What the data for this category looks like
Core data for this category comes from system lists exported by evaluation tools, on-site interview records, and security device logs. Four standard document types are produced regularly: classification confirmation reports, gap analysis reports, rectification plans, and evaluation reports. Data updates follow a per-project cycle. All documents for a completed evaluation project are synchronized when the project finishes. Documents include structured control item lists, rectification requirement entries, and unstructured on-site descriptions and evaluation conclusions. No unified fixed single-document length standard exists.
What constraints these characteristics impose on knowledge base retrieval and recall
This category’s data updates follow a per-project cycle. A single update covers all documents for one project. The knowledge base must support retrieval isolated by project. This prevents mixing data across projects. Data sources include structured and unstructured content. Retrieval logic must adapt to parsing and recall for different text types. The core business process is gap checking for control items. Retrieval must accurately match cybersecurity classified protection control item entries. Recall results must cover complete rectification evidence and evaluation conclusions. Otherwise, errors may occur during the evaluation process. Data update frequency is low. High-frequency incremental synchronization is not needed. Regular full updates can maintain the knowledge base.
How to set configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the semantic matching accuracy required for classified protection control items, avoids missing key gap items, and filters irrelevant interfering content |
limit | Top 10 entries | Covers the number of standard control items within a single project, prevents result overload that reduces manual checking efficiency |
searchMode | vector | Prioritizes matching semantically related control items and rectification requirements, adapts to retrieval needs for unstructured documents |
usingReRank | Enabled | Rearranges initial recall results, improves the ranking priority of core control items and rectification evidence |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands question semantics, covers vague user inquiries about control items, such as "Level 3 access control requirements" |
collectionIds | Bind specified collections per project | Isolates knowledge base data across different projects, prevents result confusion from cross-project retrieval |
Three common mistakes
- Symptom: Knowledge base error prompts appear during retrieval. Cause: The
collectionIdsparameter is not bound. Attempts to access cross-project datasets without authorization trigger permission verification failures. - Symptom: Parsing status cannot be obtained after creating a knowledge base parsing task via API. Cause: The status synchronization logic corresponding to
datasetSearchUsingExtensionQueryis not correctly enabled. Field mappings for returning parsing in progress, ready, and failed statuses are not configured. - Symptom: Semantic similarity returns abnormal values above 10000, making it impossible to set valid filtering thresholds. Cause: The similarity value ranges of different models are confused. Filter rules are not adjusted based on the standard range of the
similarityparameter.
How to verify correct configuration
- Initiate a control item retrieval within a single project. Confirm returned results only include documents for the current project, with no cross-project data mixed in.
- Call the API to create a knowledge base parsing task. Check returned results include three status fields: parsing in progress, ready, and failed.
- Set the
similarityparameter to the baseline value. Initiate a retrieval. Confirm similarity values of returned results fall within a reasonable range. - Enable
usingReRank. After retrieval, check if result ranking prioritizes core control items and rectification evidence content.
The values provided here are common starting points. They should be evaluated against the relevant samples being used.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.