What the documents look like
Livestream violation appeals deal with penalties that have already been issued. The working materials are the violation notice, the livestream recording, product qualification files, and the appeal statement. The comparison task pairs each claim in a draft appeal statement against the original materials that can be retrieved from the knowledge base. Sources include the platform violation center, livestream replays, customer service records, and the product qualification library. Updates are irregular and each violation starts a fresh round of material collection. The people doing this work are store compliance staff, livestream operations staff, and legal staff. Two features shape retrieval here. First, the appeal statement is written language that makes claims about dates, subjects, and statuses, and those claims need to be checked against source text rather than paraphrased. Second, the source materials mix precise identifiers such as report numbers with narrative descriptions, so a single search mode rarely serves every query.
Constraints at the retrieval step
The knowledge base search node can link one or more knowledge bases that use the same vector model. Knowledge bases using different vector models cannot be linked together. When candidate bases are present, check the vector model identifier first, exclude those that do not match, and record what was observed. Search modes are semantic retrieval, full-text retrieval, and hybrid retrieval. Hybrid retrieval merges multiple result paths through RRF; RRF is a fusion process, not a switch that can be turned on. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used, and it acts as a filter threshold, not as a permission or entity isolation mechanism. The citation limit is measured in tokens and controls how much content a single search can cite. Question optimization performs coreference resolution and question expansion, and enabling it adds one model call before retrieval. Image retrieval requires image input and corresponding model capability; the optional paths listed in the documentation do not mean every request executes all of them.
Hypothetical walkthrough sample. Source text one: "Violation notice states: on 12 March 2025, this store's livestream room was penalized with product broadcast suspension because product qualification display was incomplete; the penalized subject is the livestream room of Store A; the penalty period is 12 March 2025 to 19 March 2025." Source text two: "Product qualification library record: Store A uploaded the quality inspection report for this product on 10 March 2025, report number Q-2025-0310, status passed." Draft sentence to be judged: "This store completed the product qualification upload before the penalty, and the appeal requests cancellation of the broadcast suspension." The comparison subject is the same store, the same product, and the same period. The draft sentence's claim that upload was completed before the penalty matches the date in source text two. Source text one does not state whether the appeal channel is open or whether an appeal has been accepted. The phrase "requests cancellation" in the draft is a handover request and remains in a pending submission state; a retrieval result does not constitute authorization.
Configuration and implementation checks
| Configuration item | Value or check on this page | Basis and explanation |
|---|---|---|
| Linked knowledge bases | Link only appeal material bases that use the same vector model | Cross-model bases cannot be linked; check the identifier first and exclude mismatches |
| Search mode | For this hypothetical walkthrough, start with hybrid retrieval | Report numbers and natural-language claims coexist; compare against semantic retrieval and full-text retrieval separately |
| Citation limit | For this hypothetical trial, start at 2000 tokens | Materials contain penalty period and report number; compare against smaller values for content completeness |
| Minimum relevance | Label relevant and irrelevant samples first, then set the threshold | Takes effect only under semantic retrieval or result reranking; not a permission filter |
| Question optimization | Enable for multi-turn follow-ups or short questions | Compare the original question with the optimized question; check whether the subject was altered |
| Result reranking | Use when a rerank model is available and enabled per settings | Documentation lists this as an optional path; not executed by default on every request |
Three common errors
- Linking knowledge bases that use different vector models. Input: two bases whose vector model identifiers differ. Comparison: check whether the identifiers match. Observable result: identifiers do not match, so exclude the base and do not proceed with retrieval.
- Treating minimum relevance as a permission or entity isolation mechanism. Input: a violation notice belonging to another store. Comparison: check the retrieval result against the current store identifier. Observable result: a relevance score cannot replace subject verification; a person must confirm ownership.
- Writing a pending appeal request as completed. Input: the draft sentence "the appeal requests cancellation of the broadcast suspension." Comparison: check whether source text one states an acceptance status. Observable result: acceptance status is not stated, so record it as pending verification; do not write it as submitted or approved.
How to verify the setup
- Compare source text one with the draft sentence. Input: penalty period 12 March 2025 to 19 March 2025 and the draft claim "completed the upload before the penalty." Comparison: check whether the date fields refer to the same subject and the same period. Observable result: matching dates support only the upload timing claim; the cancellation request remains pending verification.
- Check retrieval hits against source text two. Input: report number Q-2025-0310. Comparison: compare what full-text retrieval returns against what semantic retrieval returns. Observable result: identifier queries can be matched under full-text retrieval; semantic retrieval results need item-by-item checking for the same subject.
- Check downstream behavior with a paper input of an empty array. Input: citation content returns length 0. Comparison: check whether downstream nodes still execute. Observable result: the output path still runs with empty citations; record the gap rather than inferring no violation or that the matter has been clarified.