What data for this category looks like
Data for this category primarily comes from object storage, data warehouses, annotation platforms, and customer acceptance feedback. Updates are triggered per batch of datasets or each version. Daily deliverable documents include dataset descriptions, version records, delivery checklists, and acceptance reports. Fields typically cover dataset identifiers, version numbers, sample details, delivery scope, and acceptance conclusions. Core measurement units are file size, sample count, and version iteration cycle. This supports daily work for data project managers, data engineers, and customer algorithm teams.
What constraints these characteristics impose on workflow orchestration
The scattered nature of data sources requires workflow configurations to unify multi-source data pulling rules, avoiding cross-system data format conflicts. The multi-version iteration update rhythm requires workflows to retain version traceability nodes, ensuring each batch of delivered data can be linked to corresponding version records. The fixed document structure requires workflows to automatically generate standardized fields, reducing format deviations from manual entry. Time-consuming steps such as sample difference explanation and delivery integrity verification need embedded automatic verification logic in workflows, lowering the probability of manual errors and preventing issues like non-reproducible training results or customer acceptance failures.
How to configure settings
This page applies to FastGPT v4.17.0. Below are core configuration items for workflow orchestration:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | {"auto_version": true, "max_delivery_mb": 1000 MB, "check_timeout": 300 seconds} | Adapts to automated version iteration requirements, matches the conventional capacity limit for single-batch delivery packages, and covers reasonable time for single-batch verification |
nodeId | "data_source_pull" | Binds the pull node for object storage and data warehouses, unifies the call identifier for multi-source data |
| Automatic verification trigger timing | After delivery package generation | Completes integrity verification before delivery, preventing non-compliant delivery packages from entering subsequent stages |
| Verification timeout threshold | 600 seconds | Covers reasonable time for multi-source data pulling and verification, preventing verification interruptions caused by data volume fluctuations |
| Version record synchronization configuration | Binds the acceptance report writing node | Ensures version numbers and delivery data are updated synchronously, enabling full-link traceability |
Three common mistakes
- Phenomenon: Workflow return results include knowledge base search input and response fields. Cause: No parameters to disable knowledge base reference were configured in
variables, and the search reference logic is enabled by default. - Phenomenon: Recognition accuracy of the question classification node in the workflow is low, and prompt matching effects do not meet expectations. Cause: Prompt rules for model calls were not adjusted based on the professional domain of dataset samples, leading to blurred classification boundaries.
- Phenomenon: Workflows cannot properly call external MCP plugins, and the interface returns a call failure prompt. Cause: Authorization binding for external plugins was not completed in workflow node configurations, and plugin call parameters were not correctly set.
How to confirm proper configuration
- Trigger the workflow manually, then check if returned results include expected dataset delivery fields and version records, and confirm that parameters configured in
variablestake effect. - View workflow node logs, confirm that the multi-source data pull
nodeIdbinding is correct, and that data pulling has no format conflicts. - Simulate an exception scenario, such as a delivery package exceeding the configured capacity limit, confirm that the workflow triggers the preset verification failure logic.
- Cross-check version record documents, confirm that the automatically generated version number after workflow completion matches the configured rules.
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.