What the documents look like
Channel diversion review deals with regional and price order, not rebate amounts. Its working materials are anti-counterfeit code records, e-commerce platform prices, distributor shipment records, and market inspections; the daily documents are diversion complaint forms, penalty notices, and investigation photographs. These materials update weekly or irregularly.
In the multi-turn prompt step, document shape determines how context is built. Anti-counterfeit code records usually arrive as code lists, low-price shop comparison depends on price screenshots, and complaint forms and penalty notices carry subject, region, and time fields. The scope of supplied material must be stated, and missing evidence stays missing.
Three facts matter most here. First, a retrieval hit on a code record or a complaint form is not an authorization to act; the record shows what was queried, not who approved a penalty. Second, a similarity score is a relevance number and does not isolate regions or distributors. Third, an interactive form collects values; business verification, approval, database writes, and external synchronization require their own downstream implementation.
Constraints at the multi-turn prompts step
History scope affects follow-up accuracy. A new session and a continued session receive different input, so the context actually carried in must be checked. Question optimization applies to knowledge-base continuous conversation; check referent resolution and question expansion, and do not assume every short question fits. Model context and reply length must be tested against long documents combined with follow-ups. Reply format follows downstream consumption; when json_schema is selected, the format requirement is filled in and the returned structure is verified.
Hypothetical drill sample. Complaint form text: "Distributor A shipped batch code A-0305 to the East China region on 5 March 2025; e-commerce shop B lists it below the suggested retail price." Anti-counterfeit code record text: "Code A-0305 first queried 8 March 2025, query location South China." Draft sentence: "This batch is confirmed as cross-region sales; a penalty is recommended." Pending request: "Please generate a penalty notice draft based on the above materials." The materials show only code, time, location, and price. They do not state an approval record authorizing a penalty.
Memory turns control how many earlier rounds are carried in. The documented setting is a count of prior chat rounds; a larger value brings in earlier dialogue but adds content, which may raise consumption and slow response, while a small value may fail to use prior information. The documentation recommends a default when there is no clear need, and notes that customer service and knowledge-base Q&A applications usually keep only a small number of history rounds. Reply length is controlled by a slider once enabled; too low may truncate the reply early, higher allows fuller content and may raise consumption. Temperature controls stability; lower values suit customer service, knowledge-base Q&A, and rule-clear scenarios, higher values suit writing and brainstorming, and the documentation recommends keeping the default when uncertain. Topp overlaps with temperature, and the documentation advises against adjusting both at once. Stop sequences end output at a fixed marker and are normally unnecessary for ordinary chat. Reply format stays default for ordinary chat, customer service Q&A, and knowledge-base Q&A; jsonschema suits fixed-structure returns and requires the corresponding format requirement. Multimodal recognition depends on model capability; the popup shows only available options, unsupported types are filtered again before the request is sent, and document files are not sent as multimodal input directly.
Configuration and implementation checks
| Configuration item | Relevant setting on this page | How to check |
|---|---|---|
| AI model | Choose a model whose maximum context covers the material | Compare the popup's maximum context and tool-calling display with the complaint form plus code record length |
| Memory turns | Hypothetical trial starting value of 3 rounds | This value controls how many prior rounds are carried in; compare with a request that omits chatId and builds context entirely from messages |
| Reply length | Set according to penalty notice draft length | Compare with truncation behaviour and observe whether the reply is cut off early |
| Temperature | Hypothetical trial starting value on the low side | Compare with the stability required by rule-clear scenarios |
| Reply format | Keep default for ordinary Q&A; select json_schema when a fixed structure is needed | After selecting, fill in the format requirement and verify the returned structure |
| Multimodal recognition | Enable according to model capability when materials include investigation photographs | Check the capability shown in the popup; unsupported types are not sent |
Three common errors
- Treating retrieval results as authorization. A retrieval hit on an anti-counterfeit code record or a complaint form does not mean a penalty approval exists. Input: the complaint form and code record in the hypothetical sample. Comparison: whether the materials contain an approval record field. Observable result: whether the draft sentence directly outputs a penalty conclusion.
- Treating a similarity score as an entity filter. The score is a relevance number and does not perform region or distributor isolation. Input: a low-price shop comparison query. Comparison: whether returned results include records outside the target region. Observable result: whether unrelated subjects are excluded on the score alone.
- Treating an interactive node form as submitted. A form collects values; business verification and writes need a downstream implementation. Input: a penalty notice form. Comparison: form values against an approval status field. Observable result: whether a penalty conclusion is produced before submission.
How to verify the setup
- For the hypothetical sample draft sentence, input the complaint form and code record text, compare whether the draft sentence contains "confirmed as cross-region sales" and "penalty" wording, and observe whether the output preserves the approval gap. Condition met: the output clearly states that the penalty basis is insufficient.
- For the pending request, input a continued session under the same chatId, compare the number of history rounds carried in against the messages construction difference, and observe whether the follow-up references the earlier code A-0305. Condition met: the context carried in matches the memory turns setting.
- For the json_schema format, input the penalty notice structure requirement, compare returned fields against required fields, and observe whether any required item is missing. Condition met: the returned structure matches the filled-in format requirement.
The retrieval check must observe the failure branch. When the result is empty, use the explicit paper input [] to check the downstream design; do not claim that a fabricated rule retrieval necessarily returns empty. Libraries under different vector models cannot be associated together; check the identifier first, exclude non-matching ones, and record the actual observation, without running a cross-model retrieval to compare missed recall. Whether a hybrid fusion process is active is not written as an on/off switch. Interactive wait states, record status, and hidden dialogue boxes follow the documentation; no corresponding control switch, submission count, automatic judgement, or snapshot guarantee is invented. A thinking budget is a thinking budget and is not reused as a citation token limit. A pending review does not demonstrate a lack of operating permission; signing, reaching cooperation, and contract effectiveness are three distinct facts; a quotation validity period does not indicate a supply period. Authorization or effectiveness clauses are not fabricated to obtain a definite answer, and the evidence gap is explicitly preserved.