What the data for this category looks like
Coal transportation and sales inquiry and reply data mainly comes from coal purchase and sales contracts, railway/road waybills, weighing measurement sheets, settlement reconciliation vouchers, industry supervision notices, and past customer inquiry records. Most data uses structured fields. These include clear items such as goods category, shipping station, receiving station, transportation tonnage, freight rate standard, and settlement cycle. The dataset also includes a large number of unstructured resources, such as scanned waybills and contract PDFs. Waybill data is updated daily. Purchase and sales contracts are updated per performance cycle. Supervision documents are released as needed.
Constraints on Vector Models and Indexing
Coal transportation and sales structured data includes multi-dimensional business fields. Retain associations between fields in vector indexes. Do not split blocks that break business logic. Unstructured scanned documents have complex layouts including tables and signatures. Extract table content first and convert it to structured format during index construction. Data update cycles vary significantly. Configure incremental index refresh for real-time updated waybill data. Use fixed-cycle full reconstruction for periodically updated contract data. Business field units and value ranges are fixed. Adapt vector models to structured field encoding logic. Ensure accurate matching of business keywords during retrieval.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Coal transportation and sales business documents often contain long paragraphs of contract terms and waybill details. This range preserves business logic integrity and avoids splitting critical information across blocks |
| Overlap Length | 100–200 characters | Prevents loss of cross-block business information in long documents. Ensures retrieval can associate complete business context |
| Similarity Threshold | 0.75–0.85 | Matches precise business keywords and field values in coal transportation and sales operations. Filters low-relevance search results |
| Single Search Limit | Top 10 results | Controls the number of returned search results. Fits the high-frequency short query scenario of business inquiries |
defaultToken | 8000 | Adapts to the average length of coal transportation and sales documents. Ensures sufficient context can be loaded for a single retrieval |
maxToken | 12000 | Covers complete chunked content of long documents. Avoids truncation of critical business information due to token limits |
Three Common Configuration Mistakes
- Observation: Two knowledge base matching results are returned during retrieval. The specified knowledge base index cannot be prioritized. Cause: The associated settings for knowledge base priority are not configured correctly. The retrieval weight of the target knowledge base is not increased.
- Observation: A 60-second timeout error is returned when calling the retrieval interface. The interface shows the index task is running. Cause: Incremental index refresh is not configured for incrementally updated waybill data. Full reconstruction of large volumes of historical waybill data triggers a timeout.
- Observation: A parameter error is returned by the interface when adding indexes to document chunks in a collection in bulk. Cause: Required fields for bulk index requests are not filled according to specifications. The association parameters between the collection ID and document chunks are not specified correctly.
How to Confirm Proper Configuration
- Navigate to the vector index settings page for the knowledge base. Check the chunk length and overlap length configuration values. Confirm they match the length characteristics of business documents.
- Initiate a simulated business inquiry. Check the matching degree of search results. Adjust the similarity threshold to a range that fits business requirements.
- Test triggering an incremental index refresh. Check if task duration falls within a reasonable range. Confirm no timeout limit is triggered.
- Review bulk index request documents. Confirm required parameters are filled according to specifications. Bulk index tasks can be triggered normally.
The values listed are common starting points. They should be evaluated against sample data relevant to the specific deployment.
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.