What the data for this category looks like
Customer requirement pool management data comes from ticketing systems, customer interview records, CRM customer management systems, and product roadmap documents. The update frequency is weekly or before each version release. Daily produced documents include requirement pool lists, requirement evaluation forms, customer feedback summaries, and version planning descriptions. Fields typically include requirement source, associated customer identifier, priority score, R&D cost estimate, scheduling node, and evaluation status. There is no fixed unified standardized field format, and adaptation to original data formats from multiple sources is required. The content of this page is compatible with FastGPT v4.17.0.
What constraints these characteristics impose on the "workflow orchestration" link
Since data sources are scattered and formats are inconsistent, workflow orchestration needs to configure multiple nodes to pull raw data from different systems, then perform unified format processing. The weekly or version-level update frequency requirement means the workflow must support scheduled triggering or binding to version release event triggering. The need for associated processing of multiple documents requires the workflow to support binding fields of different documents via variables, to avoid errors caused by manual copy-pasting. The time-consuming steps of duplicate requirement merging and value evaluation require adding deduplication and score verification nodes to the workflow to reduce manual intervention workload.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Variable reference settings | Enable variables to bind requirement pool fields | Adapt to field formats of multi-source documents and enable automatic data transfer |
| Timeout threshold | 600 seconds | Cover the average time range for pulling tickets and CRM data across systems, and align with FastGPT v4.17.0 node timeout configuration |
| Node trigger condition | Trigger weekly on a schedule or before version release | Match the weekly/version-level update frequency of requirement pool data |
| Log storage duration | 30 days | Meet post-hoc traceability requirements for requirement reviews |
| Number of returned data entries | Top 10 entries | Balance data loading efficiency and requirement coverage scope |
| Number of failure retries | 2 times | Prevent workflow interruptions caused by single system fluctuations |
Three Common Mistakes
- Phenomenon: After calling the workflow via an interface, the running data in the conversation log is empty. Cause: The binding relationship of interface return fields is not configured in
variables, resulting in data not being passed to subsequent nodes. - Phenomenon: When workflow A calls workflow B, the sub-workflow cannot execute completely. Cause: The parent workflow does not specify the trigger entry of the sub-workflow via
nodeId, and does not pass the associated parameters of the requirement pool. - Phenomenon: After changing an AI conversation to variable reference mode, the temperature parameter cannot be set. Cause: The variable reference mode inherits the global configuration by default, and no separate parameter adjustment items are configured in the workflow node.
How to Confirm the Configuration is Complete
- Manually trigger the workflow once, check if the running log contains complete requirement pool field data, and confirm that cross-system data pulling works normally.
- Check the binding configuration of the variable reference node, confirm that the corresponding fields of documents such as the requirement pool list and evaluation form have been associated.
- Simulate a system timeout scenario, verify that the workflow triggers the failure retry mechanism and can complete the process normally after retries.
- View the running records of the nested sub-workflow, confirm that all execution steps of the sub-workflow have been completed.
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.