What Data Looks Like for This Category
Data sources include animal quarantine information, supplier batches, production traceability records, temperature collection data, metal detection results, and laboratory test reports. Daily documents include quarantine certificates, slaughter and cutting records, ingredient marinating records, thermal processing records, cold chain temperature records, and microbial test reports. Data updates per batch and per shift. Continuous temperature control data updates in real time. Document fields include batch number, quarantine number, temperature threshold, test result values, processing duration, and others. Units include degrees Celsius, kilograms, hours, colony count units, and additional relevant units.
Constraints Imposed on Workflow Orchestration by These Characteristics
Since data updates per batch and per shift, and temperature control data updates in real time, workflows must support triggering node execution per batch. This prevents cross-batch data mixing. Documents include multiple types of compliance records. Workflows must sequentially verify quarantine matching, raw and cooked zone separation records, and temperature compliance. Workflows must also distinguish field verification rules for different document types. Biological risk requirements for raw materials mean the cross-review link must first verify the quarantine qualification mark. The link must also associate batch traceability data to prevent unqualified raw materials from entering production. Multi-dimensional data associated with batches requires field mapping in workflows. This ensures batch numbers on quarantine certificates and slaughter records match, avoiding compliance issues caused by batch mismatches.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
| Trigger Condition | Match and trigger by batch number | Data for this category updates per batch, so batch numbers must bind all associated document data |
| Variable Configuration | Bind batch number, quarantine number, and temperature threshold variables | Multi-document batch consistency requires verification, and variables pass batch-related parameters |
| Node Execution Order | Verify quarantine certificates first, then production records, and finally temperature control data | Compliance processes first confirm raw material quarantine qualification, then validate processing link compliance |
| Timeout Setting | 600 seconds | Multi-document verification reads batch-associated historical data. A reasonable duration is set based on actual measurements |
| Problem Optimization Component | Place after node result verification | Basic data verification completes first, before optimizing review result expression and compliance |
| Node ID Configuration | Set a unique nodeId for each verification node | Workflows track execution status of each link to facilitate failure troubleshooting |
Three Common Configuration Mistakes
- Phenomenon: Workflow conversation logs are empty, and no return content generates after invocation. Cause: The
variablesparameter is not bound by batch number, so the workflow cannot read document data for the corresponding batch. - Phenomenon: The workflow shows a failure, but the model backend has response logs. Cause: Node execution order is configured incorrectly. The model calls before the preceding node completes data verification, so the model cannot obtain valid context.
- Phenomenon: Prompt words run repeatedly, and full prompt word loading triggers every time user input is received. Cause: Node trigger logic is not configured correctly. Incorrect
nodeIdbinding causes repeated calls to the prompt word component.
How to Verify a Successful Configuration
- Manually trigger the workflow, enter the specified batch number, and check if each node's input parameters include document fields for the corresponding batch.
- View workflow execution logs to confirm each node's
nodeIdis unique and execution order matches the preset configuration. - Simulate abnormal data input to verify if the workflow triggers corresponding verification logic and returns review results.
- View the model backend logs of FastGPT v4.17.0 to confirm the workflow's passed context includes correct category document data.
The values provided here are common starting points and should be measured against the reader's own samples.