What the documents look like
Channel diversion review concerns regional and price order. It does not calculate rebate amounts. The working materials come from anti-counterfeit code systems, e-commerce platform prices, distributor shipment records, and market inspection results. Day-to-day documents include diversion complaint forms, anti-counterfeit code records, penalty notices, and investigation photographs. Brand channel control teams, anti-counterfeit teams, and regional managers are the typical operators. Data arrives weekly and irregularly.
For copy drafting, these materials supply the expressions that a draft sentence can be checked against. Fragment length varies widely. An anti-counterfeit code record may hold a single line of code, while a complaint narrative or a photograph description may run to several hundred characters. The knowledge base reference limit is measured in tokens, so an overlong fragment can be trimmed and a draft sentence can lose its subject or its status basis. The reply limit and the model context are separate concepts: the reply limit governs output length and does not replace a check of the input-side reference scope. History turns affect whether earlier materials remain available during a multi-turn follow-up; a large value raises consumption, and a small value can drop a previously confirmed comparison conclusion.
Constraints at the context limits step
A hypothetical paper exercise sample is set out here for checking purposes only. A brand channel control team receives a diversion complaint form. The material text reads: "Complaint form number HYP-2024-0312. The complained party is East China regional authorized distributor A. The complaint states that a same-model product listing below the suggested retail price was found on an e-commerce platform. Shipment records show this batch of goods moved to the South China region." A draft sentence awaits judgement: "This distributor has engaged in cross-region diversion, and the brand has initiated penalty proceedings." The material records only the complaint content and the shipment flow. It records no investigation conclusion and no penalty decision. The phrases "has engaged in cross-region diversion" and "has initiated penalty proceedings" are not supported by the material and remain pending verification.
Three constraints follow. First, the reference limit is counted in tokens, not in top k, because chunk lengths differ greatly across a mixed knowledge base. A complaint fragment can be trimmed before the draft sentence reaches the model. Second, the minimum relevance value is a filter threshold that applies only under semantic retrieval or result re-ranking. It is not a category, entity, or permission filter, and it does not exclude unrelated businesses or unauthorized records. Third, retrieval is not authorization. The search returns candidate content; business verification, approval, database writes, and external synchronization require their own downstream implementation.
The model context is the content length a single request can reference. The reply limit is the maximum answer length. Both appear in the AI configuration dialog, and the dialog shows only the settings the current model supports. A model without multimodal support does not display a multimodal recognition option.
Configuration and implementation checks
| Configuration item | Hypothetical starting value for this exercise | Reason and comparison method |
|---|---|---|
| Reference limit | Set to 2000 tokens for this exercise | The sample material is about 150 characters; 2000 tokens can hold several fragments. Compare with 500 tokens and observe whether the draft sentence basis is trimmed |
| Reply limit | Set to 800 tokens for this exercise | The draft sentence plus comparison notes need about 200 characters. Compare with 200 tokens and observe whether output is cut off |
| Minimum relevance | Set to 0.3 for this exercise | The sample material is semantically clear. Compare with 0.7 and observe whether the complaint fragment is filtered out |
| Search mode | Hybrid retrieval | The anti-counterfeit code needs full-text matching and the complaint description needs semantic matching. Compare with pure semantic retrieval for code recall |
| Question optimization | Enabled | Coreference resolution helps link earlier material during multi-turn follow-ups. Compare with disabled for recall differences in follow-up scenarios |
| Reply format | Default | The draft sentence is natural-language output. Compare with json_schema where field parsing is required |
These values are hypothetical starting points for this exercise, not official defaults. The knowledge base reference limit uses tokens as its unit and differs from top k. The minimum relevance value takes effect only under semantic retrieval or result re-ranking. Hybrid retrieval merges semantic and full-text recall through RRF, which is a fusion process rather than a switch. The optional paths in the overall retrieval flow do not all execute on every request: image retrieval requires image input and model capability, and re-ranking requires a model and must be enabled by configuration.
Three common errors
- Treating the reply limit as the model context window. The reply limit controls output length; the model context is the content length a single request can reference. These are different fields. To check, inspect the maximum context shown in the model information and the reply limit setting separately.
- Treating a similarity score as a permission or entity filter. The minimum relevance value is a filter threshold. It does not exclude unrelated businesses or unauthorized records. To check, confirm whether retrieval results contain material from a non-target distributor and record the actual observation.
- Treating a pending status as an executed penalty. The complaint form records complaint content and records no investigation conclusion or penalty decision. A draft sentence that states "has initiated penalty proceedings" does not match the material status. To check, compare subject, object, status, and effective scope field by field.
How to verify the setup
- Input the hypothetical sample material text and the draft sentence. Compare "has engaged in cross-region diversion" in the draft sentence against the complaint content and shipment flow records in the material. The material records no investigation conclusion, so this expression is unsupported. If the output presents the complaint content directly as a confirmed diversion finding, the check does not pass.
- Input the hypothetical sample material text and the draft sentence. Compare "has initiated penalty proceedings" against the penalty notice field in the material. The material contains no penalty notice, so this expression is pending verification. If the output treats the complaint form number as a basis for penalty proceedings having started, the check does not pass.
- Input an empty history and the same question with one prior turn of context. Compare the material fragments returned by the two retrievals. If the complaint fragment is trimmed or lost when history is present, inspect the reference limit and history turn settings. If the empty-history case returns an empty result, record that observation and do not infer that a fictional rule necessarily returns an empty array. A downstream design can be checked against an explicit paper input of an empty array, without claiming that retrieval under a fictional rule must return it.
Retrieval checks record actual observations and failure branches. They do not guarantee a first-hit match or full recall. Libraries built on different vector models cannot be associated together; verify the identifier first and exclude non-conforming ones rather than running a cross-model retrieval to compare missed recall. Image retrieval requires image input and model capability. Re-ranking requires a model and must be enabled by configuration.