Data Characteristics for This Category
Data related to livestock and poultry farming financial reports comes from two primary sources: the Ministry of Agriculture and Rural Affairs’ livestock and poultry farming monitoring database, and publicly disclosed periodic reports from listed farming entities. There are two update cadences: industry monitoring data is updated monthly, and listed entity financial report data is updated quarterly and annually. Documentation is structured by farming category, with modules covering core fields including inventory scale, slaughter volume, total feed consumption, unit farming cost, and disease prevention and control indicators. Field units use standard professional measurements such as 10,000 head, tons, and yuan per kilogram. Field naming conventions vary across different data sources, with no unified standard.
Constraints on Tool Calling and Plugins
When calling tools, differences in field naming and units across multiple data sources require dedicated field mapping and unit conversion rules for each data source. This prevents data parsing errors. Different data sources follow distinct update cadences. Scheduled trigger cycles must be configured to match monthly industry data pulling needs, as well as quarterly and annual financial report pulling needs. Livestock and poultry farming has many distinct categories. Category parameters must be passed during tool calling to accurately filter relevant data, reducing redundant requests and invalid data. Large annual financial report documents have large file sizes. Tool calling workflows must support configuration for large file parsing and transmission, to avoid timeouts or data truncation.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
HTTP_REQUEST_TIMEOUT | 300 seconds | Response delays for livestock and poultry farming industry data sources are generally high; 300 seconds covers most normal request durations |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Annual financial report PDF files from some listed entities have large volumes, requiring adaptation to long document parsing needs |
TOOL_FIELD_EXTRACT_RULE | Match by specified field name | Fields in livestock and poultry farming financial reports are highly specialized; explicitly specifying core fields such as slaughter volume and inventory volume avoids extracting irrelevant data |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large financial report documents takes significant time; 600 seconds prevents parsing from being interrupted mid-process due to timeout |
MCP_TOOL_RETRY_COUNT | 2 times | Industry data source interfaces may experience temporary fluctuations; 2 retries reduces the impact of single request failures |
API_DEFAULT_TIMEOUT | 600 seconds | FastGPT external API calls must adapt to long-duration financial data pulling and parsing processes |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- The phenomenon is that an HTTP request component interface call succeeds, but returns empty fields. The cause is that
TOOL_FIELD_EXTRACT_RULEis not configured to specify target extraction fields, so the default full data extraction fails to match specialized fields in livestock and poultry farming financial reports. - The phenomenon is that the MCP tool returns a
504 Gateway Timeouterror. The cause is that theHTTP_REQUEST_TIMEOUTparameter is not adjusted, and the default timeout duration is insufficient to cover the response delay of industry data sources. - The phenomenon is that file upload fails after the MinerU container starts, with a prompt indicating the file exceeds the limit. The cause is that the
--env UPLOAD_FILE_MAX_SIZE=2048MBparameter is not added to the container startup command, and the default 2 MB limit is used.
How to Confirm Configurations Are Valid
- Initiate a test HTTP request, check whether the returned results include preset core fields of livestock and poultry farming financial reports, to confirm that the field extraction rule is effective.
- Call the MCP tool to initiate a simulated request, check whether the platform logs show the request timeout duration as the configured
300 seconds, to confirm that the timeout parameter is effective. - Upload a 1.5 GB simulated financial report PDF file, confirm that the upload progress is normal and no file size limit error occurs, to confirm that the upload size configuration is effective.
- Call the FastGPT external API interface, check whether the response duration of the interface return meets expectations, to confirm that the API timeout parameter is configured correctly.
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.