What this category of data looks like
This category of data comes from government portals, document management systems, government information disclosure directories, policy document repositories, and press conference materials. The update frequency is daily. Daily documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. Fields cover document disclosure attribute, confidentiality level, release time limit, associated columns, audience scope, and more. Government offices, policy and legal affairs departments, and website operation and maintenance teams handle maintenance.
What constraints these characteristics impose on the knowledge base retrieval and recall link
High-frequency daily updates of government documents require the retrieval and recall pipeline to adapt to incremental synchronization mechanisms, to avoid index lag affecting timeliness. Documents include fields such as disclosure attribute and confidentiality level. This requires automatic filtering of confidential or restricted content before retrieval, to prevent accidental disclosure of confidential or sensitive information, and only recall entries that meet proactive disclosure requirements. The associated structure binding policy documents and interpretation drafts requires automatic association and matching of associated documents during retrieval, to avoid misinterpretation of policy stances from single content. The proactive release attribute for the public requires recall results to be sorted by release time limit, prioritizing the latest content. It also requires matching the classification rules of the public disclosure directory, to ensure results are consistent with corresponding columns.
Configuration guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Meets the rigor requirements for government content, avoids low-relevance results leading to policy misinterpretation, while covering core policy keywords |
limit | Top 10 entries | Aligns with public information acquisition habits for consultation, avoids excessive results interfering with judgment, while covering multi-dimensional policy-related content |
searchMode | hybrid | Combines keyword matching and semantic retrieval, adapts to structured content in policy documents and natural language expressions in interpretation drafts |
usingReRank | Enabled | Addresses the long-text characteristics of government documents. The reranking model optimizes result sorting accuracy, resolving relevance bias in initial recall |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands synonyms and abbreviations related to policies, adapts to colloquial expressions in public consultations, such as "social security" corresponding to "social insurance" |
collectionIds | Configure dedicated collections classified by public disclosure directory | Ensures the retrieval scope only covers proactive disclosure content from corresponding columns, preventing irrelevant information from other columns from being included |
Three common configuration errors
- Phenomenon: After enabling the
usingReRankreranking function in the knowledge base, the corresponding interface switch displays an abnormal mark, and normal reranking triggering fails. Cause: The permission binding for the reranking model has not been completed, or theusingReRankparameter is not correctly enabled in the configuration, causing the reranking pipeline to not be loaded. - Phenomenon: After migrating the image, knowledge base retrieval results and interface configuration are displayed in a non-target language. Cause: The language identification field of the original data source was not retained during migration, causing the system to call the default non-target language model instead of matching the native language of the government data source.
- Phenomenon: When calling the knowledge base, a prompt indicating insufficient reference quota is returned, or retrieval results cannot be filtered by custom tags. Cause: The
limitparameter value has not been adjusted to adapt to concurrent call scenarios, or documents have not been correctly associated with preset classification tags, resulting in the retrieval scope not being limited per business rules.
How to confirm the configuration is complete
- Enter the knowledge base configuration page, check the
usingReRankswitch status, confirm it is enabled and the configuration has been saved. Initiate a retrieval test and check if the result sorting conforms to the reranking logic. - View the retrieval log, confirm that the matching results of the
similarityparameter are within the preset range, with no excessively low or high matching values. - Initiate a retrieval request with a public disclosure directory tag, confirm that only documents bound to the corresponding category are returned, verifying that the
collectionIdsconfiguration is effective. - Upload a test document updated on the current day, initiate a retrieval to confirm that the new content has been recalled, verifying that the daily incremental synchronization pipeline is working properly.
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.