What the Data for This Category Looks Like
The data related to equipment inspection and maintenance Q&A for furniture and wood products manufacturing mainly comes from order design systems, sheet and wood batch ledgers, CNC cutting and drilling equipment logs, ERP/MES systems, and board moisture content testing equipment. Data updates align with business node timelines: update the order breakdown drawing and cutting list every time an order is generated, sync equipment operation logs and coating process parameters daily, and update batch information and test records when each batch of raw materials is placed into storage. Daily business documents include order breakdown drawings, cutting lists, edge banding and drilling processing programs, coating process cards, hardware matching lists, trial assembly and packaging records. Document fields include board size (millimeters), processing sequence number, board batch number, coating thickness (microns), hardware model, and other details. All data types must be associated by order dimension.
What Constraints Do These Data Characteristics Impose on Workflow Orchestration
These data characteristics impose clear constraints on workflow orchestration. First, multi-type documents associated by order dimension require the workflow to pass the order ID as a grouping identifier via variables to prevent cross-order data confusion. Second, differences in update frequencies across data sources require configuring trigger conditions for workflow nodes, to separate real-time equipment log calls and bulk order document processing. Third, field differences across multiple business document types require configuring different parsing nodes in the workflow, to adapt to size parameters in order breakdown drawings, operation duration in equipment logs, and other distinct fields. Fourth, the custom order-driven production model requires the workflow to support dynamically passing personalized parameters. Fixed parameter templates are not suitable for this use case.
How to Configure Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Define global variables by order ID and board batch number, with values `Order ID: string, Board Batch Number: string | Adapts to the variable management rules of FastGPT v4.17.0, matches the business data association requirement of grouping by order, and avoids data confusion |
nodeId | Bind equipment inspection nodes with corresponding process nodes, with values `Equipment Log Node ID + Process Sequence Number | Accurately associates equipment operation data with production processes, matches the order-based association rules of business data |
| Trigger Condition | Trigger by order generation time, with values Batch process the previous day’s equipment logs at 0:00 daily, trigger inspection requests for new orders in real time | Matches the update rhythms of different data sources, distinguishes real-time and batch processing, and adapts to the update frequency of business nodes |
| Context Window | 8000–12000 token | Adapts to the content length of multiple types of business documents, avoids context overflow, and fits the multi-document scenario of furniture and wood products manufacturing |
| Node Timeout | 600 seconds | Adapts to the parsing and retrieval duration of large-scale cutting equipment logs, and avoids timeout interrupts |
| Single Retrieval Limit | Top 20 entries | Fits scenarios with a large number of board parts, avoids excessive data occupying context, and improves retrieval efficiency |
Three Common Configuration Mistakes
- Issue: A
localStorage is not definederror occurs when running custom code in a workflow. Cause: The workflow runtime does not support the browser-side localStorage object. Use FastGPT's built-invariablesto store temporary data. - Issue: Only a single language is displayed when configuring multilingual opening prompts in the workflow. Cause: No language identification parameter is passed in
variables, so the opening prompt cannot be dynamically switched based on requests. - Issue: No thought process content is returned after initiating a workflow request via API. Cause: The thought process output configuration is not enabled in the workflow node, or the return type is not specified in the API request parameters.
How to Confirm the Configuration is Correct
- Initiate a workflow request for a test order, check whether the order ID passed in
variablesis correctly associated with the corresponding order breakdown drawing and equipment log data. - Run the workflow node, verify that the custom code module can correctly read the temporary data in
variableswithout error messages. - Call the API to initiate a workflow request, check whether the returned results include the expected equipment inspection and maintenance Q&A content, as well as the configured thought process output.
- View the workflow operation logs, confirm that the node timeout setting conforms to the actual business scenario, and no frequent timeout interrupts occur.
The values provided are common starting points and should be measured against the reader's own samples.