What the documents look like
Cross-border standalone-site payment risk work revolves around card-network disputes and receiving accounts. The evidence set includes payment chargeback notices, fraudulent order lists, invoices, and logistics proof of delivery. Procurement and supplier records form one slice of that set: they record purchase batches, supplier names, goods quantities, payment status, and delivery evidence. These records cross over into dispute evidence chains, so a purchase invoice for one batch of goods may serve both to explain inventory origin and to answer a dispute.
The brief gives a daily and per-order update frequency. For this page, the relevant consequence is that chunking must be organized by batch. Records from different dates should not be merged into one data block, because a dispute review may need to isolate one batch's invoice and delivery proof without pulling in unrelated purchase dates.
Constraints at the document chunking step
Chunking has to preserve the complete semantic unit of a procurement record. Supplier name, purchase batch number, goods quantity, amount, payment status, and the corresponding invoice number should stay inside one data block. Conditional statements and the content they constrain must not be split apart. FastGPT stores original data in the MongoDB dataset.datas table, with an indexes field holding the corresponding vector IDs as an array, so one group of original data can map to multiple vectors. Longer text can use multiple indexes to raise retrieval precision, at the cost of a narrower retrieval scope per index.
Assume a paper exercise sample. Material text for comparison: supplier "Huachen Trading" issued a purchase invoice on 10 March 2026, invoice number HC-20260310-07, goods are 1,200 Bluetooth earphones, amount RMB 86,400, payment status "30% deposit paid." The logistics proof of delivery for the same batch shows a signed date of 18 March 2026 and a signed quantity of 1,200 units. Draft sentence to be judged: "This purchase has completed full payment and settled the supplier account." The fields needed for judgment are payment status and settlement status. The source text records only a 30% deposit paid and does not state full payment or settlement. The draft sentence is unsupported by the supplied wording.
Configuration and implementation checks
The table covers settings documented for this feature and implementation checks tied to this page's sample. Values marked as a starting point are hypothetical for this exercise, not documented defaults.
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| Search mode | Hybrid search | Batch numbers and supplier names contain exact identifiers; semantic and full-text recall run together. Compare recall for an identifier query against a natural-language query. |
| Reference limit | Measured in tokens, starting at a length that covers one full procurement record | The official text controls the reference limit by tokens rather than top k, because chunk lengths vary widely in mixed knowledge bases. Compare whether a smaller starting point truncates key fields. |
| Minimum relevance | Starting point 0.5 | The official text states this value takes effect only under semantic search or with result reranking. Compare whether raising it filters out low-similarity results that still contain the batch number. |
| Question optimization | Off for a single-turn, explicit question | The official text states question optimization adds one model call and increases overall latency. Compare retrieval before and after enabling it across consecutive follow-up turns. |
| Result reranking | Enabled per configuration | The official text states reranking depends on the model and is enabled by configuration. Compare the ordering produced by rerank scores against vector scores. |
| Image index | No image input in this sample; no image index built | The official text states image retrieval requires image input and model capability. This sample is plain text. |
Three common errors
- Reading "30% deposit paid" as "settled." Input is the invoice text above; the compared field is payment status; the source does not state settlement. The judgment remains unsupported, and the record must not be marked settled.
- Treating retrieval recall as authorization to execute. Retrieving a procurement record means only that the content can be cited. It does not mean payment, approval, or supplier cooperation has taken effect. Input is a retrieval request; the compared object is an authorization status field; the two are different.
- Associating libraries across different vector models. Input is the vector model identifier of two libraries; compare whether the identifiers match. When they do not match, exclude that library and record the observation. Do not run a cross-model retrieval to compare missed recalls.
How to verify the setup
- Input the invoice text above and the draft sentence. Compare "full payment and settled" in the draft against "30% deposit paid" in the source. The same field holds mutually exclusive values, so the observable result is a judgment of unsupported. This is the expected result and was not actually tested.
- Input batch number HC-20260310-07 and the natural-language question "how much has Huachen Trading paid on that earphone batch," and search each separately. Compare whether both retrieve the same data block. If both hit the block containing that batch number, the chunking meets the identifier and semantic dual-path need. If the identifier query does not hit, check whether that block has completed training and indexing.
- Input an empty reference list
[]to check the downstream display design. Compare whether the downstream side stays in a waiting or logging state when no references are present. This check addresses downstream design and does not claim that a fictional rule retrieval necessarily returns an empty result.
This page covers only cross-border standalone-site payment risk / procurement and supplier records / document parsing and chunking. At operational handover, the authorization state of materials, operations, and requests must not be confused with retrieval or form submission.