This document is based on FastGPT version 4.17.0.
What this category of data looks like
Typical entities in this category include market supervision, housing and urban-rural development, ecological environment, cultural and tourism, human resources and social security regulatory departments. Daily documents include inspection plans, inspection target lists, inspection item lists, on-site inspection records, rectification notices, inspection result public notices, and law enforcement standard documents related to party building learning. Data is mainly sourced from the "Double Random, One Public Disclosure" regulatory platform, enterprise credit information public disclosure system, industry regulatory systems, law enforcement personnel directory database, and internal party building knowledge base. The update frequency is monthly. Core documents are mostly structured content, including fixed fields such as the unified social credit code of inspection targets, inspection item category, and law enforcement personnel ID number. No extra custom units are used.
What constraints do these characteristics impose on the knowledge base retrieval and recall workflow
The monthly update rhythm means the knowledge base does not require frequent synchronization. Scheduled full updates can meet business requirements. Documents are mainly structured lists, law enforcement records, and party building learning materials, with fixed fields. Retrieval must support precise matching by specified fields to filter irrelevant content. The length of individual documents varies widely, from short entries to complete law enforcement records, so chunking rules of different lengths must be supported. At the same time, party building learning content and law enforcement business content must be distinguished to avoid mixing retrieval results, ensuring content credibility and targeted relevance.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Aligns with structured field matching needs, filters low-relevance non-law enforcement or non-party building content |
limit | Top 8 entries | Covers the scope of targets and items involved in a single inspection task, avoids context overload |
searchMode | vector + keyword | Combines semantic retrieval and keyword matching, adapts to structured fields and natural language queries |
usingReRank | Enabled | Performs secondary ranking on recall results to raise the priority of highly relevant law enforcement records and party building learning materials |
datasetSearchUsingExtensionQuery | Disabled | This category of documents has a fixed structure, no need to expand query terms additionally, avoids introducing irrelevant content |
collectionIds | Bind exclusive datasets for party building learning + regulatory business | Isolates business data from other knowledge base content to ensure precise retrieval scope |
Three Common Misconfigurations
- Phenomenon: Retrieval results always return the same top few entries with no change in matching degree. Cause: The
similaritythreshold is not configured correctly, or fixed recall count is locked, and semantic matching ranking logic is not enabled. - Phenomenon: Retrieval results contain a large number of non-law enforcement general documents, and irrelevant content cannot be filtered. Cause:
collectionIdsis not specified to bind exclusive datasets, so the retrieval scope covers irrelevant knowledge base content. - Phenomenon: Structured fields such as inspection item category cannot be matched precisely, and a large number of irrelevant records are returned. Cause:
searchModeis not set to vector + keyword; using pure semantic retrieval alone cannot hit fixed field keywords.
How to Verify Proper Configuration
- Upload a single inspection item list document, enter the corresponding query term, and check whether the matching fields of the returned results match the query term.
- Adjust the
similaritythreshold to 0.7, initiate the same query again, and observe whether the number and relevance of recall results change. - Check the retrieval log to confirm that only the specified
collectionIdsdataset is bound, and no cross-dataset retrieval results appear. - Initiate a query containing a law enforcement personnel ID number, and check whether the returned results include the corresponding law enforcement record content.
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.