What the documents look like
Marketplace refund and return handling occurs continuously per order, not around a single livestream commitment. The materials come from the after-sales backend, customer service chat, WMS receiving, and payment refund records. Daily documents are refund applications, return logistics labels, quality inspection photos, and refund approvals. Product data and selection Q&A must answer whether model numbers, specifications, and accessories match, so the retrieval objects include both text descriptions and inspection photos. The brief gives an update frequency of per order and daily; this page states only that and does not infer batch or real-time mechanisms.
For this category, a refund application records the order, item, and requested amount. A return logistics label records the shipment back to the warehouse. A quality inspection photo records the condition observed at receiving. A refund approval records the decision state. These are separate documents at separate stages, and a value in one does not complete another.
Constraints at the vector indexes step
Knowledge bases associated for retrieval must use the same vector model. Check the actual model and input type before associating them. A single original data block can be linked to multiple indexes; the indexes and the original content are checked separately. Image retrieval also depends on whether image descriptions or image vectors were generated at ingestion; uploading an image at query time does not create an index. Semantic retrieval, full-text retrieval, hybrid retrieval, and result reranking are optional paths. Image retrieval requires corresponding image input and model capability. Reranking requires a rerank model and must be enabled by configuration. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used, and it is a filtering threshold, not a permission or entity isolation mechanism. RRF is the fusion process for hybrid results.
A refund approval marked pending is not a completed approval. A quality inspection photo that does not record a model comparison conclusion does not supply that conclusion. An unsigned termination is not a completed termination. Retrieval is not authorization, and a form that collects values does not by itself perform business verification, approval, database writes, or external synchronization. Those require their stated downstream implementation.
Hypothetical paper test case: An after-sales specialist submits a draft sentence, "The item in this order does not match the model selected by the customer, and a refund is agreed based on the quality inspection photo conclusion." The material text for comparison is: "Refund application R-0417, order date March 2, 2025, item is two A-type filter elements; the quality inspection photo shows outer packaging damage and does not record a model comparison conclusion; the refund approval field is pending review." The draft sentence combines a pending state and a model mismatch conclusion into one fact. The material does not state a model comparison conclusion and does not state a completed approval.
Configuration and implementation checks
| Configuration or check item | Purpose on this page | Basis and comparison method |
|---|---|---|
| Vector model identifier | Determine whether multiple knowledge bases can be associated | Read the model identifier per knowledge base; exclude those with inconsistent identifiers; do not perform cross-model retrieval |
| Original data and indexes | Check the indexes linked to one data block against its original text | Open the dataset.datas record and compare the indexes array with the original content |
| Index content length | Weigh retrieval coverage against index length | For this hypothetical trial, the starting value is a shorter index; the reason is that model-number questions require focus; compare cited original text with a longer-index sample |
| Image index | Check whether image descriptions or image vectors were generated at ingestion | Inspect the ingestion record for the corresponding index; a query-time image upload does not replace this check |
| Reference limit | Control the tokens of content cited per search | Measured in tokens; compare with the length of returned cited content |
| Minimum relevance | Filter low-relevance results | Takes effect only under semantic retrieval or result reranking; compare with the rerank score |
Three common errors
- Treating a query-time quality inspection photo upload as an established image index. Check the input as the image index field in the ingestion record, compare whether the query-time image and the ingestion index exist, and observe that an empty index field indicates the index was not established.
- Reading a pending refund approval field as an agreed refund. Check the input as the value of the refund approval field, compare the draft sentence wording with the material text, and observe that a pending value indicates the statement is not supported.
- Associating knowledge bases with different vector models and then inferring missed recall. Check the input as each knowledge base model identifier, compare whether the identifiers are consistent, and observe that inconsistent identifiers cause that knowledge base to be excluded and recorded, without asserting a runtime result.
How to verify the setup
- Input the hypothetical draft sentence and the material text, compare the subject, object, state, and effective scope, and observe that when the draft sentence contains a model comparison conclusion and a completed approval state not stated in the material, the sentence is judged unsupported.
- Input the approval field value of refund application R-0417, compare it with the wording "refund agreed," and observe that when the value is pending review, the evidence gap is retained and approval completion is not judged.
- Input each knowledge base model identifier, compare whether the identifiers are consistent, and observe that inconsistent ones are excluded and the actual observation is recorded. An empty result can be checked against the downstream design using the explicit paper input [], without claiming that retrieval necessarily returns an empty array.