What the data for this category looks like
Data sources for feed intelligent due diligence include raw material purchase ledgers from feed manufacturers, finished product inspection reports, logistics tracking systems in circulation links, and feeding record databases from downstream breeding terminals. Data update frequencies vary: raw material purchase data syncs daily, finished product inspection reports generate with each shipment batch, logistics data updates every 12 hours, and terminal feeding feedback aggregates weekly. Data is delivered in structured JSON format. Core fields include raw material batch identifier, crude protein content, moisture content, production license number, delivery date, logistics node list, and terminal feeding intake data. Corresponding units are batch number, grams per kilogram, grams per kilogram, identification number, date, node name, and kilograms per head per day. No overly deeply nested hierarchical structures exist.
Constraints Imposed on HTTP Interfaces and External Systems by These Characteristics
Feed due diligence data comes from three independent systems: production, logistics, and terminal systems. Each system uses different interface authentication methods, so multiple sets of authentication parameters must be configured in HTTP requests. Batch data updates based on shipment nodes. Queries must support batch number and time range parameters to accurately pull target data. Field units vary across different data sources. Some sources use percentage formats, others use grams per kilogram formats. Unified conversion must be applied after interface responses, so field mapping configuration items must be reserved. Logistics data has high real-time requirements. Polling intervals must align with the 12-hour sync cycle to avoid overly frequent requests or delays relative to data update cycles. Total feed batch data volume is large. Pagination pulling is a common requirement, so pagination query parameters must be configured.
How to Configure the Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
request_method | GET or POST | Match interface requirements of the corresponding data source. GET is used for query and pulling, POST is used for batch submission or authentication |
auth_type | api_key, oauth2, or none | Adapt to the multi-source authentication needs of feed data. Production ERP systems mostly use api_key, logistics platforms mostly use oauth2 |
response_parse_type | json_path | Feed data uses structured JSON format. JSONPath must be used to extract specified fields for downstream nodes |
timeout | 30-60 seconds | Adapt to the response speed of ERP-type data sources, avoid request failures caused by short timeouts |
field_mapping | Configure based on the correspondence between data source fields and standard fields | Unify field names and units across different data sources, prevent errors in subsequent due diligence report generation |
request_body_max_size | 10-20 MB | Adapt to the upload requirements of attachments such as feed inspection reports, avoid triggering interface size limits |
The parameter values provided on this page are all common recommendations that serve as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: Downstream nodes cannot retrieve extracted variables after an HTTP response is returned. Cause:
response_parse_typeis not correctly configured asjson_path, or the JSONPath expression syntax is incorrect and fails to match target fields. - Phenomenon: Error logs starting with
[failed to get]appear when starting the container. Cause: The server lacks network permissions and cannot connect to external data source interfaces, leading to configuration pull failures during initialization. - Phenomenon: HTTP requests return a 413 status code and are rejected. Cause: The
request_body_max_sizeparameter is not configured, or the size of uploaded feed batch inspection report attachments exceeds the limits of the external interface.
How to Confirm Configuration is Successful
- Initiate a single test request, view the original data returned by the interface, and verify whether the JSONPath expression can correctly extract target fields.
- Check container runtime logs to confirm there are no
[failed to get]type errors, and verify that network connectivity and authentication configurations are effective. - Compare returned fields from different data sources, and check whether the
field_mappingconfiguration has completed unified conversion of units and field names. - Initiate a batch pull request, confirm that pagination parameters are effective, and verify that the number of returned feed data batches matches the expected configuration.
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.