What the data for this category looks like
Data for this category centers on the full lifecycle of cybersecurity rating protection assessment projects. Core documents include classification determination reports, gap analysis reports, rectification plans, and assessment reports. Data sources include scan results exported from assessment tools, on-site interview records, asset system inventories, and security device operation logs. The update cycle for each project’s data follows the project timeline or annual cycles. Document fields include control item compliance status, rectification completion progress, and evidence material association identifiers. No unified standardized unitized fields are configured. Content must be matched to actual project conditions.
Constraints for Workflow Orchestration
Data for this category comes from multiple tools and records in a distributed manner, and updates alongside project timelines. Workflows must support parallel data pulling nodes. Document structures vary across different projects. Workflows must be configured with dynamic field mapping rules to meet extraction needs for documents such as classification determination reports and rectification plans. Project-level data updates follow independent logic. Workflows must bind project-specific variables to avoid conflicts with global variables. Time-consuming steps focus on material sorting and verification. Workflows must set reasonable node timeouts and failure retry strategies to ensure process efficiency.
Configuration Settings
The following configurations are based on the workflow orchestration feature of FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Create per project, including project ID, assessment level, and control item list | Data for this category updates per project, so binding project-specific variables prevents data confusion |
nodeId | Assign a unique identifier to each data pulling node | Precise tracking of processing status and execution results for data from different sources is required |
| Parallel node configuration | Launch 3 to 5 data pulling nodes simultaneously | Data sources for this category are distributed, so parallel processing reduces the duration of time-consuming steps |
| Node timeout | 600 seconds | Operations such as exporting data from assessment tools and pulling logs typically require long wait times |
| Failure retry count | 2 times | Network fluctuations or temporary data loading failures can be resolved via retries, preventing process interruptions |
| Field mapping rules | Preset mapping templates by document type | Document structures for this category are diverse, so dynamic matching supports field extraction for different reports |
Three Common Configuration Errors
- Symptom:
variablesin workflows are not bound to project-specific identifiers, leading to cross-confusion of data across multiple projects. Troubleshooting step: Check if workflow variables use global variable configurations, and whether dedicated variables are created per project. - Symptom: Multiple AI chat nodes cannot execute in parallel, causing process execution duration to exceed expectations. Troubleshooting step: Verify that parallel node configurations are correct, and confirm that node execution order is not set to serial.
- Symptom: The number of output results from the workflow query merge module does not match expectations, failing to meet control item verification needs. Troubleshooting step: Check if field mapping rules are preset by document type, and confirm that the merge logic matches extraction requirements.
How to Confirm Successful Configuration
- Verify that server environment variables
AIPROXY_API_ENDPOINT(root address of the AI Proxy service) andAIPROXY_API_TOKEN(AI Proxy administrator Token) have been configured, and that these parameters are not duplicated in the workflow. - Start a test workflow, and check node logs for correct display of project-specific
variablesparameters. - Trigger parallel node execution, confirm that multiple data pulling nodes start simultaneously with no execution order conflicts.
- Run a field mapping test, confirm that field extraction results for different document types follow preset rules.
The values provided are common starting points and should be evaluated against local deployment 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.