What the documents look like
Group-buy presale collection takes orders first and organizes procurement and fulfillment afterward. Inventory procurement and supplier materials therefore revolve around four document types: the presale product table, the collection result, the procurement plan, and the cut-off notice. These materials come from mini-program orders, supplier inventory, group-leader feedback, and warehouse routing, and they update daily or once per session. For document parsing and chunking, the structure of each material determines whether a segment remains usable. The presale product table carries product names, specifications, and supplying entities. The collection result carries session and quantity. The procurement plan carries suppliers and arrival requirements. The cut-off notice carries a time boundary. Each of these supports a different judgment. If a specification condition is separated from the product entity, or a cut-off time is separated from the applicable session, the retrieved fragment cannot point back to the source text, and procurement staff checking supplier materials receive incomplete grounds. Supplier materials and procurement plans often contain numbers, models, and proper nouns, so chunking must preserve these exact identifiers.
Constraints at the document chunking step
Chunking follows the structure of the material itself, keeping conditions, explanations, and the content they constrain inside one data block. Original data and retrieval indexes are treated separately: one set of original data can correspond to multiple indexes, and adding indexes does not change the original data content. During retrieval, vectors are recalled first, then the vector ID is used to find the original data in MongoDB; if the same set of original data is matched, the results merge and the vector score takes the highest value. After a material update, the actual training and index status must be checked; a successful upload does not mean retrieval has updated. Semantic recall and relevance scores express similarity only and do not carry permission, entity, or supplier isolation. The same-vector-model requirement for a retrieval library is limited to association inside that library and does not extend to external systems. Hybrid retrieval merges multiple result paths through RRF, which is a result-merging process. An empty result can accept a clearly defined paper input to check downstream design; it does not mean a fabricated rule retrieval necessarily returns empty.
Hypothetical drill sample: the source material reads "Cut-off notice for 18 March 2024: the cut-off time for this session 'Spring Vegetable Session A' is 18 March 2024 at 20:00, the applicable supplier is Cooperative A, and the procurement plan number is CG-0318. The leafy-vegetable presale product table supplied by Cooperative A lists a specification of 500 grams per portion." The draft sentence to be judged is "Cooperative A may still add supply for this session's leafy vegetables after 18 March at 20:00." This request involves the entity Cooperative A, the object Spring Vegetable Session A leafy vegetables, the time boundary 18 March at 20:00, and number CG-0318. The authorization scope is not stated in the material.
Configuration and implementation checks
The table below centers on the sample above and lists documented settings and manual checks relevant to this function. The values are starting points for this hypothetical trial, used for comparison, and do not represent default values.
| Configuration or check item | Hypothetical trial starting point | Reason for selection and comparison method |
|---|---|---|
| Search mode | Hybrid retrieval | The sample contains number CG-0318 and a natural-language supply question; compare semantic recall and full-text recall hit differences |
| Minimum relevance | Hypothetical starting point 0.3 | Used to filter low-relevance fragments; compare with the recall count when no threshold is set |
| Reference limit | Hypothetical starting point 2000 tokens | Controls the amount of referenced content; compare with the actual length of the cut-off notice plus procurement plan |
| Question optimization | Not enabled for now | The sample question has a complete subject; compare with retrieval time and hits when enabled |
| Result reranking | Not enabled for now | Requires a rerank model; compare with ranking changes when enabled |
| Chunking check | Manual check by material structure | Check whether specification and time boundary stay in the same block as the subject; compare with source-text back-reference |
Three common errors
- Splitting the cut-off time and the applicable session into different data blocks. Input is the sample cut-off notice source text. Compare whether the retrieved fragment contains both "Spring Vegetable Session A" and "18 March at 20:00." If only the time or only the session returns, the chunking does not satisfy the back-reference requirement.
- Treating a retrieval hit as grounds for authorization. Input is the draft sentence "Cooperative A may still add supply for this session's leafy vegetables after 18 March at 20:00." Compare whether an authorization clause exists in the material. The material does not state additional-supply permission, so the request is unsupported and cannot be judged as authorized or denied.
- Treating a successful upload as an updated index. Input is the supplier material update operation record. Compare the actual training and index status. If only upload completion appears without a training completion marker, whether retrieval has updated remains unknown.
How to verify the setup
- Input the two source passages, the sample cut-off notice and the procurement plan. Compare whether the retrieved content contains the entity Cooperative A, the session Spring Vegetable Session A, number CG-0318, and the time boundary 18 March at 20:00. All four appearing together satisfies the back-reference condition; record any missing item as a gap.
- Input the draft sentence "Cooperative A may still add supply for this session's leafy vegetables after 18 March at 20:00." Compare the authorization field in the material. The material does not state additional-supply permission, so the judgment is unsupported, and the evidence gap is retained without fabricating an authorization clause.
- Input the paper empty result []. Compare how the downstream design handles an empty reference. Do not claim that a fabricated rule retrieval necessarily returns empty; check only the empty-result handling logic. For libraries using different vector models, check the identifier first and exclude non-matching ones, record the actual observation, and do not run cross-model retrieval to compare missed recalls.