What Data for This Category Looks Like
Data sources include mining production scheduling systems, mineral processing workshop process parameter logs, compliance service approval archives from safety management departments, and service guideline documents from local mine supervision departments. Update rhythm: production-related parameters sync every shift, compliance service documents update immediately after approval processes complete, and daily routine inspection records are archived. Documents are divided into structured process parameter tables (with fields such as equipment number, runtime, processing capacity, mineral processing recovery rate, etc.) and unstructured service process descriptions, hidden danger rectification reports, and on-site operation guides. Most field units are physical quantities like tons, hours, and cubic meters.
What Constraints Do These Characteristics Impose on the "Workflow Orchestration" Link
Since data sources are scattered and update rhythms vary greatly, workflows must support multi-source data trigger rules configured via variables, and distinguish the pulling logic between real-time process parameters and static compliance documents. Structured parameter tables must be bound to fixed field mapping rules to avoid field confusion with unstructured documents. Service consultation scenarios involve compliance verification, so workflows must add branch judgment nodes to compare input consultation content with matching items in compliance documents. Some confidential mine service documents require permission verification nodes to limit data access scope for unauthorized users.
How to Configure the Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Variable Reference | Bind production and compliance data sources configured via variables | Enable dynamic invocation of scattered mining and mineral processing business data |
| Knowledge Base Selection | Combine service guideline knowledge base and process parameter knowledge base | Cover compliance requirements and process detail needs for service consultations |
| Single Search Limit | Top 10 results | Balance response speed and information coverage |
| Timeout Setting | 600 seconds | Adapt to pull time for large mine datasets |
nodeId Configuration | Number according to workflow node execution order | Facilitate debugging and maintenance of branch workflows |
| Query Optimization | Calibrate based on actual testing | Adapt to semantic correction for mining industry-specific terminology |
Three Common Misconfigurations
- Phenomenon: When the workflow calls knowledge base search, the knowledge base selection variable does not take effect, and irrelevant results are returned. Cause: The dynamic parameter for the knowledge base ID is not bound in the
variablesconfiguration, causing the node to read a fixed knowledge base by default. - Phenomenon: Workflow execution times out, returning a 504 status code. Cause: The timeout setting value is less than 600 seconds, which does not adapt to the pull time for large mine process data.
- Phenomenon: Audio and video markers added in the workflow cannot render properly. Cause: The rich text rendering switch is not enabled in the node configuration, and manually inserting tags only in the reply node does not take effect.
How to Confirm the Configuration Is Complete
- Initiate an API call to the workflow, pass a test mining service consultation question, and check whether the returned results include corresponding process parameters and compliance guideline content.
- View the workflow node logs, confirm that the data sources bound via
variableshave been successfully pulled, with no field missing errors. - Manually trigger the branch node of the workflow, and verify whether the compliance verification logic triggers as configured.
- Insert an audio and video test tag, enable the rich text rendering switch, then check the node preview to confirm the tag displays normally.
The values listed above are common starting points, and should be evaluated against the user’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 2026-09-28.