What This Category of Data Looks Like
Consultation and reply data for government and enterprise informatization services mainly comes from official service guides, communication service tariff policies, window FAQ libraries, and troubleshooting manuals. Data update cadence adjusts with policy changes: tariff-related content is updated monthly, service guides are updated quarterly, and window FAQs are supplemented in real time. Documents include structured fields (item ID, processing channel, effective date) and unstructured text. Some documents contain nested processing step descriptions. Common units used are workdays and contact phone numbers.
Constraints Imposed on Knowledge Base Retrieval and Recall
The high proportion of structured fields requires the retrieval process to support filtering by fields such as item ID and effective date, to exclude expired or irrelevant entries. Different update cadences across data sources require support for incremental index updates, to avoid resource usage and delays caused by full index reconstruction. Documents with nested processing steps require retaining contextual connections during chunking, to prevent logical breaks after step splitting. Real-time supplemented window FAQs require shortening index synchronization cycles to ensure the timeliness of consultation content.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Government and enterprise service consultation has high semantic matching accuracy requirements; this range filters out low-relevance policy or tariff content |
limit | Return top 8 entries | Valid results for service consultation typically appear in the first few entries; 8 entries covers most users' complete consultation needs |
searchMode | hybrid | Combines semantic and keyword matching, adapting to mixed retrieval needs of structured fields and unstructured text |
usingReRank | Enabled | For redundant results after long document chunking, re-ranking improves the semantic relevance of top results |
datasetSearchUsingExtensionQuery | Enabled | Can supplement and expand user consultation phrasing, adapting to colloquial questions from government and enterprise users |
collectionIds | Specify according to knowledge base collections of the corresponding business domain | Prevents irrelevant cross-business domain data from being included, ensuring retrieval results only target the current service consultation scenario |
Three Common Misconfigurations
- Phenomenon: The order of custom-chunked document blocks does not match the order stored in the index. Cause: The system's default deduplication logic deletes duplicate document blocks, destroying the custom chunking sequence.
- Phenomenon: After deploying FastGPT from source code and connecting to a Docker database, knowledge base content does not display synchronously. Cause: The latest database connection configuration is not loaded, or the scheduled task for database incremental synchronization is not enabled.
- Phenomenon: Retrieval results include entries with semantic similarity below the set value or full-text search score below the set threshold. Cause: Filtering parameters such as
similarityare not configured correctly, or the re-ranking function for filtering low-relevance results is not enabled.
How to Verify Configuration Correctness
- Submit a typical service consultation query, check if the relevance of returned results meets business expectations, and adjust relevant parameters to appropriate ranges.
- View the knowledge base index update logs, confirm that incremental update tasks run according to the set cycle with no failed records.
- Test retrieval requests that include structured fields, confirm results only contain content from the corresponding business domain, and verify that the business domain filtering configuration takes effect.
- Submit repeated test queries, confirm that the order of retrieval results meets business requirements, and verify the effect of deduplication and re-ranking configurations.
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.