What data does this category include?
Data for this category originates from meteorological warning systems, hydrological monitoring systems, emergency command platforms, grassroots disaster reporting systems, and video surveillance. The update frequency is daily. Daily documents include duty records, warning notices, consultation minutes, rapid disaster reports, emergency response plans, and material allocation slips. Some documents include fields such as rainfall and water level values, risk avoidance areas, material categories, and quantities. Document formats and field specifications differ across sources.
What constraints do these characteristics impose on the vector model and indexing workflow?
Multi-source, heterogeneous data formats and field differences require preprocessing to complete unified field mapping and format standardization. This prevents field mismatch issues during indexing. Daily updated data volume requires the incremental indexing trigger mechanism to align with batch synchronization rhythms. This reduces server resources used by full indexing. Document lengths vary widely, from short warning notices to lengthy consultation minutes. Flexible chunking rules are needed to match content length and avoid semantic breaks. Low latency requirements in emergency scenarios also apply. The index recall link must be optimized to cut retrieval latency and ensure fast response times.
How to set configuration parameters
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxToken | 8000–12000 token | Matches the length of most consultation minutes and policy documents. Prevents truncation of critical policy basis content |
| Chunk Length | 800–1200 characters | Balances content integrity for short warning notices and long response plans. Reduces semantic breaks after chunking |
| Overlap Length | 100–150 characters | Ensures semantic continuity between adjacent chunks. Prevents policy clauses from being split across chunks |
| Single Search Limit | Top 10 results | Emergency scenarios require fast access to core policy basis. Too many results increase subsequent processing time |
| Reranking Model | Calibrated via actual testing | Reranking effects vary widely across scenarios. Adaptability must be verified using locally deployed models |
| Maximum Context Window | 4000–6000 token | Ensures complete retrieval of relevant policy articles and historical consultation records during Q&A |
Three common configuration errors
- Phenomenon: The set chunk length exceeds the single-record upper limit of index storage. The interface shows the error "Chunk too long to index". Cause: The chunk parameters were not adjusted to match the length span of documents in this category. Generic scenario configuration values were used directly.
- Phenomenon: A PostgreSQL-related dependency error occurs when deploying the vector database. The service fails to start normally. Cause: A compose file with extra database dependencies was used incorrectly. The lightweight indexing deployment requirements of this scenario were not met.
- Phenomenon: The retrieved policy basis has low matching accuracy with user questions. Corresponding regulatory clauses cannot be matched accurately. Cause: The reranking model was not enabled. Only basic recall results were used. No further filtering was performed for semantic similarity of policy text.
How to confirm configuration is properly set
- Upload the longest single consultation minute and shortest single warning notice. Verify content integrity and semantic continuity after chunking. Confirm chunk parameters match the document length span.
- Trigger an incremental indexing task. Check the indexing update logs for FastGPT v4.17.0. Confirm daily updated disaster data has been successfully synchronized to the index database.
- Input a typical policy Q&A question. Cross-check the number and relevance of retrieved results. Confirm the single search limit and reranking configuration meet business requirements.
- Test the truncation effect of the
maxTokenparameter. Confirm policy articles are not accidentally truncated. Complete regulatory basis content is retained.
The values given are common starting points and should be evaluated using locally collected test data.
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.