What the documents look like
Presale group buying collects orders first and organizes procurement and fulfillment afterward. In this category, conversation records fall into two phases. Before the order cutoff, questions concern whether a group will reach its minimum size and when the cutoff falls. After the cutoff, questions concern stockout refunds, fulfillment delays, and group-leader complaints. Daily and per-session updates mean one chatId can span several presale sessions, so log review must bind each conversation to a specific session and cutoff status.
The main data sources are mini-program orders, supplier stock, group-leader feedback, and warehouse routing. These business records and the conversation logs live in separate systems. The presence of a log does not by itself constitute reconciliation or compliance auditing. The following sections describe the conversation logs and audit step for order fulfillment and after-sales answers, using the presale product table, group-result record, procurement plan, and cutoff notice as the surrounding documents.
Constraints at the conversation logs step
The chat interface uses the detail parameter to decide whether intermediate values are returned. In non-stream mode the result is saved in responseData; in stream mode the distinction is made through event values, which include answer, flowNodeStatus, flowResponses, interactive, and error. When run details are needed, set detail according to the official contract and inspect responseData. Business data that is not returned cannot be presumed to have been fully retained.
When chatId is a non-empty string, the system automatically takes the session from the database and uses the last item in the messages array as the user question; the remaining messages are ignored. Identity checks therefore need to combine chatId with business records. Conversations from different entry points must not be counted together. Identity fields in test mode can differ from formal calls, so input, history, and returned content need separate checks. Retrieval and similarity scores carry no permission or entity-isolation role.
Hypothetical drill sample: On 10 June 2025, after the cutoff of session A, a platform operator receives group-leader feedback that "3 portions of leafy greens for group point B-07 did not arrive." The materials for comparison are as follows. The cutoff notice records "Session A cutoff time 9 June 20:00; group point B-07 orders 12 portions." The group-result record states "Group point B-07 leafy greens reached 12 portions; supplier confirmed 9 portions." In the conversation log under this chatId, one AI reply reads "the out-of-stock portion will be refunded in a unified way." The draft sentence to be judged is: "Group point B-07, session A, leafy greens short by 3 portions; refund completed." This sentence names the subject, object, session, and status, but the phrase "refund completed" has no corresponding record in the materials and remains unsupported.
Configuration and implementation checks
The table below covers the sample and lists official documented settings or implementation checks relevant to this feature and primary task.
| Configuration item | Value or check content | Basis and explanation |
|---|---|---|
| appId | Target application ID, matching the application that owns the sample session | Required by the official interface to locate the application |
| chatId | The group leader's session ID, length under 250 | Official description; used to locate the session |
| detail | Set to true to obtain responseData | Official description; needed for run details |
| stream | Chosen according to the review need; event distinction differs | Official description; the two modes return different structures |
| source | In getHistories, source=api returns only sessions created through the API | Official description; source filtering |
| loadCustomFeedbacks | Set to true when custom feedback must be read | Official description; optional parameter |
Setting detail to true is the starting point for this hypothetical trial. The reason is that module run records are needed from responseData. The comparison is against the result when detail=false, where only choices are returned, to confirm whether intermediate values appear.
Three common errors
- Treating a retrieval similarity score as a permission or entity filter. In the sample, score indicates only the degree of recall relevance, not whether this group leader is entitled to view the record. Check method: input the sample chatId and query, compare the dataset_id in the returned quoteList against the business authorization scope, and treat a judgment based only on a high score as an error.
- Treating a form configuration returned by an interactive node as already submitted or executed. If a userInput inputForm appears in the sample, it represents display configuration only, not that a refund form has been filled in. Check method: compare the returned interactive field against whether serialized input appears in subsequent messages; if no input record exists, submission has not occurred.
- Treating the AI reply "will be refunded in a unified way" in the log as a completed refund. The sample draft sentence makes this error. Check method: compare the draft sentence against the source materials; since the source has no refund execution record, "completed" is unsupported and should be recorded as pending verification.
How to verify the setup
- Input the sample source materials and the draft sentence. Compare "refund completed" in the draft against "the out-of-stock portion will be refunded in a unified way" in the source, and observe whether an execution-status record exists. Expectation: when no execution record exists, judge the claim unsupported and preserve the evidence gap.
- Input the sample chatId and call the conversation list interface. Compare the dataId in the returned list against the conversation ID in the business records, and observe whether they correspond one to one. Expectation: the session record for that session can be located, and sessions under other chatIds are not mixed in.
- Paper check for empty-result handling: suppose a query returns quoteList as []. Compare whether the downstream design treats this empty result as no reference, and observe whether data from another session is incorrectly filled in. Expectation: the empty result is handled as no reference; hidden records are not presumed, and no claim is made that a fictional rule guarantees an empty retrieval.
This page covers only group-buy presale order fulfillment and after-sales answers, specifically the conversation logs and audit step. Reconciliation, retention, and compliance requirements are handled by the full business solution. The presence of a log does not equal completed compliance auditing. Retrieval and similarity do not carry permission or entity isolation. Whether a refund, a form submission, or an approval has actually occurred depends on records outside the conversation log, and those records remain the source of judgment.