What this category of data looks like
Data sources for this category include employee contact lists, email gateways, internal training platforms, and click statistics tools. Daily generated documents include training courseware, phishing simulation plans, email templates, and simulation result reports. Data update cycles are usually quarterly or annually. Data fields include simulation crowd identifiers, email send times, click behavior records, training completion progress, and review conclusions. There are no fixed statistical units. Values adjust based on the specific scenario of each simulation.
What constraints these characteristics impose on workflow orchestration
Dispersed data sources mean workflows must be configured with cross-source data pull nodes. These nodes connect to systems such as employee contact lists and email gateways, ensuring complete acquisition of simulation crowd and click data. Low update frequency allows workflows to be set to trigger periodically, without needing to run frequently, to match quarterly or annual simulation plan cycles. Diverse document types require workflows to support multi-format file processing nodes. These nodes adapt to the upload, circulation, and archiving of training courseware, email templates, and simulation reports. Time-consuming simulation crowd screening requires workflows to include pre-set crowd grouping nodes. These reduce manual operation steps and improve configuration efficiency. The review process relies on full data aggregation, so workflows need result integration nodes. These nodes ensure complete data fields, supporting final operation report generation. Unlike security baseline checks, this category focuses on personnel security awareness and behavior. Workflows must prioritize the integration of crowd and behavior data, focusing on simulation data and results related to personnel.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Include employee ID, simulation batch number, email template path | Match core fields of simulation data, supporting crowd screening and template invocation |
| Database connection node | Configure port numbers based on actual measurements | Connect to employee contact list and training platform databases, ensuring normal data pulling |
| File upload node | Support PDF, TXT, HTML formats, maximum 1000 MB | Adapt to upload and circulation needs of training courseware and email templates |
| Tool call rate limiting | Set request interval based on actual measurements, up to 10 calls within 600 seconds | Avoid triggering the call frequency limit of the qwen3.5-plus model |
nodeId | Bind the associated ID of the email sending node and statistics node | Ensure accurate data flow links in the workflow, avoiding data misalignment |
| Workflow trigger method | Trigger periodically, execute once per quarter | Match the quarterly or annual update frequency of this category |
Three common configuration errors
- Database connection nodes cannot accept port number inputs. This occurs because the advanced configuration switch is not enabled in FastGPT v4.17.0.
- Workflows cannot upload test images during runtime. This occurs because the allowed formats and size limits of the file upload node are not configured, and the file upload function is not enabled.
- Tool call nodes frequently return 429 Request rate increased too quickly errors. This occurs because a reasonable request rate limiting configuration is not set, and the call frequency exceeds the model's limit threshold.
How to confirm the configuration is complete
- Execute a test workflow, check if the database node can pull employee contact list data normally, and confirm that fields are complete.
- Upload a test format file, confirm that the file upload node can receive and circulate files normally, with no format or size errors.
- Trigger a tool call, check if the returned results meet expectations, with no 429-type errors.
- Check that the configurations of
variablesandnodeIdmatch the actual IDs and variable names of workflow nodes, ensuring correct data flow links.
Note: The configuration values listed above are common starting points. Adjust them based on your own specific samples and operational requirements.
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.