What Data for This Category Looks Like
Data sources for this category include customer color swatches, formula libraries, dye chemical batch records, dye vat operation data, colorimeter test results, setting machine parameters, and environmental monitoring logs. Data is generated per vat, per batch, or per shift. Daily documents include dyeing formulas, chemical mixing records, dye vat temperature curves, sample confirmation sheets, color difference reports, setting process sheets, and sewage discharge logs. Data fields include dye vat number, chemical batch number, color difference ΔE value, setting machine speed, and others. Units include degrees Celsius, kilograms, seconds, ppm, and others.
Constraints Imposed by These Characteristics on Workflow Orchestration
This category has high data update frequency and strong batch association, so workflows must support single-vat and single-batch triggers using real-time mode. Data types are diverse, including text formulas, temperature curves, and numerical test results, so workflow nodes must support multi-source data parsing and merging. Quality errors have severe consequences, so workflows must be configured with exception branch processing logic, such as triggering a re-inspection process when color difference exceeds standards. The characteristics of wet chemical batch processing require workflows to bind batch IDs as core associated variables, ensuring the accuracy and consistency of traceability data and avoiding cross-batch data confusion.
This configuration is based on FastGPT v4.17.0.
How to Set the Configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Mode | Trigger by batch ID | Matches the feature of this category managing production data by vat and batch, ensuring accurate association of traceability data for each batch |
| Knowledge Base Association Scope | Bind the formula library and dye chemical logs associated with the current order | Narrow the retrieval scope to avoid interference from irrelevant historical data |
| Single Search Limit | Top 3 entries | Matches the precision requirements of dyeing and finishing process parameters, reducing interference from redundant results |
variables | Calibrate based on actual measurements (field length 1000-1200 characters) | Adapt to differences in batch field naming and units across dyeing mills |
| Timeout Threshold | 600 seconds | Covers the typical time required for dye vat curve parsing and multi-source data merging |
Three Common Mistakes
- Phenomenon: No knowledge base search result option appears in the variable selection panel of the code running node. Reason: The output result of the knowledge base node is not bound to the global
variables, so this type of data is not included in the variable pool. - Phenomenon: Too many problem category configurations in the workflow cause user questions to fail to match the corresponding knowledge base entries. Reason: The categories are not simplified based on typical dyeing and finishing quality problem types such as color difference, color streaking, and hand feel abnormality, and a large number of redundant categories are added.
- Phenomenon: Parameter error is returned when calling the API to create a workflow. Reason: The correct
nodeIdparameter is not passed according to the FastGPT API documentation, so the node configuration cannot be recognized.
How to Confirm the Configuration Is Complete
- View the workflow trigger log to confirm that each batch of production data can be correctly associated with the preset knowledge base scope.
- Submit a simulated quality problem query and verify that the number of returned results meets the configured single search limit requirement.
- Check the
variablespanel to confirm that all required batch fields and test data fields have been included. - Run a complete workflow once to confirm that there are no timeout errors or missing parameter prompts.
The values provided are common starting points and should be validated against local deployment samples.