What the Data for This Category Looks Like
Reference only; verify against the target FastGPT release and deployment documentation.
Constraints on Knowledge Base Retrieval and Recall
Multi-source heterogeneous data sources require the retrieval system to support both structured field matching and unstructured text retrieval. Daily update frequency requires incremental synchronization mechanisms to avoid performance loss from full index rebuilding. Differences in structure across document types require customized chunking rules for documents such as vehicle technical files and safety management systems. The real-time nature of business consultation requires keeping retrieval latency within a reasonable range. Retrieval scope must be strictly limited to ensure results only include data related to road transport business licenses, and prevent irrelevant content from interfering with consultation replies.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Filter low-relevance vehicle qualification and practitioner documents, and ensure recalled results match the core needs of business consultation |
limit | Top 8 entries | Control context length to adapt to the short dialogue scenario of business consultation, and avoid exceeding model context limits |
searchMode | hybrid | Adapt to structured fields such as license numbers and vehicle identification numbers, as well as unstructured safety system documents, and balance precise matching and semantic retrieval |
usingReRank | Enabled | Re-rank initial recall results, and prioritize documents directly related to business license approval |
datasetSearchUsingExtensionQuery | Enabled | Expand keywords for consultation questions, such as expanding "renewal" to "business license renewal", to cover more business scenarios |
collectionIds | Knowledge base collection ID corresponding to the road transport business license business | Limit retrieval scope, avoid interference from irrelevant data, and ensure results comply with business compliance requirements |
Three Common Misconfigurations
- Phenomenon: An empty array is returned after calling the knowledge base binding interface. Cause: The
collectionIdsparameter is not configured correctly, and the dedicated knowledge base collection for road transport business licenses is not bound. - Phenomenon: Retrieval latency exceeds 30 seconds. Cause: Daily incremental synchronization is not configured, and the full index data volume is too large, exceeding the retrieval response threshold.
- Phenomenon: Recalled results include enterprise qualification documents unrelated to the current consultation. Cause: The
similaritythreshold is set below 0.7, and low-match irrelevant data is not filtered.
How to Verify Proper Configuration
- Call the FastGPT knowledge base binding interface, and check whether the
collectionIdsin the returned configuration parameters include the collection identifier of the business-specific knowledge base. - Submit a test consultation query such as "What materials are required for road transport business license application", and confirm that the retrieval results include business documents such as license application materials and vehicle technical files.
- View retrieval logs to confirm that the initial number of recalled entries matches the
limitconfiguration, and that the result ranking afterusingReRankaligns with business priority. - Trigger a manual incremental synchronization task, and check whether the index update time matches the daily update time of the road transport administration system.
The configuration values listed above are common starting points. They should be evaluated against specific samples and use cases for the target deployment environment.
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.