What the documents look like
Reverse returned-goods inspection handles returned parcels and assigned merchandise grades. It does not handle outbound picking for new orders. The working materials come from the WMS returns module, platform after-sales records, carrier return parcels, and the inspection bench. The routine documents are the return warehouse receipt, inspection photographs, the grade determination table, and the resale listing sheet. Records update per item and per day, so copy drafting has to follow each inspection conclusion rather than reuse the original sales page description.
For copy drafting, model connection and configuration determine whether a model can read these materials at all. The system needs at least one language model and one index model to work normally. AI Proxy is a required dependency, and both the App service and any Admin service reusing its configuration must set AIPROXY_API_ENDPOINT and a non-empty AIPROXY_API_TOKEN. The model ID is the value of the model field in the request body and is globally unique; the model name is display-only.
A return warehouse receipt and a grade determination table are structured text. Inspection photographs are image input. Where drafting depends on reading a photograph to judge condition, the language model in use must accept image input, and the vision field states that capability. Tool selection and function calling affect classification, content extraction, and tool invocation: when toolChoice is true, tool selection is preferred; when functionCall is false, the flow falls back to prompt mode. The reference-content ceiling is described by quoteMaxToken. A thinking budget is a separate kind of setting, and the two are not interchangeable.
Retrieval only recalls relevant text. Semantic recall and relevance scores do not carry permission or entity isolation, and retrieval is not authorization. Libraries sharing the same vector model are the condition for joint association; libraries on different vector models cannot be jointly associated, so the identifier is checked first, non-matching libraries are excluded, and the actual observation is recorded. An empty result can be checked against a downstream design using the explicit paper input [].
Constraints at the model connections step
The step sits between the inspection bench and the drafting output. The materials arrive as one return record at a time, and the drafting sentence has to match the same subject, the same object, and the same field as the record. A grade conclusion and a condition description are separate fields, and a claim about surface condition cannot be supported by a grade label alone.
Tool-related settings matter because classification and content extraction use them. Where a draft needs to pull a specific value out of a grade determination table, the configured model must support the tool path the workflow uses, or the workflow falls back to prompt mode. That fallback is a behavior of the model capability settings, not a guarantee about extraction quality.
Image input matters only when the draft actually depends on a photograph. If no image is passed and the model has no image capability, the photograph contributes nothing, and the draft must rely on the text fields instead. A re-rank model is a separate component, present only when configured and enabled, and it is not implied by the presence of a language model.
The retrieval side supplies candidate text. A similarity score is not a category, entity, or permission filter, and it does not exclude unrelated businesses or unauthorized records. Any exclusion of unauthorized records has to come from a downstream implementation with its own stated rules.
Configuration and implementation checks
The table below lists documented settings and implementation checks tied to this page's documents. The starting values marked as hypothetical are paper exercise points for this page only, with the reason for choosing them and the value they are compared against. They are not official defaults.
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison object |
|---|---|---|
AIPROXY_API_ENDPOINT | The AI Proxy service root address, with no /v1 appended | The documentation requires the root address; compared against a form with /v1 appended |
AIPROXY_API_TOKEN | A non-empty administrator token matching the server configuration | The documentation requires a non-empty token consistent with the server; compared against an empty value or an application API key |
Language model vision | Set to true where drafting reads inspection photographs | The draft involves inspection photographs; compared against false, where image reading is unavailable |
Language model toolChoice and functionCall | Values checked against the classification and extraction needs of the workflow | The documentation states the priority between the two; compared against the prompt-mode fallback |
Index model defaultToken and maxToken | Checked against the length of the text block being indexed | Documented field descriptions; compared against a split that exceeds maxToken |
| Model probe interval | Hypothetically set to 15 minutes | The documentation supports integers from 5 to 60; compared against a value outside that range |
Three common errors
- Writing
AIPROXY_API_ENDPOINTas a full model request address with/v1appended. Check: take the entered address as input, compare it against the documented requirement that the root address carries no/v1, and treat an address containing/v1as not satisfying the requirement. - Substituting an application API key for
AIPROXY_API_TOKEN. Check: take the entered token as input, compare it against the administrator token held in the server configuration, and treat an empty value or a value that does not match as not satisfying the requirement. - Treating a semantic relevance score as a permission or entity filter. Check: take a cross-entity retrieval request as input, compare the returned records against the authorized scope, and treat the use of a similarity score to exclude unrelated business records as a misuse of the setting.
How to verify the setup
Hypothetical paper exercise sample, not an actual call: the return warehouse receipt states "Return number RT-0001, item is a folding chair, quantity 1, receipt date 2026-03-02, inspection conclusion is minor surface scratches with normal function, grade B, resalable." The grade determination table states "Grade B: visible surface blemish, function intact, may be listed as second-hand good condition." The draft sentence awaiting judgment is "This folding chair is brand new and unused, with no surface blemish at all." The sentence shares the subject, the object, and the field with the materials: the materials state minor scratches and grade B, while the draft states no blemish at all, which is a mutually exclusive value in the same field.
- Input the return warehouse receipt and grade determination table text from the hypothetical sample, together with the draft sentence "This folding chair is brand new and unused, with no surface blemish at all." Compare the draft sentence against the same field in the materials: the materials give minor scratches and grade B, the draft gives no blemish at all. An observation that the two values are mutually exclusive shows the sentence is not supported by the materials and needs rewriting or additional evidence. The materials do not state a "brand new" condition, so that point remains unsupported.
- Input the inspection photograph and a language model configuration with
visionenabled. Compare whether the model accepts the image input and returns a condition description consistent with the photograph. If the model returns a grade description inconsistent with the photograph, record it as pending verification and do not infer an error code or an automatic action. - Input the paper empty result
[]together with the downstream drafting flow. Compare the downstream output behavior when no recalled text is present, and observe whether an unsupported promotional sentence appears. If the downstream still produces a specific blemish conclusion, record that observation without claiming the system automatically blocks or rewrites it.
The materials do not state a "brand new" condition, and no field in the sample establishes one. That gap remains open rather than resolved by the draft sentence.