What this type of data looks like
Coal transportation and sales declaration and file review data comes primarily from business system sales plans, weighing vouchers, purchase and sales contracts, tax invoices, internal compliance manuals, and past review files. Each business batch triggers data updates, with single business data update intervals ranging from several hours to 1 day. Documents are mostly structured tables and semi-structured text, including fields such as coal type, transportation tonnage, settlement amount, review node, and handler. Units include tons, vehicle trips, and yuan/ton.
Constraints on Citation Source and Traceability
Coal transportation and sales business data consists mainly of structured documents and semi-structured text, and requires accurate association of core fields like document numbers and coal types. Retain original document identification information during citation and traceability to avoid splitting that damages field relevance. Each business batch updates data. If the knowledge base does not sync latest documents, traceability content disconnects from current business. A single review may involve multiple cross-cycle files. Ensure recalled sources correspond to specific business links to prevent irrelevant content from interfering with review judgments.
How to Configure
This configuration uses FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to semi-structured paragraph lengths of coal transportation and sales documents, preserving relevance of core fields like coal type and tonnage |
| Overlap Length | 100–150 characters | Prevents splitting of cross-chunk fields like document numbers and review nodes, ensuring complete traceability context |
quoteMaxToken | First 2000 tokens | Limits cited original text length, avoids overwhelming review with redundant content, and matches the content scale of single-batch files |
| Maximum Context | 6000–8000 characters | Carries associated information across multiple cross-cycle documents, meeting traceability needs for full-process review |
detail | Enabled | Forces return of original cited source fields, such as document numbers and weighing dates, to speed review personnel verification |
responseData | Return only matching documents | Filters irrelevant content, ensuring all recalled sources directly relate to coal transportation and sales review business |
Three Common Mistakes
- Phenomenon: Output fails to display citation source document numbers or titles, with empty fields. Cause:
detailconfiguration is not enabled, and original document identification fields are not forced to return. - Phenomenon: Recalled source documents are unrelated to the current coal review batch, and result count exceeds expectations. Cause: No reasonable maximum context length is set, or chunk length is too short, causing loss of field relevance.
- Phenomenon: After uploading new transportation and sales documents to the knowledge base, review requests fail to recall the document, or show old version content. Cause: No regular business system synchronization trigger rule is configured for the knowledge base, creating a disconnect between the knowledge base and business data.
How to Verify Correct Configuration
- Submit a review request for a specific coal transportation and sales weighing voucher, and check if the output includes original fields like the voucher’s number and weighing date.
- View the conversation’s citation source panel, confirm all recalled documents come from the associated coal transportation and sales knowledge base, and that the quantity matches expectations.
- Upload a new transportation and sales contract to the associated knowledge base, submit a relevant review request, and confirm the new document is correctly recalled and used as a citation source.
- Check system logs to confirm the
quoteMaxTokenconfiguration is active, and cited original text fragment lengths match the set values.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.