What Data for This Category Looks Like
Data for this category comes 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, and lifting work. They also include environmental monitoring records, hazardous waste ledgers, emission monitoring data, and accident and hidden danger rectification reports. Updates to this data trigger when individual operations complete, follow monitoring cycles, or during regular inspections. Document fields include operation time periods, equipment identifiers, detection values, qualification numbers, and more. There is no unified fixed format. Formats adjust based on operation types and regulatory requirements.
Constraints Imposed by This Category’s Data Characteristics on Knowledge Base Retrieval and Recall
The data characteristics of this category create multiple constraints for retrieval and recall. First, data sources are scattered, and update frequencies vary greatly. There are both high-frequency real-time monitoring data and discrete documents from individual operations. Balance efficiency between real-time retrieval and batch recall. Second, documents have no unified format, and fields are scattered. Support multi-field associated matching to avoid losing key information due to format differences. Third, the data covers safety, environmental protection, and operation permits. Recall results must strictly match business scenarios and compliance requirements. Filter low-match irrelevant content to ensure decision accuracy. Finally, the data covers all process operation scenarios. Limit retrieval scope to exclusive datasets. Avoid introducing documents from unrelated categories.
How to Configure the Settings
The following configurations use FastGPT v4.17.0. They are adapted for the production ledger scenario of safety, environmental protection, and special operations management.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Meets the rigor requirements of safety and environmental protection documents, filters low-match irrelevant content, and avoids incorrect references to non-relevant operation specifications |
limit | Top 8 entries | Controls the number of recall results to avoid context overload, while covering multiple types of operation-related documents |
searchMode | mixedRecall | Combines keyword and semantic retrieval to support precise matching of multi-format documents such as work tickets and monitoring records |
usingReRank | Enabled | Re-ranks initial recall results to prioritize high-priority documents related to operation scenarios, aligning with decision-making needs for safe operations |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands retrieval terms to cover synonyms of operation scenarios and regulatory terminology, improving recall coverage |
collectionIds | Bound to exclusive datasets for safety, environmental protection and special operations | Limits retrieval scope to avoid introducing documents from unrelated categories, ensuring recalled content complies with regulations |
Three Common Misconfigurations
- Issue: Upload structured table datasets such as hazardous waste ledgers and work tickets. Some numerical fields fail to retrieve normally. Recall results miss corresponding data. Cause: The configuration omits dedicated field indexing rules for structured data. It uses only default semantic chunking. This causes loss of field information.
- Issue: Submit a query for an edge operation scenario not covered by the knowledge base. The AI still returns referenced content from existing work tickets in the knowledge base. Cause: The configuration sets no reasonable
similaritythreshold. It also disablesusingReRankto filter low-match results. This leads to incorrect recall of irrelevant documents. - Issue: Configure a tool flow. The AI cannot associate real-time monitoring data for special operations during knowledge base retrieval. Cause: The configuration fails to limit retrieval scope to the exclusive dataset via
collectionIds. The retrieval range includes non-real-time historical archives. These archives cannot match real-time monitoring field requirements.
How to Verify Successful Configuration
- Upload a test confined space work ticket document. Submit a corresponding query. Check if recall results include relevant fragments of this document.
- Adjust the
similarityparameter range. Verify if recall match degree meets safe operation rigor requirements. Confirm the threshold fits the current dataset. - Submit a query for content not present in the knowledge base. Confirm the AI does not return irrelevant document references. Verify the filtering logic works.
- View the retrieval log. Confirm only the bound exclusive dataset appears in the retrieval scope. No documents from other categories are included.
The values provided are common starting points and should be measured against the reader's own samples.