What data for this category looks like
This category of data comes from government portals, document management systems, government information disclosure directories, policy document repositories, and press conference materials, with a daily update frequency. Daily documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. Most documents contain fields such as document number, issuing authority, release time, public disclosure attribute, and secrecy level, with structured formats and strong correlations between different documents.
What constraints these characteristics impose on knowledge base retrieval and recall
The daily updated data requires the retrieval and recall link to support high-frequency incremental synchronization, to avoid delayed release of public information affecting timeliness. Multi-type associated documents require matching cross-document field association logic, to ensure that policy documents and their corresponding interpretation drafts can be linked during retrieval and maintain consistent messaging. Public disclosure attribute and secrecy level fields require pre-filtering of retrieval results, to prevent sensitive or undisclosed content from being exposed. Format differences across different documents require unified chunking rules, to ensure semantic consistency during retrieval. The positioning of releasing content to the public requires retrieval results to comply with public disclosure standards, to avoid unauthorized content appearing.
How to configure the settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Filters low-relevance results, prevents undisclosed or irrelevant content from being included in retrieval results, and adapts to the strict requirements of government affairs content |
limit | Top 8 entries | Controls the number of documents recalled per single retrieval, balances context length and information coverage, and adapts to the length characteristics of policy-related documents |
searchMode | semantic | Prioritizes semantic matching, ensuring accurate associated retrieval between policy interpretations and their original documents |
usingReRank | Enabled | Performs secondary ranking on initial recall results, improving the ranking priority of highly relevant policy documents and interpretation drafts |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands retrieval queries to cover fields such as policy document numbers and issuing authorities, improving recall rates for cross-document retrieval |
collectionIds | Fill in according to the actually bound government affairs public datasets | Limits the retrieval scope to only datasets related to proactive public disclosure, preventing irrelevant data from interfering with retrieval results |
Three common configuration errors
- Undisclosed confidential documents appear in retrieval results: The phenomenon is that returned results include files marked "internal" or "confidential". The cause is failing to limit the retrieval scope via
collectionIds, or setting thesimilaritythreshold too low, resulting in undisclosed content being recalled. - The AI response does not reference retrieved policy content and directly generates generic replies: The phenomenon is that the AI’s dialogue response does not cite retrieved policy content and instead produces generic responses. The cause is that the knowledge base node configuration in the workflow was not synchronized to the dialogue chain, or
datasetSearchUsingExtensionQuerywas not correctly bound to the corresponding dataset. - The number of retrieved entries is less than the configured
limit: The phenomenon is that thelimitis set to 8 entries but only 3 are returned. The cause is insufficient valid documents for initial recall, orusingReRankfiltered some low-relevance results, resulting in the final displayed number of entries not meeting expectations.
How to confirm the configuration is correct
- Navigate to the FastGPT dataset management page, verify that the bound datasets only include proactive public disclosure-related documents such as policy documents and public disclosure directories.
- Debug the knowledge base retrieval node, input a test query such as "Government public information release requirements", check whether the
similarityvalues of the returned results fall within the 0.72–0.80 range. - Trigger an incremental synchronization task, check the system logs to confirm that newly added policy interpretation drafts and website column update records from the current day have been indexed.
- Run the complete workflow, verify that the AI output references the retrieved public document content and contains no unauthorized sensitive information.
The values provided here 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.