What this category of data looks like
This category of data mainly comes from meteorological early warning systems, hydrological monitoring systems, emergency command platforms, grassroots disaster reporting systems, and video monitoring. Daily business documents include duty records, early warning notices, consultation minutes, rapid disaster reports, emergency response plans, and material allocation slips. Data is updated daily, and some real-time monitoring data is synchronized at high frequencies. Document fields include duty periods, hourly rainfall, river water levels, material allocation quantities, receiving units, etc. Some documents are attached with metadata such as geographic location and timestamps.
What constraints do these characteristics impose on the "knowledge base retrieval and recall" link
Multi-source and heterogeneous data sources require the retrieval link to support documents in different formats and structured fields, to avoid missed recalls caused by format incompatibility. The daily update frequency requires regular synchronization with the vector database to ensure the timeliness of retrieval results. Ledger summary needs to associate multiple types of documents such as rainfall conditions, water conditions, and material allocations, requiring retrieval to support cross-document associated recall. The high-frequency synchronization of real-time monitoring data imposes clear constraints on retrieval response speed, to avoid affecting the timeliness of emergency consultations. The geographic location and timestamp metadata attached to some documents require the retrieval link to support filtering recall results by spatial and temporal dimensions.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Flood control and disaster prevention data are mostly structured fields. A threshold that is too low will introduce irrelevant disaster records, while a threshold that is too high will miss associated data that meets the matching requirements. Calibrate based on actual tests |
limit | Top 15 entries | Ledger summary needs to cover multiple types of associated documents. Setting the single recall upper limit to 15 balances recall completeness and retrieval efficiency |
searchMode | hybrid | Combines keyword and vector retrieval to adapt to the dual needs of structured fields and natural language queries, meeting the retrieval requirements for drafting consultation materials |
usingReRank | Enabled | Addresses sorting bias issues in multi-source heterogeneous data. Reranking optimizes the relevance ranking of retrieval results and solves the problem of abnormal retrieval result sorting |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands query terms and supplements domain terminology such as rainfall and water conditions, improving the recall effect on professional documents |
collectionIds | Configured for the emergency duty-specific dataset | Limit the retrieval scope to the flood control and disaster prevention-specific knowledge base to avoid interference from irrelevant business data on retrieval results |
Three common mistakes
- Phenomenon: Knowledge base search response times out, the interface shows loading failure or waits for more than 10 seconds. Cause: The retrieval scope is not limited to the dedicated dataset, resulting in recall of excessive irrelevant documents, and the reasonable
limitparameter is not configured, leading to excessive retrieval load. - Phenomenon: After enabling
usingReRank, the retrieval result sorting does not change, and the returned results are consistent with the initial recall order. Cause: The calling parameters of the reranking model are not configured, or the input length of the reranking model exceeds the limit, causing the reranking link to fail to take effect. - Phenomenon: Retrieval result sorting does not meet business expectations, such as comprehensive disaster records being ranked after a single early warning notice. Cause:
usingReRankis not enabled, only relying on initial vector similarity sorting, without adjusting based on document timestamps and importance weights.
How to confirm the configuration is complete
- View the retrieval log to confirm that the number of recall results matches the
limitparameter configuration, and no excessive irrelevant documents are returned. - Manually trigger the reranking link to verify that the sorting order of the returned results differs from the initial recall results, confirming that the reranking function is active.
- Enter a professional query term such as "XX basin rainfall summary" to confirm that associated documents such as rapid disaster reports and hydrological monitoring data for the corresponding period can be recalled.
- Check the vector database synchronization log to confirm that the daily updated flood control data has completed vector embedding, and there are no synchronization failure records.
The values provided here are common starting points and should be measured 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.