What the data for this category looks like
Data sources for this category include DCS/APC systems, LIMS laboratory information management systems, tank farm metering systems, crude oil evaluation databases, equipment management systems, and energy management systems. Data update cadences cover real-time (unit process parameters), shift-by-shift (shift handover records, material balance), and daily (distillate export quality reports, change management documents). Daily documents include operating procedures, production plans, material balance sheets, distillate export quality reports, interlock logs, shift handover records, and change management documents. Data fields include unit load, distillation range, sulfur content, tank farm inventory, and more, with corresponding units such as tons per hour, degrees Celsius, milligrams per kilogram, cubic meters, and others.
What constraints these characteristics impose on tool calling and plugins
The mixed update cadence of multi-source heterogeneous data requires tool calling and plugins to support parallel configuration of scheduled pulling and real-time triggering. Multiple units coupled through material and energy networks require plugins to associate cross-unit process parameters, quality inspection data, and tank farm metering data. Refining documents with fixed structures but numerous fields require tool calling to filter data source scope by document type. Since errors may trigger severe production risks, plugins must be configured with timeout and fault tolerance mechanisms to prevent call abnormalities from disrupting production processes.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Supports automatic matching of tool calls and natural responses, adapting to mixed multi-task requirements in petroleum refining scenarios |
| Plugin timeout threshold | 300–600 seconds | Adapts to the response window of refining process parameters, avoiding critical process interruptions due to timeout |
| Function call retry count | 2 times | Balances interface call success rate and system load, preventing exceptions caused by repeated requests |
| Data source filtering rules | Match by document type and update frequency | Only call data sources such as DCS data and quality reports associated with the current question, narrowing the call scope |
| Return result filtering rules | Retain the top 3 pieces of data related to quality issues | Focus on core relevant information, avoiding interference from redundant data during analysis |
Three Common Misconfigurations
- Phenomenon: Custom plugin calls return empty fields or 504 timeout status codes. Cause: Failure to adapt to internal network access restrictions of refining systems, or timeout threshold set too short to cover data pulling duration.
- Phenomenon: Unable to find the function call configuration entry in the interface. Cause: The tool calling function module was not enabled in the FastGPT backend, or the FastGPT version was not upgraded to v4.17.0.
- Phenomenon: Quality data returned by plugins does not match actual LIMS reports. Cause: Data sources were not filtered by document type, and irrelevant shift handover records or equipment ledger data was called.
How to Verify Correct Configuration
- Manually trigger a plugin call, check if the returned results include core fields for petroleum refining scenarios, and confirm that the data source filtering rules are active.
- Simulate a process fluctuation scenario, test the timeout and retry mechanisms for tool calls, and confirm that the system triggers retries or returns clear error messages when a timeout is simulated.
- Compare the direct reply from the LLM with the reply after tool calling, confirm that the
functionCallparameter is configured correctly, and that the tool call results are properly integrated into the reply. - Check the system logs, confirm that the interface address and authentication parameters for plugin calls match the configuration of the enterprise's internal systems.
The values provided here are common starting points, and should be validated against the reader's own samples.