What the data for this category looks like
Three main sources provide data for special steel intelligent due diligence reports: internal ERP systems of special steel manufacturers, publicly disclosed data from third-party industry information platforms, and downstream customer acceptance reports. Updates follow three schedules: production process and factory release data updates daily, industry statistical data updates weekly, and downstream performance records update monthly. The document structure of a single report includes three core modules: batch details page, performance testing page, and performance ledger page. Report fields include unique batch identifier, production parameters, testing indicators, delivery weight, and performance cycle. All units use the metric system, where weight is measured in tons and strength-related indicators are measured in megapascals.
What constraints do these characteristics impose on the tool calling and plugins link
The multi-source and multi-cycle update characteristics of special steel data require tool calling to be configured with multi-task scheduled pulling, where each task corresponds to a pull interval for a different data source. Nested performance testing sub-fields and standardized metric units require plugins to support structured field parsing and format verification to avoid passing non-standard unit data. The growth of data volume alongside production batches requires plugins to be configured with pagination pulling parameters to prevent excessive single request data volume from triggering interface current limiting or timeouts. In addition, custom field naming variations exist in the special steel industry, which requires tool calling to support field mapping configuration to adapt to field differences across different data sources.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
plugin_api_timeout | 300 seconds | Special steel due diligence data interfaces usually contain multiple batches of testing data, with large single request return volumes. 300 seconds can cover the complete pulling process |
embedding_dimension | 1024 | Adapts to the embedding dimension of bge-large-zh-1.5, ensures vector matching accuracy, and is compatible with other embedding models of the same dimension |
plugin_request_content_type | application/json, application/x-www-form-urlencoded | Special steel data source interfaces use two parameter passing formats. Supporting both formats can adapt to requirements of different third-party interfaces |
plugin_pagination_size | 500 entries | Single batch pulling data volume adapts to interface current limiting thresholds, avoiding current limiting triggers due to excessive single request data |
tool_call_max_retries | 2 times | Special steel data source interfaces have occasional fluctuations. Retrying twice covers most temporary exceptions and avoids data duplication caused by repeated pulling |
parse_field_mapping | Calibrated based on actual testing | There are custom naming variations for fields in the special steel industry. Interface return fields need to be mapped to standard due diligence report fields |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: An external embedding model interface returns a 400 error, prompting a dimension mismatch. Cause: The 1024-dimensional embedding parameter consistent with bge-large-zh-1.5 is not specified, and a request is initiated using the default dimension directly.
- Phenomenon: A third-party interface returns a parameter parsing failure after the plugin sends a request. Cause:
plugin_request_content_typeis not configured to the corresponding format, and only the default application/json is used, which cannot adapt to the application/x-www-form-urlencoded parameter passing requirements of some special steel data sources. - Phenomenon: The front-end calls the intelligent question answering interface and returns a 502 error. Local testing is normal but the online environment fails. Cause: The interface cross-domain whitelist is not configured, or the online domain name is not added to the allowed calling domain list.
How to confirm the configuration is complete
- View the plugin execution log to confirm that the single request duration does not exceed the configured
plugin_api_timeout. - Check the embedding model call log to confirm that the returned vector dimension is consistent with the configured
embedding_dimension. - Initiate multiple rounds of tool calling tests to check whether the pagination pulling results fully cover the full volume of data.
- Check the cross-domain configuration to confirm that the online domain name has been added to the allowed calling domain list.
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.