What the data for this category looks like
The data for this category mainly comes from the public monitoring database of the domestic dairy industry association, internal daily reports from large-scale dairy enterprises, and real-time quotes from fresh milk trading markets. There are two update schedules: daily data related to yield rates is updated at fixed times each day, while real-time indicators such as raw milk purchase prices are synchronized every 4 hours. The data is provided in structured table format, including fields such as product name, purchase cost, ex-factory guide price, channel distribution cost, and per-box profit margin. The units of these fields correspond to yuan/kg, yuan/liter, yuan/box, etc. There are no unified percentage-based indicator fields.
What constraints these characteristics impose on tool calling and plugins
Multi-source heterogeneous data sources and differentiated update schedules require tool calling to distinguish between real-time pull and scheduled pull logic, making a unified single-call process unavailable. The inconsistent field units require adding unit mapping rules in plugin configurations to align the formats of cost and price fields from different data sources. The product categories cover multiple sub-types such as pasteurized milk, shelf-stable milk, and yogurt, which requires the tool calling input parameters to include the product_category field to filter yield rate data for the corresponding category. Daily data updated at fixed times needs to be paired with scheduled workflow nodes to ensure that the latest updated dataset is pulled. Some private data sources require API authentication, so the plugin must configure the api_key parameter for identity verification.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
tool_call_trigger_mode | Scheduled Trigger + Manual Trigger | Dairy product yield rate data has fixed update times. Scheduled triggers automatically pull the latest updated dataset, while manual triggers are used for temporary verification of data accuracy |
api_request_timeout | 30 seconds | The response delay of domestic dairy public data sources is usually within 10 seconds, and 30 seconds covers conventional network fluctuation scenarios |
request_filter_params | {"product_category": ["Pasteurized Milk", "UHT Milk"]} | Need to filter yield rate data for target categories to avoid pulling redundant information from unrelated dairy product categories |
unit_conversion_rule | Map units by field name | The units of purchase cost and ex-factory price fields vary across different data sources. Mapping rules unify data formats |
max_retries | 2 times | Network fluctuations or temporary interface rate limiting may cause a single call to fail. Retrying 2 times improves call success rate |
api_auth_type | API_KEY | Most private dairy enterprise data sources require identity verification, and API_KEY authentication ensures the security of data access |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- A
403 Forbiddenerror is returned when calling the DingTalk webhook plugin. This occurs when the correct DingTalk robotaccess_tokenparameter is not configured, or the robot's permissions are not granted to the target collaboration group. - The tool call returns empty fields. This happens when the correct
product_categoryparameter is not specified inrequest_filter_params, resulting in pulling dairy product categories with no corresponding data. - A
Failed to fetcherror is returned when calling the yield rate interface. This is caused by not setting a reasonableapi_request_timeoutparameter, or the network environment being unable to access domestic dairy data source interfaces.
How to confirm the configuration is complete
- Manually trigger the tool calling node, check if the returned structured data includes the fields and units corresponding to the configured
product_category, and confirm that the data format is aligned. - Verify that the plugin's authentication parameters are correct, initiate a test call, and confirm that the interface returns normal yield rate data without authentication failure prompts.
- Configure the scheduled trigger task, wait for the next data update period, and check if the workflow automatically pulls and processes the latest data.
- View the DingTalk webhook push records to confirm whether the daily report results were successfully sent to the specified collaboration group.
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.