What the data for this category looks like
Non-ferrous metal smelting and electrolysis business data originates from concentrate and auxiliary material analysis reports, DCS system data, electrolyzer voltage and current monitoring data, laboratory test results, and energy and environmental protection monitoring ledgers. Data is updated per batch of raw materials, each smelting furnace run, or each electrolyzer operation. Some tank condition and energy consumption data updates in real time. Daily auditing involves documents including batching lists, smelting records, electrolyzer condition records, laboratory reports, anode and cathode quality records, and environmental protection ledgers. Fields include concentrate grade, tank voltage, current intensity, element content, emission limits, and more. Each document has fixed unit and format requirements.
Constraints on tool calling and plugins
Multi-source heterogeneous data sources require tool calling to support integration with different types of external interfaces, including industrial control systems, laboratory systems, and environmental monitoring systems. Real-time and batch update data rhythms require plugin calls to adapt to short-cycle data pulling and multi-batch data processing, to avoid delays or timeouts that disrupt auditing workflows. Fixed-field format business documents require structured data returned by tools to match preset fields. Without matching, auditing calculations such as component balance and tank condition analysis cannot be completed. Errors in the auditing link can lead to reduced metal recovery rates and unqualified products. Tool calling must therefore be configured with retry and exception capture mechanisms to reduce the risk of process interruption.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapts to multiple scenarios including supplier qualification auditing and process quality auditing, automatically selects matching tools |
| Workflow/API function-call configuration | enabled | Supports calling external data source plugins to obtain real-time smelting and laboratory data |
| Single plugin call timeout | 600 seconds | Covers the data acquisition duration for concentrate analysis and tank condition monitoring, avoids interrupting auditing processes |
| Plugin call retry count | 2 times | Addresses temporary fluctuations in DCS and laboratory interfaces, reduces the probability of auditing failures |
| Number of plugins recalled per single call | Top 3 | Focuses on core data sources required for auditing, avoids redundant data interfering with analysis |
| Plugin return data parsing rule | Map to preset fields | Matches the fixed field formats of batching lists and electrolyzer condition records, ensures accurate auditing data |
Three common mistakes
- Phenomenon: Tool calls return unformatted full text, resulting in poor readability after front-end parsing. Cause: Structured output configuration for
functionCallis not enabled, and no field mapping rules are configured for plugins. Returned content is not organized according to business document formats. - Phenomenon: Disconnection occurs when the front-end forwards tool call stream data. Page data remains fixed without recovery. Cause: No timeout reconnection logic is configured for plugin calls, or session recovery after stream interruption is not handled. Intermediate services cannot resume data forwarding.
- Phenomenon: When creating a system plugin in a Docker-deployed FastGPT, the
packages/plugins/registerfile cannot be found. Cause: FastGPT v4.17.0 has adjusted the plugin registration path to thedata/pluginsdirectory. Configuration paths must be modified according to official guidelines.
How to confirm the configuration is correct
- Initiate a tool call for supplier qualification auditing. Check if returned results include preset fields such as concentrate composition and tank condition, and if field formats match business documents.
- Simulate an interface timeout scenario. Confirm that the tool call triggers a retry mechanism, and the number of retries matches the configured settings.
- View plugin call logs. Confirm that all configured data source interfaces can normally pull data, with no permission or connection errors.
- Test a specified workflow call. Confirm that the auditing process is triggered after passing corresponding parameters, and expected structured results are returned.
The values provided are common starting points and should be measured against the reader's own samples.