What the documents look like
Regional dealer stock replenishment runs as a daily rolling order cycle. It is not seasonal concentrated ordering, so the material set changes on a weekly or monthly cadence rather than around a single event. The documents that matter for copy drafting are replenishment requests, inventory turnover sheets, outbound delivery notes, and payment collection plans. These come from dealer ERP systems, the brand ordering system, warehouse stock records, and sales collection records.
Each document type supports a different kind of statement. A replenishment request records item and quantity along with a status. An inventory turnover sheet records turnover position for a stated statistical period. An outbound delivery note records an actual shipment. A payment collection plan records receivable arrangements. A drafting task can only assert what these documents carry. Where a document does not state a claim, the claim stays unsupported and the gap is kept open rather than filled by inference. Frequent errors in this category include stockouts, channel inventory pile-up, and overdue receivables, which is why copy that overstates approval or delivery timing carries real commercial risk.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Reference content is output as an array whose length can be 0, so the downstream path still runs even when nothing is retrieved. Search modes are semantic retrieval, full-text retrieval, and hybrid retrieval. Hybrid retrieval merges multiple result paths through RRF, and result reranking applies a ReRank model for a second ordering. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used. The reference cap is measured in tokens. Question optimization handles coreference resolution and question expansion. Retrieval similarity does not carry permission or entity isolation, and the same-vector-model requirement for associated knowledge bases does not extend to external systems.
A hypothetical paper exercise sample follows. Source material reads: "Replenishment request states: item A, requested quantity 200 cases, request date 10 March 2025, status pending review by the brand channel manager." "Inventory turnover sheet states: item A, ending inventory 80 cases, weekly average outbound 60 cases, statistical period March 2025." The draft sentence under review reads: "Item A has completed replenishment approval and delivery this week can be committed externally." The sample is used to check whether the draft sentence is supported by the material. It involves no real customer or identifier.
Configuration and implementation checks
| Configuration or check item | Value or action in this page's sample | Basis and explanation |
|---|---|---|
| Associated knowledge bases | The libraries holding replenishment requests, inventory turnover sheets, outbound delivery notes, and payment collection plans; confirm they share the same vector model | The node can associate one or more knowledge bases using the same vector model |
| Search mode | The sample contains item names and status words, so compare full-text retrieval against hybrid retrieval first | Full-text retrieval suits precise queries such as numbers and proper nouns |
| Reference cap | Set a hypothetical trial starting point of 800 tokens and compare against 500 and 1200 for whether reference content stays complete | This value is a trial starting point for this exercise, not an official default |
| Minimum relevance | Label relevant and irrelevant samples first, then adjust the threshold | This value takes effect only under semantic retrieval or when result reranking is used |
| Question optimization | For follow-up questions containing references, compare the original question with the optimized question and check whether the subject was altered | Question optimization handles coreference resolution and question expansion |
| Result reranking | When a ReRank model is available and enabled by configuration, filter candidates by the rerank score | Reranking requires the model and must be enabled by configuration |
Three common errors
- Treating pending review as completed approval. In the sample the replenishment request status is pending review by the brand channel manager, while the draft sentence says approval is complete. The input is the status field; the comparison is between "pending review" and "approval completed," which are mutually exclusive values in the same field; the draft sentence is unsupported.
- Treating inventory data as a delivery commitment. The inventory turnover sheet states only ending inventory and weekly average outbound, while the draft sentence commits to delivery this week. The input is the turnover sheet fields; the comparison is whether they contain a delivery date or shipment arrangement; absent that, the delivery commitment remains unverified.
- Using a similarity score to exclude unrelated business. Minimum relevance is a filtering threshold and does not carry permission or entity isolation. The input is the similarity score and the target retrieval scope; the comparison is whether the score reaches the threshold; a high or low score does not establish access permission.
How to verify the setup
- Input the replenishment request text from the hypothetical sample and the draft sentence "Item A has completed replenishment approval and delivery this week can be committed externally." Compare the status field value against the draft sentence wording. If the status is pending review, the draft sentence is unsupported; the condition is met only when the source states approval is complete.
- Input the inventory turnover sheet text and the delivery commitment in the draft sentence. Compare whether the sheet states a delivery date or shipment arrangement. If it carries only ending inventory and weekly average outbound, the delivery commitment remains unverified; the condition is met only when a specific shipment arrangement is stated.
- Input an empty reference array [] and check how the downstream design handles an empty result. Compare whether downstream treats it as an empty reference. Observe that the output path still runs when the reference content array length is 0; do not presuppose that a particular query type necessarily returns an empty result.
Knowledge bases using different vector models cannot be associated together; verify the identifier first and exclude those that do not match, then record the actual observation. Image retrieval requires a corresponding image input and model capability, and reranking requires the model to be available and enabled by configuration.