What the documents look like
Group-buy presale collection takes orders first and organizes purchasing and fulfillment afterward. Product information and selection questions therefore revolve around four document families: presale product tables, group-order results, purchasing plans, and cut-off notices. These materials update daily or per collection round. Retrieval results feed directly into purchasing plans and cut-off notices, so a wrong or missing reference can lead to stock-out refunds, fulfillment delay, or group-leader complaints.
For this task, product specification, supplier, confirmed group volume, and cut-off time fields are often spread across several documents. Retrieval needs to associate those fields with the same product object. A presale product table may carry a product code, a specification, a supplier, and a cut-off time, while the confirmed group volume sits in a separate group-order result document. The retrieval step can surface candidate text from both, but it does not by itself merge them into a single confirmed fact.
Constraints at the retrieval step
Knowledge base search nodes can associate one or more knowledge bases that use the same vector model. Bases built on different vector models cannot be associated together. The identifier of each base's vector model should be checked first, and any base whose identifier does not match should be excluded and recorded. Retrieval is not authorization. Whether a handover material, operation, or request has been approved must be verified separately; a retrieved document or a submitted form does not establish that state.
Semantic retrieval relies on vector distance. Full-text retrieval relies on keyword hits and suits numbers, models, proper nouns, and error codes. Hybrid retrieval uses both paths and merges them through RRF. RRF is the fusion process inside hybrid retrieval, not a switch that can be turned on. The minimum relevance value is a filter threshold that takes effect only in semantic retrieval or when result reranking is used. The reference cap is measured in tokens. Question optimization performs coreference resolution and question expansion and adds an extra model call before retrieval. Reranking requires a rerank model to be configured and enabled; it produces a 0–1 score that can be used for filtering.
Image retrieval is an optional path. It requires image input and the corresponding model capability, and it depends on whether an image index was built at ingestion time. The overall flow diagram lists optional paths; not every request executes all of them.
Hypothetical exercise sample. Source text for checking: "Presale product table P-2024-0317 states: product code A-102, specification 500 g per portion, supplier Qinghe Farm, cut-off time for this round 17 March 20:00, minimum sales quantity 30 portions." Proposed sentence for judgment: "A-102 has reached the minimum sales quantity for this round and purchasing can be arranged." The proposed sentence concerns whether confirmed group volume was reached. The source text does not state any group-order result quantity. The claim is unsupported until a group-order result document is supplied.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Comparison and explanation |
|---|---|---|
| Associated knowledge bases | One base each for presale product tables, group-order results, purchasing plans, and cut-off notices | Check each base's vector model identifier first; exclude any base whose identifier differs |
| Search mode | Semantic retrieval and full-text retrieval run in parallel | Compare recall for code-type questions against natural-language questions |
| Reference cap | Set to 2000 tokens for this sample | Test with actual materials of differing length to check content completeness, then adjust |
| Minimum relevance | Set to 0.3 for this sample | Label relevant and irrelevant samples first, then compare the filtering effect |
| Question optimization | Enabled in this sample | Compare the original question with the optimized question and check whether the subject was altered |
| Result reranking | Enabled in this sample | Compare candidate ordering before and after reranking and confirm the model is configured |
The starting values above are exercise assumptions chosen for this sample, not official defaults. Each needs a stated reason and a comparison method before any adjustment.
Three common errors
- Treating retrieval or a form as authorized execution. The error is reading retrieved product information as approved purchasing. Check the input as the proposed sentence plus the source text, compare whether either states an authorization state, and observe that when the source text does not state authorization the judgment remains pending verification.
- Associating knowledge bases that use different vector models. The error is placing bases with different models into one retrieval scope. Check the input as each base's vector model identifier, compare whether the identifiers match, and observe that a mismatched base is excluded and recorded.
- Describing RRF as a switch that can be turned on. The error is presenting the fusion process as a configuration item. Check the input as the search mode setting, compare it against how the documentation positions RRF, and observe that when RRF appears only as the fusion process of hybrid retrieval the description is judged incorrect.
How to verify the setup
- Input the hypothetical sample source text and the proposed sentence. Compare "has reached the minimum sales quantity" in the proposed sentence against whether the source text states a group-order result quantity. Observe that when the source text does not state that quantity the claim is unsupported and a group-order result document must be supplied.
- Input each knowledge base's vector model identifier. Compare whether the identifiers match. Observe that association is permitted only when the identifiers match; when they do not, exclude the base and record the actual observation.
- Input an explicit paper empty-result array. Compare whether the downstream design accepts a reference output of length 0. Observe that the downstream path completes when it accepts the empty result. Do not claim that a fabricated rule retrieval will necessarily return an empty array.
These checks describe expected observations. No test, deployment, approval, refund, or other business action is claimed to have occurred. Where the source text does not state a field, the field remains unknown and the judgment remains pending verification.