What the Data for This Category Looks Like
Livestock and poultry farming business data primarily comes from daily records and monitoring equipment on the farm side. This includes inventory and slaughter ledgers, feed consumption logs, indoor temperature and humidity environmental control data, disease monitoring reports, and marketing outreach records targeting farmers. Data sources cover Excel files of breeding ledgers, real-time reports from environmental control sensors, and epidemic prevention information submitted via farmer-facing mini-programs.
Update frequencies vary widely: environmental control data updates every second, inventory ledgers update daily, and disease reports are submitted immediately. Document structure falls into two categories: structured tables, and unstructured videos and documents. Fields include inventory volume (unit: head/ bird), feed conversion ratio (unit: kg/kg), house temperature (unit: degrees Celsius), and some fields require tailored adaptation based on breeding category.
Constraints Imposed on Workflow Orchestration by These Data Characteristics
The data characteristics of livestock and poultry farming impose multiple constraints on workflow orchestration. Real-time updated environmental control and disease data requires workflows to support event triggering, and to bind file upload or data reporting events. The multi-field structured ledgers and differentiated needs for specific categories require workflows to support bulk input of multiple parameters and conditional branch configuration. Unstructured epidemic prevention videos and breeding log files require workflows to integrate file parsing nodes to complete text extraction and field mapping. At the same time, marketing content targeting farmers must match their breeding category and current breeding stage, requiring workflows to add conditional judgments for category and stage during the content generation phase.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
workflow_trigger_mode | Select "event trigger", bind "file upload" + "data reporting" events | Matches the need for real-time updates of livestock and poultry farming data and immediate adjustments to marketing content |
UPLOAD_FILE_MAX_SIZE | 500 MB | Adapts to the typical size of files such as breeding ledger Excel sheets and epidemic prevention videos |
global_var_persistence | Session-level persistence | Prevents breeding data from being lost across multiple conversation rounds |
llm_temperature | 0.3–0.5 | Ensures professionalism and accuracy of marketing content, avoids excessive divergence |
workflow_node_timeout | 120 seconds | Adapts to the typical time required for breeding data parsing and content generation |
file_parse_chunk_size | 800–1200 characters | Adapts to the field length of breeding documents, avoids overly fragmented or overly long splits |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: When configuring a workflow as a tool call, files uploaded via simple tasks cannot pass their links into workflow parameters. Cause: The "file link" type input field is not configured in the workflow's input node, and only text parameters are accepted.
- Symptom: When global variables are passed between nodes, modified values appear empty in the next node. Cause: Session-level persistence configuration for global variables is not enabled. The variable only takes effect in the current node and is not synchronized to subsequent nodes.
- Symptom: When selecting a variable reference method to specify a large model in the AI conversation component, the temperature parameter setting entry cannot be found. Cause: The temperature parameter is not configured separately in the workflow's large model node. The component-level variable reference is mistakenly confused with large model parameter configuration.
How to Verify Proper Configuration
- Upload a breeding ledger Excel file, verify whether the workflow can automatically parse and extract fields such as inventory volume and feed consumption as parameters passed to subsequent nodes.
- Manually modify the test value of the global variable, trigger workflow execution, and check whether the variable can be read normally in all subsequent nodes.
- Configure an AI conversation node, check whether the temperature parameter setting item can be called normally, adjust it, and verify whether the style of the generated marketing content meets expectations.
- Upload a breeding video file exceeding the conventional size, verify whether the system triggers a file size limit prompt or completes parsing normally.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.