What the documents look like
Brand omnichannel stock transfer work moves goods between stores and warehouses. It does not handle marketing outreach. The material comes from ERP inventory, store POS, e-commerce orders and WMS. The recurring documents are transfer requests, inventory snapshots, store shortage lists and transfer logistics notes. Product and marketing copy drafting draws on the in-transit, transferable, shortage and arrival information recorded in those materials. Material updates follow a daily or weekly rhythm, and any quantity or status cited in drafted copy has to match the period stated in the material.
The three slowest steps in this category are locating transferable stock, approving the transfer route and updating arrival and putaway. Copy drafting sits downstream of those steps: it restates what the materials already record and does not create approval, arrival or availability facts.
Constraints at the model connections step
Model access depends on AI Proxy. From V4.17.0, AI Proxy is a required dependency. The App service and any Admin service that reuses App/Service configuration must set AIPROXY_API_ENDPOINT and a non-empty AIPROXY_API_TOKEN. Missing either one causes startup validation to fail. Legacy OpenAI environment variables and single-model custom request addresses do not substitute for these two settings.
The system needs at least one language model and one index model to work normally. Model capability is checked against the input the application actually uses: multimodal input, tool calling and thinking configuration are verified separately. Application parameters are set in the application or node configuration. A same-named field on a compatible chat interface is not assumed to override orchestration.
Hypothetical paper exercise, not an actual record: Material text one reads "Transfer request A-01, requesting party: a store in the East China region, object: one style of outerwear, 120 units, status is pending approval, request date: March 1." Material text two reads "Inventory snapshot S-01, same outerwear style, transferable stock 80 units, snapshot date: March 1." The sentence under review reads "The store has been approved to transfer 120 units and can list them for sale immediately." Authorization boundary: neither approval nor arrival appears in the materials.
Configuration and implementation checks
| Configuration item | Hypothetical trial starting point for this page | Comparison and reason |
|---|---|---|
AIPROXY_API_ENDPOINT | Enter the AI Proxy service root address, without appending /v1 | Compare against the documented root-address form |
AIPROXY_API_TOKEN | Enter a non-empty administrator token matching the server side | Compare against the documented non-empty, matching requirement |
| Language model | Enable one already-enabled language model | Compare against the documented minimum of one language model |
| Index model | Enable one already-enabled index model | Compare against the documented minimum of one index model |
| Model capability | Check against the input the copy task actually supplies | Verify multimodal input and tool calling separately |
| Application parameters | Set in the application or node configuration | Compare against the rule that same-named fields do not override orchestration |
Each row is a check to perform, not a record of a completed deployment. The starting points are named for this page's exercise and are not official defaults.
Three common errors
- Treating "pending approval" as approved. Input: material text one states status pending approval. Comparison: the approval field in the material. The sentence is supported only when the material shows an approved status. At present the approval fact is unverified, and the drafted sentence claiming approval is unsupported.
- Writing 120 units as the transferable quantity. Input: material text one requests 120 units; material text two records 80 transferable units. Comparison: the same field across the two materials. The two values differ, which shows the requested quantity and the transferable quantity are different figures. It does not show a contradiction.
- Treating a relevance score as a permission or entity filter. Input: a relevance score returned by retrieval. Comparison: the authorization scope of the records. A score does not exclude unauthorized records. Permission has to be checked separately.
How to verify the setup
- Input the two material texts above and the sentence under review. Compare whether the sentence contains "has been approved" and "can list immediately." When the materials carry no approval field and no arrival field, the sentence is unsupported. The expected observation is that the approval and arrival facts remain missing.
- Input the paper empty result
[]and compare whether the downstream design handles it as empty. This checks the receiving design only. It does not assert that a rule-based retrieval must return[]. - Input library identifiers from different vector models. Check the identifiers first and exclude those that do not match, then record what is actually observed. Cross-model retrieval is not performed to compare missed recall.
These are paper checks with stated expected observations. No test, deployment, approval or refund is claimed to have occurred.