What This Category of Data Looks Like
This category of data originates from work safety supervision systems, enterprise hazard self-inspection systems, law enforcement inspection records, and accident statistics systems. It is updated daily. Daily documents include hazard investigation checklists, hazard governance ledgers, rectification notices, review records, and major hazard suspension and supervision orders. Data fields include hazard ID, investigation subject, rectification deadline, review results, and more. There are no exclusive custom units. The document structure uses a single hazard item as the basic unit, and links full-process records for rectification and review.
Constraints Imposed on Knowledge Base Retrieval and Recall
Daily data updates require the retrieval pipeline to support high-frequency incremental synchronization. This prevents recalling expired hazard rectification records or policy provisions. Documents are linked to multi-stage workflows. Retrieval must match associated fields such as hazard ID and rectification deadline, to avoid recalling irrelevant content across documents. Single documents contain multiple types of critical information. The context length of a single recall must be limited, to stay within model processing limits. Data sources cover multiple systems. Unified field mapping rules must be implemented to ensure consistent semantic matching during retrieval.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the precise matching needs of hazard investigation, to avoid low-relevance policy provisions being included in recall results |
limit | Top 10 entries | Covers multiple types of policy basis corresponding to a single hazard, while controlling the total context length |
searchMode | semantic | Matches the semantic association between policies and hazards, suitable for unstructured regulatory provision retrieval |
usingReRank | Enabled | Performs secondary sorting on initial recall results, corrects deviations in semantic matching, and highlights clauses directly related to hazards |
datasetSearchUsingExtensionQuery | Enabled | Expands relevant policy terminology based on the original question, improving recall coverage of professional regulatory basis |
collectionIds | Bind the collection ID of the corresponding hazard investigation and governance knowledge base | Limits the retrieval scope, to avoid interference from cross-category data |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Configuration Errors
- An empty recall result is returned after calling the API to trigger retrieval. This occurs when the
collectionIdsparameter is not configured correctly, or the passed collection ID does not correspond to the exclusive knowledge base for current hazard investigation and governance. - Recall results include policies or documents unrelated to hazard investigation. This occurs when the
similaritythreshold is set below 0.75, orusingReRankis not enabled for secondary filtering. - The generated answer does not reference professional knowledge base content. This occurs when
datasetSearchUsingExtensionQueryis enabled and general knowledge weight is too high, or knowledge base incremental synchronization has not completed.
How to Verify Correct Configuration
- View the knowledge base collection list in the FastGPT backend. Confirm the ID bound by the
collectionIdsparameter matches the hazard investigation and governance knowledge base used by the current business. - Enter a typical hazard investigation question. Check that the
similarityscore of the recall result falls within the 0.75–0.85 range. - Confirm the total number of retrieval results does not exceed 10 entries, aligning with the
limitparameter configuration. - Compare recall results to original policy documents. Confirm that when
usingReRankis enabled, top-ranked results are directly related to the current hazard item.
The values provided here are common starting points, and should be evaluated against your own specific 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.