What Data for This Category Looks Like
Livestock and poultry farming profit margin data is primarily sourced from Ministry of Agriculture and Rural Affairs livestock monitoring systems, local livestock industry public APIs, and third-party market aggregation services. Data updates follow a daily schedule: full data for the previous natural day is completed in the early morning each day. A single return covers national multi-category breeding market trends. Main document formats are JSON or CSV. Core fields include breeding variety code, average slaughter weight (unit: kilogram), unit feed cost (unit: yuan/kilogram), breeding cycle days, net profit per head or bird (unit: yuan), and start and end dates of the statistical cycle.
Constraints Imposed on HTTP Interfaces and External Systems
These data characteristics impose three core constraints on HTTP interface and external system configuration. First, data updates once daily. API call intervals must match the update cycle to avoid triggering third-party interface rate limits. Second, fields include multi-category identifiers and unit information. Filter parameters by variety and date must be configured, and unit conversion logic for different categories must be supported. Third, some regional monitoring data may have missing fields. Empty field handling rules must be configured to prevent workflow execution interruptions. Additionally, data return volume expands as covered categories increase. Request timeout and response parsing mode must be configured appropriately.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
request_interval | 86400 seconds | Matches the daily update rhythm of livestock and poultry farming profit margin data to avoid triggering third-party interface restrictions via frequent calls |
request_timeout | 30 seconds | Adapts to the response speed of livestock data interfaces, balancing request success rate and execution efficiency |
filter_param | {"breed_type": "all", "date": "yesterday"} | Accurately filters full-category breeding data from the previous day to reduce invalid data transmission |
response_parse_mode | json_array | Adapts to the return format of most official livestock interfaces, simplifying data parsing logic |
retry_times | 2 times | Handles request failures caused by occasional network fluctuations, preventing workflow interruptions from single requests |
empty_field_handler | skip_empty | Compatibility with missing fields in some regional monitoring data, ensuring normal workflow execution |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: No data is returned after workflow execution following HTTP interface configuration import. Cause: The date parameter in
filter_paramwas not configured correctly, resulting in the retrieval of expired or unmatched datasets. - Symptom:
429 Too Many Requestserrors are returned frequently during interface calls. Cause:request_intervalwas set too small, exceeding the call frequency limit of the third-party livestock data interface. - Symptom: Field matching failures occur when parsing returned data. Cause: Unit fields of livestock and poultry farming data were not adapted, and general numerical parsing rules were used directly, leading to a mismatch between units and business logic.
How to Confirm Proper Configuration
- Manually call the configured HTTP interface, pass filter parameters consistent with those used in the workflow, and check if the returned data includes expected core fields such as breeding varieties and net profit.
- Execute a single data source call in the FastGPT workflow test panel, and verify that the original response content is complete and has no abnormal status codes.
- Check workflow execution logs to confirm there are no interrupt errors caused by request timeouts or missing fields.
- Configure a scheduled trigger task, wait for automatic execution to complete, and verify that the generated broadcast content covers the target breeding categories and correct statistical dates.
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.