What the data for this category looks like
Data for railway and highway yield rates comes from public operational datasets released by the Ministry of Transport's Road Network Monitoring and Emergency Response Center, and official operational disclosure documents from regional transportation operating entities. Update cadences differ: national trunk railway data updates daily, and provincial highway regional data updates on workdays. Data is delivered in structured CSV or JSON format returned via API, including fields such as line code, operating entity type, passenger and freight turnover, total operating cost, and total operating revenue. Corresponding units are string, categorical label, million ton-kilometers, ten thousand RMB, and ten thousand RMB respectively.
What constraints these characteristics impose on tool calling and plugins
Scattered data sources use different authentication methods. Plugins must support multi-source credential configuration to separately connect to official railway interfaces and regional highway platforms. Differing update cadences require plugins to support pull tasks triggered on different cycles. This avoids excessive calls or data lag. Inconsistent field naming requires configuring standardized mapping rules. These rules ensure operational data from different sources can be uniformly identified. Potential unit differences require configuring conversion logic. This logic unifies monetary data from different disclosure units into a standard format.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
plugin_multi_source_auth | Configure API keys and OAuth2.0 credentials separately by data source type | Railway and highway data sources use different authentication methods; separate permission configuration is required to ensure access legitimacy |
plugin_update_interval | Set railway data to 86400 seconds, highway regional data to 28800 seconds | Matches the official disclosure update cycles of the two data types, avoiding data lag or excessive calls |
field_mapping_rule | Configure a universal field mapping table to map custom revenue fields from different data sources to unified fields | Different operating entities use inconsistent field naming; standardization is required to ensure the model can recognize valid data |
unit_conversion_threshold | Set to 10000 | Adapts to scenarios where most data sources disclose amounts in ten thousand RMB, completing unified unit conversion |
plugin_timeout | 300 seconds | Cross-source data pulling requires longer wait times, avoiding premature timeout interruptions |
api_rate_limit | Calibrate based on actual testing | Different data sources have different QPS limits; adjust parameters based on actual call conditions |
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 specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Mistakes
- When calling the plugin, the error
connect ECONNREFUSED 172.23.0.2:3001is returned. The cause is that public network access permissions for the data source or intranet penetration rules are not correctly configured, preventing the FastGPT service from connecting to the target data source interface. - Core fields in the pulled railway and highway data are empty. The cause is that the
field_mapping_ruleparameter is not configured, and custom fields from the data source are not mapped to unified identifiers, preventing the model from recognizing valid operational data. - Frequent
429 Too Many Requestserrors are returned during consecutive calls. The cause is that theapi_rate_limitparameter is not configured, and the QPS limit threshold of the data source is not matched, resulting in exceeded call frequency limits.
How to Verify Successful Configuration
- Call the test interface and check if the returned structured data includes core fields with unified names, and that field units match the configured conversion rules.
- View plugin operation logs to confirm that multi-source authentication credentials have passed verification, and there are no connection failure errors.
- Count the time taken for multiple calls, and confirm that the time does not exceed the configured timeout threshold.
- Check plugin operation records to confirm that the data update frequency matches the configured trigger cycle.
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.