuration decides whether the retrieval and generation path can reach the right product document. It does not decide the review status of any order.
Constraints at the model connections step
The system requires at least one language model and one index model to operate normally. Model ID is the value of the model field in the interface request body and is globally unique. Model name is for display only. A model channel corresponds to a provider protocol, and one model can be configured across multiple channels for load balancing. Custom request address and key can bypass the channel, which the documentation marks as not recommended. Model probing targets only currently enabled system models. Disabled models do not participate in probing and produce no history records.
Hypothetical exercise sample: The knowledge base contains a product data passage stating "Product A fits device models X1 and X2, effective from March 1, 2026." A fraudulent order list records "Order 20260315-01, Product A, amount 120 USD, status pending review." The draft sentence to be judged is: "Order 20260315-01 is confirmed fraudulent, and Product A fits device models X1 and X2." This draft sentence writes a pending-review status as confirmed fraud, and merges the product data effective range with the order status in one sentence.
The sample is a paper exercise only. No order, dispute, refund, or account action is asserted. The pending-review status is not an approval, not a denial, and not a completed determination. The effective date in the product passage is a validity boundary for the product data, not a statement about any order.
Configuration and implementation checks
The table below lists documented settings or implementation checks relevant to this sample. Where a value appears, it is a hypothetical starting point for this exercise, with the reason for choosing it and the comparison object.
| Configuration item | Hypothetical value and reason | Check method |
|---|---|---|
| AIPROXYAPIENDPOINT | Set to the AI Proxy service root address, without appending /v1 | Compare against the documented requirement and confirm no path is appended |
| AIPROXYAPITOKEN | Set to a non-empty admin token consistent with the server side | Confirm non-empty and not replaced by an application API key |
| Language model | Enable one language model for Q&A generation | Confirm the model status is enabled |
| Index model | Enable one index model for product data retrieval | Confirm the model status is enabled |
| Model probing | Assume interval set to 30 minutes, chosen because it falls between the documented 5 to 60 minute range | Compare against the documented allowed range and confirm an integer |
| Alert Webhook | Assume one callback address is configured to receive model status changes | Confirm the address is HTTP or HTTPS |
Three common errors
- Writing a pending-review status as confirmed fraud. The input is "status pending review" in the fraudulent order list. The comparison object is the draft sentence "confirmed fraudulent." The observable result is that the status field values do not match.
- Merging the product data effective range with the order status. The input is the product data passage "effective from March 1, 2026" plus the order status field. The comparison object is the draft sentence that combines both into one clause. The observable result is that the draft sentence lacks a separate qualification of the effective date.
- Using a disabled model in probing. The input is the model enablement state. The comparison object is the probing scope description. The observable result is that disabled models produce no probe records.
How to verify the setup
- For the draft sentence "Order 20260315-01 is confirmed fraudulent," the input is the fraudulent order list original text "status pending review." Compare whether the status field matches. The condition is satisfied when the draft sentence status matches the original or is changed to pending verification. The current draft sentence does not satisfy this.
- For the draft sentence "Product A fits device models X1 and X2," the input is the product data original text "effective from March 1, 2026." Compare whether the draft sentence retains the effective date qualification. The condition is satisfied when the draft sentence separately notes the effective date. The current draft sentence does not satisfy this.
- For model probing, the input is the enabled model list. Compare against the probing scope description. The condition is satisfied when probe records cover only enabled models. Whether disabled models produce records remains an unresolved item and is not replaced by speculation.
A relevance score is not a category, entity, or permission filter. Retrieval does not establish authorization. A form collects values; business verification, approval, database writes, and external synchronization require their stated downstream implementation. The pending-review status in the sample is not an approval, not a completed termination, and not a refund. The unsigned status of any dispute remains unsigned. Missing evidence remains missing.