What data looks like
Data sources for multi-source monitoring data fusion include real-time data collected by industrial sensors, equipment ledger archives, operation and maintenance inspection logs, and video frame analysis results. Sensor data updates from seconds to minutes. Equipment ledgers and historical logs sync once per day. Each data entry includes fields for unique device identifier, collection timestamp, monitoring value, preset threshold, and alarm level. Units cover standardized engineering units such as degrees Celsius, millimeters per second, and percentage humidity.
Constraints for knowledge base retrieval and recall
Second-level real-time updates of multi-source data require the retrieval and recall pipeline to adapt to high-frequency data synchronization. The pipeline must avoid recalling stale data outside a reasonable time window. The multi-field composite structure requires retrieval to match multiple dimensions such as device identifier, monitoring value, and alarm level. Single-keyword recall cannot cover complete business logic. Structured sensor data and unstructured video analysis fragments are stored in mixed formats. The system must adapt to chunking and matching rules for different formats. It must avoid disjoint recall results that cannot link multi-source monitoring information for the same device.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Adapts to composite field matching for multi-source data, avoids recalling irrelevant monitoring data with low matching scores |
limit | Top 8 entries | Balances alarm analysis response speed and information completeness for inspection scenarios, avoids context overload |
usingReRank | Enabled | For mixed-format multi-source data, re-ranking optimizes relevance ranking of matching results, improves alarm analysis accuracy |
datasetSearchUsingExtensionQuery | Enabled | For colloquial alarm descriptions in inspection scenarios, optimizes semantic expansion of user queries, covers associated retrieval needs for multi-source data |
collectionIds | Fill in IDs of bound multi-source monitoring knowledge bases as needed | Ensures only multi-source monitoring data within the target knowledge base is retrieved, avoids invalid recall across datasets |
searchMode | Hybrid search | Covers both structured field matching and unstructured text matching, adapts to mixed storage structure of multi-source data |
Three common configuration mistakes
- An API call returns empty results with no matching data fields. The cause is incorrect configuration of the
collectionIdsparameter during cross-team deployment. The retrieval scope does not cover multi-source monitoring data in the target knowledge base. - A large number of non-target device monitoring data appears in retrieval results. The cause is failure to set a reasonable
similaritythreshold, or failure to enable hybrid matching forsearchMode. This leads to recalling irrelevant data using only single keywords. - Response timeout occurs due to overly long context for alarm analysis. The cause is failure to limit the
limitparameter value. Excessive redundant historical monitoring data is recalled, exceeding the system context capacity limit.
How to confirm correct configuration
- Input a monitoring alarm description for a single device manually. Verify that recall results include multi-source monitoring data for that device.
- Call the retrieval interface. Verify that the number of returned results matches the configured requirements.
- Compare recall result rankings with and without
usingReRankenabled. Confirm that the re-ranking function is active. - During cross-team deployment, verify that only knowledge base data bound to the specified
collectionIdscan be retrieved.
The values provided 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.