What the documents look like
General trade import declaration work handles a fixed set of documents on every shipment: the import declaration form, commercial invoice, packing list, bill of lading, and contract. The data sources named in the brief are the International Trade Single Window, the customs tariff, the freight forwarder's arrival notice, and foreign exchange payment vouchers. For the inventory procurement and supplier records task, document parsing and chunking works on the correspondence between the same shipment's procurement record and its declaration record. The fields that matter are the transaction terms, the dutiable value, freight and insurance, and the tax payment basis, and the question is whether those fields can be split into complete chunks and traced back to the source document.
These materials update per shipment. The import declaration form, invoice, packing list, bill of lading, and contract each have a different structure, and the same shipment's description, quantity, amount, currency, and transaction terms are spread across several files. Chunking has to preserve the document identity and version that allow a chunk to point back to its source, and it has to avoid separating a condition or note from the field it constrains.
Constraints at the document chunking step
Chunking precision directly affects whether retrieval can reassemble one shipment's fields into a complete meaning. In FastGPT a knowledge base consists of library, collection, and data. The smallest search unit is the library; collections only classify data and do not affect search results. One data record can map to multiple vectors, and when several vectors match the same source record the highest score is kept. A single procurement passage can therefore carry separate indexes by supplier, by declaration number, and by product name.
Semantic search relies on vector distance. Full-text search suits numbers, models, proper nouns, and error codes. Hybrid search merges the two paths through RRF, and a ReRank model produces a 0-1 score used for filtering. The minimum relevance value takes effect only under semantic search or when result reranking is used, and it is a filter threshold that does not perform permission or entity isolation. Retrieval results do not constitute authorization. Values collected by forms require downstream implementation to carry out business verification, approval, database writes, and external synchronization.
Hypothetical paper exercise: an importer's customs manager receives one shipment's procurement materials. The source text for comparison is three sentences. First sentence: "Supplier A issued commercial invoice INV-2025-0310 on 10 March 2025, amount USD 48,000, transaction terms CIF." Second sentence: "The corresponding bill of lading B/L-0310 states the port of loading as Busan, the port of discharge as Shanghai, and 120 packages." Third sentence: "Procurement contract CT-2025-03 sets payment terms of telegraphic transfer 30 days after sight of the bill of lading copy." The draft sentence to be judged is: "This shipment has completed import declaration and paid all taxes, and the inventory can be booked." The question is whether the draft sentence is supported by the three source sentences above.
Configuration and implementation checks
The configuration below stays with the sample and lists only settings documented in the official material or implementation checks tied to this page's task. The numeric values are starting points for this hypothetical exercise, used to compare against retrieval output. They are not official defaults.
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| Search mode | Hybrid search | The sample contains identifiers INV-2025-0310, B/L-0310, and CT-2025-03, so semantic and full-text recall are both needed before RRF merging |
| Reference limit | 3000 tokens | The three source sentences plus the draft sentence are short; start here and observe whether the referenced content covers all fields, then compare with a smaller value |
| Minimum relevance | 0.3 | Under semantic search this filters low-relevance results; compare recall content against 0.1 and 0.5 |
| Question optimization | Not enabled in this exercise | The sample question has a clear subject; observe retrieval without it first, then decide whether to compare the enabled case |
| Result reranking | Not enabled in this exercise | The candidate set is small; observe ordering without reranking, then compare against scores with it enabled |
| Chunk review | Check separately by document type | Verify that the invoice, bill of lading, and contract segments are each complete and can point back to source identity and version |
Three common errors
- Treating a successful upload as an updated index. After materials change, the actual training and index state has to be checked; the upload action itself does not mean new content has entered the searchable range. Check: input the amount field of INV-2025-0310 from the sample and compare whether the returned content is USD 48,000. If the old value still returns, the index has not updated.
- Using retrieval results in place of an authorization judgment. Contract CT-2025-03 in the sample sets a payment term; retrieving that sentence does not mean payment has been executed or goods have been released. Check: input "has this shipment paid all taxes" and compare whether the returned content contains a tax payment record. If it does not, record the claim as unsupported.
- Treating minimum relevance as an entity filter. Minimum relevance is a 0-1 filter threshold and does not exclude unrelated suppliers or unauthorized records. Check: input another supplier name and compare whether the returned content still includes the sample documents. If it does, the threshold performed no entity isolation.
How to verify the setup
- Input the three source sentences from the sample and compare whether the returned content covers the invoice amount, the bill of lading package count, and the contract payment term at the same time. Observe whether each of the three segments is complete and can point back to its source.
- Input the draft sentence "This shipment has completed import declaration and paid all taxes, and the inventory can be booked" and compare whether the returned content contains a direct record of declaration completion and tax payment. Observe whether only stage evidence such as the contract payment term returns. If only that returns, judge the draft as unsupported.
- Input an empty-reference check scenario using the paper input [] and examine how the downstream design handles an empty result. Observe whether the system returns empty content and how the following process continues. Do not assume that a fictional rule necessarily returns an empty result.
This page addresses only general trade import declaration, inventory procurement and supplier records, and document parsing and chunking. At handover, the authorization state of materials, operations, and requests must not be inferred from retrieval or form submission.