What the Data for This Category Looks Like
Steel trade-related data primarily comes from steel mill price adjustment letters, port warehouse ledgers, logistics freight rate public notices, and downstream manufacturing procurement order ledgers. Data update cadence is divided into tiers: Steel mill ex-factory unit prices are updated daily. Port inventory data is updated weekly. Downstream demand ledgers are aggregated monthly. Most documents are in structured table format. Fields include steel product name, specification model, origin identifier, tax-included unit price, inventory volume, and delivery cycle. Corresponding units are no identifier, millimeters, origin code, yuan/ton, ten thousand tons, and calendar days.
Constraints Imposed by These Characteristics on Tool Calling and Plugins
Differences in update cadence across multiple data sources require configuring multi-data source synchronization scheduling rules for tool calls. This prevents marketing content distortion caused by data timeliness deviations. The complexity of structured specification model fields increases the parameter verification threshold for tool calls. Precise matching must be implemented for combinations of product names and specifications. The high-frequency updates of unit price data require that tool call cache duration be set to no more than 24 hours. Otherwise, quotation deviations will occur. Non-standardized downstream demand ledger fields require custom field mapping rules to be configured for plugins. Only then can effective data integration be completed.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
tool_call_timeout | 300 seconds | Steel trade data interfaces are mostly internal enterprise or third-party public interfaces. Response times typically fall between 2 and 5 minutes. 300 seconds covers most normal calling scenarios |
tool_cache_expire | 86400 seconds | Steel mill ex-factory unit prices are updated daily. Setting the cache duration to one day ensures data timeliness while reducing repeated call volume |
max_tool_calls_per_session | 10 times | Generating steel trade marketing content requires calling multiple tools such as inventory, freight rate, and demand tools. 10 calls cover conventional multi-tool linkage scenarios |
spec_matching_threshold | 0.85 | Steel specification models have multi-dimensional combinations. Setting the similarity threshold to 0.85 enables precise matching of valid specification data and avoids mismatches |
field_mapping_mode | Custom mapping | Downstream demand ledger fields have non-standard differences. Custom mapping adapts to ledger formats from different sources |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material forms, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: When calling MCP-type steel trade data tools, a 400 status code is returned when using a large language model deployed via Xinference. Cause: The tool calling request format of the Xinference model does not match the default MCP protocol parameters of FastGPT. Structured tool calling parameters were not passed correctly.
- Phenomenon: Interface calls return the
aiPointsNotEnougherror code. Cause: Insufficient calling point quota was not configured. Steel trade tool calls frequently request data from multiple sources. Insufficient quotas will trigger this error. - Phenomenon: Marketing materials generated by multimodal plugins do not include steel specification images. Cause: Associated image pulling for specification parameters was not enabled in plugin configuration. This prevents matching corresponding material assets.
How to Confirm Configuration Is Correct
- Initiate a single tool call request for steel inventory data. Verify that the returned result fields include core preset information such as product name, inventory volume, and origin.
- Simulate a marketing content generation process involving multi-tool linkage. Check whether the timestamp of each tool's returned data meets the preset update cadence requirements.
- Review tool call logs to confirm that no error messages such as timeouts or permission verification failures appear.
- Test the custom field mapping configuration. Convert non-standard downstream demand ledger fields to a unified format. Verify the accuracy of the conversion results.
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.