What the data for this category looks like
Ticket auto-classification data comes from government and state-owned enterprise hotline ticket systems. Core data includes user request text after calling the hotline, ticket number, acceptance time, transfer nodes, and pre-classification tags. Data updates occur in real time or near real time. Each ticket enters the pending queue immediately after generation. Document structures use mostly structured fields. Request text is unstructured short text, most often 50 to 500 characters long. Classification tags are fixed enumeration values. The basic statistical unit is a single ticket.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Because request text is short and highly colloquial, retrieval must balance semantic matching and keyword matching. This avoids missing key request information. The real-time data update feature requires retrieval configurations to support high-frequency synchronization. This ensures recall results match the latest ticket data. The structured classification tag field requires retrieval results to match the context associated with the tags. Simple keyword matching alone cannot guarantee classification accuracy. The single-data length range requires retrieval to adapt to short text chunking rules. This prevents semantic loss from over-chunking.
How to set up configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Matches short text semantic accuracy for ticket requests |
limit | Top 6–10 entries | Reasonable range for candidate result count to match ticket classification |
searchMode | Hybrid Search | Balances keyword and semantic matching to cover different request expression habits |
usingReRank | Enabled | Filters duplicate or low-relevance recall results to improve classification accuracy |
datasetSearchUsingExtensionQuery | Enabled | Adds context-associated information for tickets to improve matching relevance |
collectionIds | Bind exclusive hotline ticket knowledge base collection | Isolates ticket data from different business lines to avoid cross-business interference |
Three common mistakes
- Phenomenon: Retrieval fails to correctly call configured knowledge base variables. Cause: Context parameters for the corresponding variables are not bound in the retrieval configuration.
- Phenomenon: Retrieval results lag behind ticket updates. Cause: The real-time synchronization switch for the knowledge base is not enabled, or the synchronization cycle is set too long.
- Phenomenon: Table-type datasets cannot be selected in the configuration interface. Cause: The table data import permission for the knowledge base is not enabled, or the dataset format does not meet requirements.
How to confirm configurations are set correctly
- Enter the FastGPT retrieval configuration page, verify whether
collectionIdsis bound to the knowledge base collection exclusive to the target business. - Submit a test ticket, check whether the number of results returned by retrieval falls within the interval set by
limit. - Manually update the knowledge base content, wait for synchronization to complete, then confirm whether the retrieval results include the updated information.
- Adjust the
similarityparameter, verify whether the matching accuracy of retrieval results meets business expectations.
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.