What this category’s data looks like
Shipbuilding declaration materials and case review data mainly come from ship design drawings, construction progress ledgers, ship inspection declaration documents, completion acceptance files, and other sources. Data update rhythm follows construction project milestones. Materials for single-batch projects are updated in stages during phases such as design confirmation, block construction, and sea trial acceptance. Document structures include long-text design specifications, structured fields such as ship type number, construction batch, inspection date, multi-format attachments including CAD drawings and test report PDFs. Field units involve professional parameters like total tonnage (tons), main engine power (kilowatts), construction cycle (days), and more.
What constraints these characteristics impose on vector models and indexing
Long-text design specifications carry a risk of exceeding per-block token limits, requiring adjustment of chunking rules to match length limits. The coexistence of structured fields and non-text attachments requires index configurations to distinguish association logic between structured metadata and vector text. The staged update feature requires adaptation to incremental index trigger mechanisms to avoid repeated full index execution. Documents dense with professional terminology place higher requirements on the semantic understanding accuracy of vector models, requiring matching vector model parameters adapted for industrial scenarios.
How to set configurations
This content is optimized for FastGPT v4.17.0, for shipbuilding declaration material scenarios.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the per-chapter length of ship design specifications, avoids single-block tokens exceeding model limits |
| Overlap Length | 100–150 characters | Retains contextual association of professional terms between adjacent chunks, avoids semantic breaks across chapters |
| Similarity Threshold | 0.75–0.85 | Matches semantic similarity judgment standards for the shipbuilding professional field, filters general semantic interference |
| Single Search Limit | Top 10 entries | Matches the scale of case files for single-batch reviews, avoids redundant results interfering with review processes |
defaultToken | 8192 | Matches default token limits of mainstream industrial vector models, covers long document parsing needs |
| Max Context | 4000–6000 characters | Matches typical context length requirements during review, supports association judgment for multiple segments of materials |
Three common mistakes
- Similarity scores in retrieval results exceed 0.9 but actual semantic matching fails. The cause is failure to adjust the similarity threshold for shipbuilding professional terminology, amplifying matching deviations of general vector models for professional semantics.
- Supplementary ship inspection standard documents do not appear in retrieval results. The cause is failure to include supplementary data in index source configurations, only synchronizing core declaration files.
- The same case file appears repeatedly in retrieval results when a single case file is associated with multiple attachments. The cause is failure to configure grouped index rules for multi-vector associations, leading to repeated hits after a single data entry generates multiple vectors.
How to confirm the configuration is correct
- Upload a typical ship construction declaration case file, check that the chunked text length falls within the preset chunk range.
- Enter a shipbuilding professional query term, verify that the similarity scores of retrieval results fall within the preset threshold interval.
- Import case files associated with multiple attachments, confirm that no repeated hits of the same case file appear in retrieval results.
- Add a supplementary standard document, trigger incremental indexing, and verify that the document can be retrieved normally.
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.