What Data for This Category Looks Like
The primary data for this category consists of work outputs and inputs from cybersecurity level protection assessment institutions, security consulting firms, and enterprise security leaders. Daily documents include four types of structured files: classification determination reports, gap analysis reports, rectification plans, and assessment reports. Data sources include data exported from assessment tools, project interview records, system inventories, and security device logs. Data updates follow individual project cycles, with full updates occurring annually or upon completion of each assessment project. Core time-consuming steps include organizing classification determination materials, verifying control item gaps, and collecting rectification evidence. Data must strictly match the control item requirements of cybersecurity level protection standards.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
Diverse and structurally scattered data sources require multi-turn dialogue to integrate multiple data types including assessment tools, interview records, and logs. Prompts must clearly specify extraction rules for each data type. The document structure is fixed to four types of reports, so prompts must anchor to the field requirements of the corresponding report to avoid generating non-compliant formatted content. Data updates follow project cycles, so multi-turn dialogue context must be limited to a single project, and data cannot be reused across projects. Core time-consuming steps of organization and verification require multi-turn dialogue to focus on specific tasks such as control item matching and evidence collection, reducing irrelevant information retrieval.
This configuration explanation is based on FastGPT v4.17.0.
How to Configure Settings
| Configuration Item | Recommended Setting Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the typical paragraph length of classification determination reports and gap analysis reports, ensuring complete matching between control item descriptions and document content |
| Overlap Length | 100–200 characters | Prevents control item descriptions from being truncated during chunking, ensuring complete retrieval of relevant control item content during multi-turn dialogue |
| Similarity Threshold | 0.75–0.85 | Filters low-match, non-level protection related data, ensuring retrieved assessment tool and log data meet project requirements |
| Single Search Limit | Top 10 entries | Controls the volume of retrieved data, avoiding exceeding the context capacity limit of multi-turn dialogue |
| Maximum Context | 4000 tokens | Adapts to the interaction length of multi-turn dialogue for a single project, ensuring complete storage of the classification determination material organization process for a single project |
| Question Optimization | Calibrated via actual testing | Optimizes prompts to match the output format of the four report types, aligned with the structured requirements of cybersecurity level protection documents |
Three Common Misconfigurations
- No internal interaction records in the conversation details page. Cause: The session log storage configuration associated with
chatIdis not enabled, resulting in failure to persistently record multi-turn dialogue context. - Knowledge base training data processing results in empty content after local deployment. Cause: Chunk length is set beyond the actual paragraph length of the document, or the data sources associated with the
variablesparameter (system inventories, security device logs) are not correctly bound. - HTTP request calls to the knowledge base return poorly formatted content. Cause: The question optimization step is not configured, and the prompt does not explicitly require output structured content compliant with cybersecurity level protection assessment documents, resulting in retrieved information that does not match report format requirements.
How to Verify Successful Configuration
- Initiate a multi-turn dialogue targeting the fields of a classification determination report, verify that the interaction logs for the
messagesparameter are fully displayed in the details page. - Upload a system inventory document to complete training, confirm that valid chunked content is generated during the data processing stage.
- Send an HTTP request to call the dialogue interface, verify that the returned content matches the structural requirements of cybersecurity level protection assessment documents.
- Conduct multi-round testing after adjusting relevant configuration items, confirm that retrieved data sources meet the requirements of the current project.
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 2026-10-19.