What this category of data looks like
This data comes from work safety supervision systems, enterprise hidden danger self-inspection systems, law enforcement inspection records, and accident statistics systems. It updates daily. Daily documents include hidden danger investigation checklists, hidden danger governance ledgers, rectification notices, review records, and major hidden danger listing and supervision orders. Fields cover hidden danger ID, investigation time, responsible entity, rectification deadline, and review results. The data uses standard formats for government and work safety domains, with no custom special units.
Constraints on vector models and indexes
The daily update requirement mandates indexes support incremental synchronization. This avoids resource consumption from full reindexing. Mixed document formats require adapted chunking logic for structured ledgers and unstructured notices. Standardized fields cover core business nodes. This ensures vector extraction covers key information including hidden danger investigation, rectification, and review. Law enforcement records and accident statistics data have strong correlations. This requires support for cross-document associated recall to prevent scattered retrieval results.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the single-page content length of hidden danger ledgers and rectification notices, avoids damaging business logic integrity via chunking |
| Overlap Length | 100–150 characters | Covers key information such as cross-chunk rectification deadlines and review nodes, prevents key content from being truncated |
| Similarity Threshold | 0.75–0.85, calibrated via actual testing | Matches semantic similarity standards for government documents, filters low-relevance non-business results |
defaultToken | 4096 | Adapts to context length requirements for policy basis Q&A, covers associated content from multiple rectification and review documents |
maxToken | 8192 | Supports full vector recall for long documents, meets full information extraction for major hidden danger listing and supervision orders |
| Single Search Limit | Top 8 entries | Balances retrieval efficiency and recall completeness, covers associated documents from the same batch of hidden danger investigations |
Three Common Configuration Errors
- After uploading chunk mode data via the pushdata API, the interface always displays "indexing in progress". Cause: Incorrect matching between configured chunk length and document format, leading to chunk verification failure and blocked index processes.
- The final set of indexes after Q&A splitting cannot pass verification. Cause: Overlap length set too small, leading to incomplete extraction of key business fields in the final chunk set, making vector matching fail to meet threshold requirements.
- Overall relevance of search results is low, with all returned results having insufficient association with query intent. Cause: Similarity threshold set too low, failing to filter non-work safety documents with irrelevant semantics, or the vector model not adapted to professional terms in the government domain.
How to Confirm Correct Configuration
- Review incremental synchronization logs, confirm newly added daily hidden danger investigation data completes indexing within a reasonable timeframe, with no blocking errors.
- Manually input typical query terms, verify returned results include core business fields such as hidden danger ID and rectification deadline, adjust the similarity threshold to a range meeting business requirements.
- Upload a single major hidden danger listing and supervision order, check that chunked vectors cover all key content with no information truncation.
- Call the test interface, verify chunk mode uploaded data completes indexing normally, with no long-term blocking state.
The values provided here are common starting points, and should be evaluated 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.