What this category of data looks like
Data for this category primarily comes from highway maintenance management systems, bridge and tunnel monitoring systems, road administration patrol systems, and traffic flow monitoring data. The update frequency is daily. Daily documents include maintenance plans, patrol logs, disease disposal orders, road-related construction permits, and road property damage compensation forms. Structured documents contain fields such as road section numbers, maintenance cycles, and permit document numbers. Unstructured documents include on-site disease photos and patrol description text. Some documents are linked to road property asset numbers and maintenance responsibility subjects.
What constraints these characteristics impose on knowledge base retrieval and recall
Daily updated road property maintenance data is stored alongside Party Building materials. This requires the knowledge base retrieval and recall process to support high-frequency incremental synchronization, to avoid resource consumption from full re-scanning. Multiple document types have differing fields. For example, precise matching of permit document numbers for road-related construction permits, and semantic disease descriptions in patrol logs. This requires configuring differentiated retrieval weights for different fields, to prevent semantic matching deviations. The uniqueness of road property asset numbers and road section numbers requires retrieval results to link to corresponding road property information, to prevent incorrect cross-section matching and ensure the accuracy of business cases in Party Building learning. At the same time, mixed retrieval of business documents and Party Building content requires balancing the recall priority of the two content types, to avoid overloading business information in Party Building learning scenarios.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Similarity threshold | 0.75–0.85 | Adapts to mixed semantic matching of Party Building materials and business documents, balances recall accuracy and coverage |
| Single recall limit | Top 8 entries | Controls context length, ensures information density and coherence for Party Building Q&A |
| Search mode | Hybrid retrieval | Balances precise keyword matching and semantic recall, adapts to mixed retrieval needs of structured fields and unstructured text |
| Reranking switch | Enabled | Reranks initial recall results to highlight core business documents and Party Building materials required for Party Building learning |
| Query expansion | Enabled | Automatically expands Party Building-related query terms, covers associated retrieval scenarios for Party Building materials and business documents |
| Specified knowledge base collection | Corresponding road property maintenance and Party Building knowledge base ID | Limits retrieval scope, excludes irrelevant knowledge base content, ensures scenario relevance for Party Building learning Q&A. If managing more than 30 knowledge bases, use collection grouping to categorize, avoid exceeding the single-instance knowledge base quantity limit |
Three common errors
- Phenomenon: Retrieval results include content from non-specified knowledge bases, which does not match the Party Building learning scenario. Cause: The specified knowledge base collection parameter is not correctly configured, and the retrieval target scope is not limited, leading to recall of irrelevant data across knowledge bases.
- Phenomenon: Some documents remain after performing a full deletion operation on the specified knowledge base. Cause: The official full clearing interface is not used, only single document deletion operations are performed, or the asynchronous synchronization task is not waited to complete.
- Phenomenon: Abnormal results are returned when nested searching knowledge base collections, and target documents cannot be hit. Cause: The hierarchical relationship of nested searches is not correctly configured, or the collection ID is filled incorrectly, and the corresponding relationship between the parent collection and child collections is not associated.
How to confirm the configuration is complete
- Manually enter a test query that includes road section numbers and Party Building-related keywords, verify that retrieval results only include documents from the specified knowledge base.
- Call the full clearing interface, then retrieve the original knowledge base content again, confirm that no residual entries exist.
- After configuring the nested search collection, enter a query that includes child collection keywords, verify that documents within the child collection can be hit.
- View the system retrieval log, confirm that the values of parameters such as similarity threshold and reranking switch match the configured values, with no abnormal overwrites.
The values provided 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.