What the documents look like
Livestream violation appeals deal with penalties that a platform has already issued. The working materials are the violation notice, the livestream recording, the product qualification file, and the appeal statement. In the product and marketing copy drafting step, each proposed sentence has to be aligned against the qualification materials to judge whether the sentence has material support.
Materials update irregularly, and each violation forms its own group. Within one livestream session, the recording segment, the product qualification document, and the clause in the violation notice carry three matching relationships: time, subject, and field. The context and token constraint follows from this. A single model request can only reference a limited amount of content, so long materials are truncated, and the truncation position determines whether a proposed sentence can see the corresponding evidence.
The model's maximum context sets how much content one request can reference. The reply limit only caps output length, and the two cannot substitute for each other. The knowledge base reference limit controls, in tokens, how much content each search may cite, so a long segment crowds out reference space for other segments. Prior conversation turns occupy context, and the same question sent with empty history and with history produces different model input. When a fixed reply format is used, field completeness and successful parsing need separate checks, and text length cannot stand in for them.
Constraints at the context limits step
Paper exercise sample, not a real record:
Material text one: the violation notice states that in the session of March 12, 2025, product A carried the promotional sentence "this ingredient can replace drug treatment," judged as an efficacy violation.
Material text two: the product qualification file states that product A is an ordinary food, the filing category is solid beverage, the filing date is January 8, 2025, and the filing subject is a food manufacturing enterprise.
Material text three: the livestream recording transcript states that the host spoke at 21:14 on March 12, 2025, saying "this ingredient can replace drugs."
Proposed sentence to be judged: "The ingredient in product A can assist improvement, and the related wording has been adjusted to the filing scope for ordinary food."
The fields needed for judgment are the promotional sentence content, the product category, the filing scope, and the spoken time. Material text two states only the filing category and date; it does not state the specific functional wording scope for that ingredient. The phrase "assist improvement" in the proposed sentence has no support in that material and remains an item pending verification. It does not form a contradiction with the filing content.
Configuration and implementation checks
| Configuration item | Relevant value or check item on this page | Relation to the sample |
|---|---|---|
| AI model maximum context | Check against the actual model capability; do not treat the reply limit as the full context window | The three material texts plus the proposed sentence must fall completely within one request |
| Reply limit | Adjust for the task, keeping enough room to express the basis and the handling action | The proposed sentence and the judgment reason must be output in full |
| Knowledge base reference limit | Reference is controlled in tokens; check against single-segment length and the question sample whether content is truncated | Check whether material text two is truncated |
| Memory turns | Compare the input for the same question with empty history and with history | Exclude unrelated session content carried in by history |
| Reply format | When json_schema is used, verify field completeness and successful parsing | Judgment fields need the same names as the material fields |
| Thinking strength | Choose among the levels the model supports; the thinking budget and the reference token limit are separate settings | A higher level may be selected for comparing a complex evidence chain |
The reference limit uses the token unit rather than top k, because chunk lengths vary widely. The minimum relevance value takes effect only in semantic retrieval or when result reranking is used; it is a filter threshold and does not perform permission or entity isolation.
For this page the configuration table lists documented settings and implementation checks. Where a numeric starting point is needed for the paper exercise, it is named as a hypothetical starting value for this exercise and compared against a stated value, not presented as an official default.
Three common errors
- Treating the reply limit as the full context window. The reply limit caps output length, while the input length of material texts one through three plus the proposed sentence is bounded by the maximum context. In the check, compare the total length of the three material texts plus the proposed sentence against the maximum context shown for that model, and observe whether material is truncated on the input side.
- Setting the reference limit too small so that material text two does not enter the referenced content. In the check, compare the token value of the reference limit against the actual token volume of the three material texts, and observe whether the returned references include the filing category and filing date fields. When they are absent, record this as not referenced, and do not infer that the material does not exist.
- Checking the proposed sentence with history-laden input, where history brings in content from other sessions. In the check, build an empty-history input and a history-laden input for the same proposed sentence, compare the material sets sent to the model in the two cases, and observe whether the history-laden input mixes in wording from a session other than March 12, 2025.
How to verify the setup
- Input material texts one through three and the proposed sentence to be judged. Compare "assist improvement" in the proposed sentence against the filing category and filing scope fields in material text two, and observe whether the output marks "assist improvement" as pending verification. When material text two does not state the functional wording scope, the phrase must not be judged as supported.
- Input an empty-history version and a history-laden version of the same proposed sentence. Compare the session dates appearing in the two sets of referenced content, and observe whether the history-laden version contains session wording other than March 12, 2025. If it appears, record it as history carry-in and mark it in the check record.
- Input a paper-based empty reference result and check the downstream node's design for carrying an empty reference. Observe whether the downstream outputs "no citable material retrieved" and preserves the field structure. This check verifies only the carrying design and does not claim that retrieval will return an empty result.
These checks are paper exercises and were not actually executed. They do not constitute an operating conclusion about any model, library, or downstream system.