What the Data for This Category Looks Like
The core documents for this category include hazard inspection checklists, hazard management ledgers, rectification notices, review records, and major hazard supervision orders. Data is sourced from safety production supervision systems, enterprise self-inspection systems for hazards, law enforcement inspection records, and accident statistics systems. The update frequency is daily. A single document typically includes fixed fields such as hazard ID, hazard type, inspection time, rectification responsible person, rectification deadline, and review result. Some law enforcement documents also include fields associated with on-site photos. All data is generated around the closed-loop hazard management workflow.
Constraints for Vector Models and Indexes
High-frequency data updated daily requires indexes to support incremental synchronization, avoiding excessive time spent on full reconstruction. Mixed storage of multiple document types requires differentiated chunking rules for different document structures, ensuring key fields such as hazard rectification deadlines and review results are fully captured. Unstructured attachments included in law enforcement documents increase the complexity of vector extraction. Hazard data requires high rigor, so retrieved index results must strictly match business fields to avoid irrelevant content interfering with inspection judgments. The number of retrieved results must also be limited to prevent information overload during document drafting.
Configuration Guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the paragraph length of documents such as hazard inspection checklists and rectification notices, preserving complete semantics of key fields |
| Overlap Length | 100–200 characters | Prevents key information spanning paragraphs, such as hazard rectification deadlines and review results, from being truncated |
| Similarity Threshold | Calibrated based on actual testing | Matches the semantic similarity distribution of data in this category, filtering irrelevant retrieved results |
| Single Search Limit | Top 8 entries | Controls the volume of information input during document drafting, avoiding content redundancy |
| defaultToken | 4096 | Adapts to the context window of large models, accommodating combined content from multiple hazard documents |
| maxToken | 8192 | Supports vector indexing of long documents and complete context input after retrieval |
Three Common Misconfigurations
- Vector index construction progress stalls with no updates for long periods. The cause is failure to configure incremental synchronization rules, leading to excessive time spent on full reconstruction of the massive daily updated hazard data.
- Knowledge base retrieval results are irrelevant to the query, returning a large number of unmatched hazard records. The cause is a similarity threshold set too low, or chunk length not matching the document structure, leading to incorrect association of irrelevant semantics.
- Vector model calls time out, and index tasks fail. The cause is failure to adjust reasonable timeout parameters, exceeding the preset waiting duration when processing unstructured attachments of law enforcement documents.
How to Verify Correct Configuration
- Check index task logs to confirm incremental synchronization tasks trigger automatically daily, with no abnormal time spent on full reconstruction.
- Input typical hazard inspection queries, verify that the document types and business fields of retrieved results match the preset hazard data.
- Test importing and exporting configuration packages to confirm that associated settings for vector models and indexes are not lost.
- Check storage statistics in the vector database to confirm that the number of documents per batch of indexing falls within the preset range of chunk lengths.
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.