What data looks like for this category
This category of data originates from regulatory standards, online environmental monitoring equipment, gas detectors, personnel qualification files, equipment isolation lists, and supervision platforms. Daily documents include risk identification records, work tickets for hot work, confined space work, lifting work and similar tasks, environmental monitoring records, hazardous waste ledgers, emission monitoring data, and accident and hidden danger rectification reports. Updates occur upon completion of individual operations, in real time per monitoring requirements, or during regular inspection cycles. Document fields include work type, isolation measures, guardian qualifications, monitoring values and other relevant items. Structure varies slightly across document types, but core fields are consistently defined.
Constraints imposed on vector models and indexing
Multi-source and frequently updated data requires indexes to support incremental updates, to avoid performance loss caused by full reconstruction. The length of different types of documents varies widely, so chunking rules must be adapted to retain key associated information. Core fields such as isolation measures and personnel qualifications must maintain contextual relevance during vector matching, and must not be split across chunks. Incorrect association of work-related documents may lead to safety accidents, so the accuracy of recall results is higher than that of general scenarios, and recall of low-similarity results must be strictly controlled.
How to configure settings
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the average length of single documents such as work tickets and monitoring records |
| Overlap Length | 100–150 characters | Retains cross-chunk information related to work isolation measures and qualification associations |
defaultToken | 4096 | Matches the average token usage of safety and environmental protection documents |
| Similarity Threshold | 0.75–0.85 | Filters low-relevance non-work documents and retains core risk information |
| Single Search Limit | Top 8 entries | Covers multiple types of relevant documents associated with a single work task |
maxToken | 8192 | Supports complete context for long documents such as accident rectification reports |
Three common configuration errors
- Phenomenon: Inaccurate knowledge base capacity estimation, leading to inability to properly plan storage resources. Cause: Failure to calculate total storage requirements by combining the average length and update frequency of single documents such as work tickets and hazardous waste ledgers.
- Phenomenon: 503 errors returned when calling the vector model, or no response from text-embedding related APIs. Cause: Failure to adapt to concurrency limits of localized models, and failure to set reasonable request timeout parameters.
- Phenomenon: Search results omit key isolation measures or work requirements. Cause: Chunk length set too large or too small, leading to core information being split or truncated, preventing complete matching.
How to verify correct configuration
- Import a single typical hot work ticket document, and check if chunked fragments retain complete work type, isolation measures and guardian qualification information.
- Initiate a query containing "confined space work isolation requirements", and verify that the similarity of returned results falls within the preset threshold range.
- Simulate a scenario of continuously uploading multiple real-time environmental monitoring records, and check if indexes complete incremental updates without data loss.
- View vector model call logs in FastGPT v4.17.0, and confirm that request parameters match configuration items.
The values provided are common starting points and should be evaluated against the user's own samples.