What data for this category looks like
Data for this category comes from meteorological warning systems, hydrological monitoring systems, emergency command platforms, grassroots disaster reporting systems, and video surveillance. It updates once per day. Daily documents include duty logs, warning notices, consultation minutes, rapid disaster reports, emergency response plans, and material allocation slips. Most data fields contain real-time rainfall and water level values, warning levels, affected areas, material allocation quantities, and similar metrics. Structure varies widely based on document type. Some data is structured, automatically generated by systems. Other data is unstructured text filled out manually.
Constraints imposed on vector models and indexing by these characteristics
Data for this category spans multiple systems, and includes both structured monitoring values and unstructured text. Indexes must support both structured field matching and vector retrieval. Real-time daily updated data must use incremental indexing mechanisms, to avoid excessive resource usage from full index rebuilding. Diverse document structures require flexible chunking strategies. Material allocation slips (short fields) and consultation minutes (long text) need tailored chunking rules for their respective formats. In real-time response scenarios, retrieval delay directly impacts emergency dispatch efficiency. Index response time must be strictly controlled.
Configuration settings
| Configuration Setting | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Ensures semantic integrity for common long-text documents such as consultation minutes and rapid disaster reports |
| Overlap Length | 100–200 characters | Prevents key information from being cut off after chunking, and maintains cross-chunk semantic connections |
| Similarity Threshold | 0.75–0.85 | Balances retrieval precision and recall, and meets key information matching needs in emergency scenarios |
| Single Search Limit | Top 8 entries | Controls the volume of returned results, and supports fast decision-making in emergency response scenarios |
| defaultToken | 4096 | Adapts to the context length after multiple documents are concatenated, and ensures complete invocation of consultation materials |
| maxToken | 8192 | Limits maximum context usage per retrieval round, and prevents resource overload |
Three common configuration mistakes
- Index parameters cannot be adjusted directly in the retrieval test panel. Changes must be made via the content management page of the target knowledge base. The system binds index debugging permissions to the knowledge base content configuration module, and no quick access entry is provided in the retrieval panel.
- The image indexing model option is not available in local deployment environments. This occurs because the multimodal extension plugin is not installed, and the feature requires commercial edition authorization components.
- Retrieval results include large numbers of outdated historical disaster documents, and do not match the current real-time scenario. This happens because incremental index updates are not enabled, and full legacy indexes are still used for retrieval.
How to confirm configurations are correct
- Upload a typical consultation minute document, and verify that the chunked text length falls within the preset chunk length range.
- Trigger a retrieval test, and confirm that the number of returned results matches the configured single search limit value.
- View the index refresh log, and confirm that real-time daily updated data has completed incremental synchronization, with no delayed errors.
Reference only; verify against the target FastGPT release and deployment documentation.
The values provided are common starting points, and should be evaluated against the applicable 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.