What data for this category looks like
Data mainly comes from toll declaration forms, road law enforcement case files, maintenance project submission materials, and toll station traffic data reports generated during expressway operations. Sources include daily completed and archived documents from frontline toll stations, road law enforcement teams, and maintenance project departments. Update frequency fluctuates with business cycles. Regular declaration data is updated daily. Special case review data is uploaded in batches when cases are closed. Most documents are a mix of structured tables and scanned files. They include fixed fields such as road section number, traffic trips, toll amount, and approval document number. Units used include yuan, kilometers, trips, and others.
What constraints these characteristics impose on vector models and indexing
A high proportion of structured tables requires preserving row and column relationships during text splitting to avoid breaking data logic. Mixed format of scanned files and electronic documents requires the indexing process to support both unformatted plain text output from OCR and native structured text. Volatile data volume from batch-uploaded special case files requires the system to adapt to dynamically adjust index shard load. Fixed fields require vector retrieval to support associated field filtering, which narrows recall scope and improves retrieval accuracy. High-frequency updates for regular declaration data require configuring incremental index synchronization mechanisms to avoid performance loss caused by full index rebuilding.
How to set configurations
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the average length of structured tables and OCR text, avoids splitting that breaks business logic |
| Overlap Length | 100–150 characters | Preserves contextual connections across chunks, covers content continuity across table pages |
maxToken | 4096 token | Matches the input limit of general embedding models, adapts to the single-chunk text length of expressway declaration materials |
| Similarity Threshold | 0.72–0.80 | Based on the semantic matching characteristics of fixed fields, filters low-correlation redundant recall results |
| Single Search Limit | Top 10 entries | Controls the scale of the initial recall dataset, adapts to the precise retrieval needs of case file review |
defaultToken | 1500 token | Configures the default token quota for chunks, balances text truncation and information integrity |
Three common mistakes
- Phenomenon: After uploading a single case file scan, the initial display shows 8 chunks. After a period of time, the number changes to 13, with repeated segmented content. Cause: The automatic re-parsing function for OCR results is not disabled. The system repeatedly triggers OCR and chunking processes, leading to redundant segmentation.
- Phenomenon: After upgrading from an older version to FastGPT v4.17.0, previously queryable declaration material content can no longer be recalled. Cause: The underlying storage format of the vector index was adjusted after the upgrade. A full index rebuild was not performed, so existing data cannot match the new retrieval logic.
- Phenomenon: After uploading an Excel-format toll declaration file, the vectorized retrieval results only include header fields, with no detailed traffic data. Cause: The structured table parsing switch is not enabled. The system only extracts plain text header content, and does not parse detailed row data in the table.
How to confirm configurations are properly set
- Upload a typical toll declaration form, check the chunk preview interface, and confirm that table content is not split to break row and column relationships.
- Initiate a case file keyword search, verify that the number of segmented recall results matches the reasonable number of segments for the original document, with no repeated segments.
- After upgrading the system, run a full index rebuild task, and verify that existing case file content can be recalled normally.
- Upload an Excel-format declaration file, check the vectorized text preview, and confirm that detailed table rows have been fully extracted.
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.