What the documents look like
Livestream violation appeals respond to penalties that have already been issued, so the evidence chain has to cover the violation notice, the livestream recording, product qualification files and the appeal statement. Sources sit in separate places: the platform violation center, livestream replays, customer service records and the product qualification library. Updates are irregular and each violation triggers its own batch of material. Operating reporting and exception review aligns these materials with conversation logs, checking which appeal corresponds to which conversation segment and which qualification was valid over what date range.
Conversation logs come from the chat interface. Per the official documentation, a session starts through chat/completions, and passing body.appId in the request body is recommended. When chatId is a non-empty string, the system pulls the session from the database and uses the last element of the messages array as the user question, ignoring the remaining messages. When responseChatItemId is passed, it becomes the ID of this response message stored in the database, and it must be unique under the current chatId. These fields determine whether a log can be aligned with a business record.
Constraints at the conversation logs step
Appeal materials and conversation logs must line up on time, subject and object. The existence of a log does not mean a compliance audit is complete; reconciliation, retention and compliance requirements are handled separately by the full business solution.
Hypothetical drill sample: a store received a platform violation notice on 10 June 2025, number ZB-2025-0610-07, concerning a livestream segment for product A. The customer service record reads, in two sentences: "At 14:20 on 10 June, the user asked whether product A's qualifications were complete, and the agent replied that the qualifications had been submitted to the platform for review." "At 15:05 on 10 June, the user followed up on the review result, and the agent replied that no platform conclusion had been received yet." Draft sentence under review: "Customer service confirmed that product A's qualifications passed platform review." The materials show only that the qualifications were submitted and that the platform conclusion had not arrived, so the draft sentence does not match the source wording.
Constraints: with detail=true the interface returns intermediate values and responseData; with detail=false it does not. In stream mode events distinguish the output; in non-stream mode the result is stored in responseData. When checking log fields, business data that was not returned cannot be assumed to be fully retained. Identity fields in test mode may differ from a production call, so input, history and returned content need separate checks. Similarity and retrieval carry no permission or entity isolation.
Configuration and implementation checks
The table below centers on the hypothetical sample and lists settings the official documentation describes, or implementation check items. The values are starting points for this hypothetical trial, not official defaults.
| Configuration item | Hypothetical starting point for this trial | Reason for the choice and comparison method |
|---|---|---|
appId | Sample application ID | Check against the store named in the violation notice to confirm the log belongs to the same application |
chatId | Sample session ID | Check against the customer service record date to confirm the session covers 10 June |
responseChatItemId | This response ID | Check uniqueness under the current chatId to avoid overwriting |
detail | Set to true | responseData is needed to check run details; compare with what is returned when false |
stream | Set to false | In non-stream mode the result is stored in responseData, which is easier to check field by field |
variables | Pass uid and name | Replaces [key] in module input fields; check against the business record subject |
Three common errors
- Mixing calls with an empty
chatIdand calls with achatId. With an empty value the system does not use the context feature and builds everything from messages; with a non-empty value it pulls the session from the database. Confirm which kind of call this is before comparing log scope. - Treating a
detail=falseresponse as a complete run record. That mode returns no intermediate values and noresponseData. A missing field cannot be read as proof that business data was not retained; it is recorded as unsupported. - Treating a similarity score as a permission or entity filter. Similarity does not exclude unrelated businesses or unauthorized records, and retrieval is not authorization. Confirm identifiers first and set aside records that do not match.
How to verify the setup
- Input the sample source wording and the draft sentence, then compare the draft "Customer service confirmed that product A's qualifications passed platform review" against the source "qualifications had been submitted to the platform for review" and "no platform conclusion had been received yet." Observable result: the draft and the source take different values on the review status field, so the draft is judged unsupported.
- Input the
chatIdand the customer service record date, then compare whether the session coverage includes the two records at 14:20 and 15:05 on 10 June. Observable result: when the session time range covers both records the condition is met; when it does not, record the gap. - Input two requests, one with
detail=trueand one withdetail=false, then compare whetherresponseDatais present in the return. Observable result: it is returned when true and not returned when false, which fixes the scope of the check. All of the above are paper expectations and were not actually tested.