What this category of data looks like
Reference only; verify against the target FastGPT release and deployment documentation.
What constraints these characteristics impose on workflow orchestration
Large disparities in policy document lengths, especially lengthy cross-regional joint policies, create context overflow risks for workflows. Text truncation length per call must be limited. Many structured fields require workflows to bind variables to store key parameters including policy document numbers and effective dates, to prevent parameter misalignment during calls. Policy updates follow no fixed cycle, so workflows must be configured with nodes that periodically sync data sources to ensure Q&A matches the latest valid policies. New energy development policies vary by region, so workflows must filter the corresponding policy dataset using incoming region parameters to narrow the recall scope.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind policy document number, region code, effective date | Match structured fields of policy data to enable precise recall |
| AI node context retention rounds | Previous 1 round | Policy Q&A mostly consists of single, precise queries; excessive context introduces irrelevant historical interference |
| Data source sync frequency | 2:00 AM daily | Most policy releases occur on workdays; daily sync covers most update scenarios |
| URL parameter transfer configuration | Pass region code parameter | Adapt to parameter passing requirements for external system calls |
| Node failure retry count | 2 times | Cover common scenarios of network fluctuations or temporary data source unavailability |
Three Common Misconfigurations
- Phenomenon: A policy summary field configured in the workflow is required to be cleared, but the old value persists after actual invocation. Cause: The target field is not bound via the
variablesconfiguration item, and modifying the variable only within a single node does not sync it to global storage. - Phenomenon: After passing the
data=1123parameter via the application link, the workflow's global variables do not load the corresponding value. Cause: URL parameter mapping configuration is not enabled, and the incoming parameter is not bound to the corresponding field invariables. - Phenomenon: When accessing with the same ID multiple times, the context retention rounds of the first AI node do not follow the configured settings, and multi-round chat history appears. Cause: Context cache is not reset for each session in the workflow, and historical chat data is reused across sessions.
How to Verify Correct Configuration
- The workflow debugging page is accessed, the region code parameter is passed, and the
variablessection is checked for correct loading of the corresponding parameter value. - Workflow execution is triggered, node logs are reviewed to confirm that context retention rounds match the configured settings.
- Data source sync is manually triggered, and node status is checked for a sync successful indication.
- Multiple calls are simulated with the same session ID, and confirmation is made that context is not reused across sessions.
Note: The configuration values listed above are common starting points. Adjust them based on specific samples and use cases for each deployment.
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.