What Data for This Category Includes
Daily documents for precast concrete components include component detailed drawings, steel bar cutting lists, mold inspection records, pouring and vibration records, curing records, and demolding and factory inspection reports. Data sources include BIM or detailed design documents, steel bar and concrete batch ledgers, mold table and curing kiln operation data, laboratory test records, and product QR code traceability systems. Data updates are completed synchronously with individual components, each batch of materials, and each curing batch in the kiln. Core fields include component model, steel bar specification, pouring strength, curing duration, and demolding inspection results. Unlike categories that deliver fluid materials by truck, this category requires matching individual large component parameters for on-site lifting positions.
What Constraints These Characteristics Impose on Workflow Orchestration
The multi-source heterogeneous documents and high-frequency update characteristics of this category require workflows to support automatic parsing of multi-format documents and batch association. The exclusive parameters of individual components require workflow nodes to bind the corresponding QR code traceability ID, to avoid parameter confusion between different batches of components. The high-frequency updated curing and inspection data require the workflow's node trigger logic to support real-time synchronization of the latest ledgers. The accuracy requirements for core verification fields such as embedded position and strength require a pre-verification node to be set in the workflow, to intercept non-compliant parameters before entering the subsequent inspection and maintenance Q&A link. At the same time, because components need to match on-site lifting positions, the workflow must retain the association field between components and installation positions, to facilitate subsequent Q&A to accurately match the corresponding scenarios.
How to Configure Settings
This document is written based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
| Variable Configuration | Bind component ID, batch number, and curing strength fields in variables | Match the individual traceability and core parameter verification requirements of precast concrete components |
| Trigger Timing Configuration | Trigger upon completion of demolding inspection and at the end of each kiln curing cycle | Match the high-frequency update rhythm of this category by batch and kiln |
| Timeout Threshold | 600 seconds | Adapt to the time consumption requirements of multi-source document parsing and parameter verification |
| Code Run Timeout | 300 seconds | Adapt to the time consumption requirements of code parsing multiple component documents |
| Maximum Number of Parsed Documents per Single Run | 5 | Adapt to the range of supporting document quantities for a single batch of components |
| Context Call Limit | Top 8 entries | Match the range of associated data volume for a single batch of components |
| Core Node ID | Bind nodeId as the core inspection and maintenance Q&A node | Facilitate workflow debugging and log positioning |
Three Common Errors
- Symptom: The console.log logs from the code run node do not appear in the inspection console. Cause: The workflow's debug log switch is not enabled, or the node is not configured to allow output of operation logs.
- Symptom: The code run node throws an execution error. Cause: Required fields such as component ID and batch number are not bound in
variables, resulting in missing parameters for code calls. - Symptom: The AI model dropdown list is empty. Cause: The access key for the corresponding large model is not configured in the platform backend, or the workflow call permission for this model is not enabled.
How to Confirm Configuration Is Correct
- Manually trigger the workflow, pass test component batch data, and check whether the bound fields in
variablesload correctly. - Run the code run node, check whether the preset operation logs are output in the console, and confirm that the logs can be displayed normally.
- Enter the workflow configuration page, check whether the AI model dropdown list loads available large model options.
- Trigger a simulated curing record update, and confirm whether the workflow starts automatically according to the preset timing.
The provided values are common starting points and should be evaluated against the relevant samples of the deployment.