What the data for this category looks like
The road transport administration system, the national public service platform for dynamic information of road transport vehicles, and the vehicle and practitioner database provide most of the data for this category. Daily documents include business license application materials, vehicle technical files, driver qualification materials, work safety management systems, and road transport business license documents. The system updates data once every 24 hours. Document structures primarily include structured approval forms, unstructured management system texts, and associated data for dynamic vehicles and personnel. Fields cover license numbers, vehicle license plate numbers, practitioner qualification certificate numbers, safety system clauses, and similar content. There is no unified fixed unit; values vary based on document type.
What constraints these characteristics impose on the knowledge base retrieval and recall link
The scattered data sources and high-frequency update requirements for this category mean the knowledge base retrieval must support an incremental synchronization mechanism. This ensures recalled content matches the daily updated data from the road transport administration system. Mixed document types—structured approval forms, unstructured management system texts, and dynamic associated data—require retrieval to balance precise field matching and semantic understanding. This avoids returning only single, one-sided content. Vehicle and practitioner data has a strong association, so retrieval must recall relevant associated archive information. This prevents returning isolated, invalid single data entries.
Reference only; verify against the target FastGPT release and deployment documentation.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Adapt to retrieval matching accuracy for mixed structured and unstructured documents, balancing recall rate and accuracy |
limit | Top 10 entries | Cover multi-dimensional document types related to road transport business licenses, avoiding one-sided single results |
searchMode | hybrid | Combine keyword matching and semantic retrieval to adapt to mixed document structures of fields and texts |
usingReRank | Enabled | Re-rank recalled results to optimize retrieval relevance for unstructured management system texts |
datasetSearchUsingExtensionQuery | Enabled | Expand retrieval scope to cover associated vehicle and practitioner archive data |
collectionIds | Bind corresponding knowledge base collections by business domain | Isolate document data for different transport enterprises or approval departments, avoiding cross-domain interference |
Three common configuration errors
- Phenomenon: Semantic retrieval fails to locate document blocks with specified business keywords. For example, content related to "business scope change" does not appear in recalled results. Cause: The
similaritythreshold is set too high, filtering out content that meets semantic matching standards but does not exactly match target keywords. - Phenomenon: When using a strict question-and-answer template, the system prompts no answer found after retrieving an image-format document address. Switching the template allows normal content return. Cause: Only recall parsing rules for text content are configured, without adapting to the retrieval logic for image documents.
- Phenomenon: Complex ledger summary requests only return a single entry, failing to cover associated vehicle, driver, and safety system documents. Cause: The
limitparameter is set too low, not recalling enough associated documents.
How to verify correct configuration
- Run a single retrieval test with a typical business query, checking whether the document types and quantities in the recalled results meet business requirements.
- Review knowledge base synchronization logs to confirm the daily incremental update task runs normally, with no data synchronization failure error records.
- Switch between different retrieval templates, testing whether document blocks containing image addresses can be correctly recalled and parsed to validate adaptation logic for non-text content.
- Check the
collectionIdsconfiguration to confirm only knowledge base collections for the current business domain are bound, with no cross-domain documents mistakenly recalled.
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.