What the data for this category looks like
Data for this category comes from online composition analysis equipment, DCS control systems, laboratories, kiln and grinding equipment, raw fuel ledgers, and energy metering devices.
Daily documents include raw meal batching plans, kiln operation records, laboratory reports, quality control notices, equipment inspection records, and energy reports.
Data update frequencies fall into three groups: real-time (such as kiln temperature and online composition data), shift-based (such as inspection records), and daily (such as energy reports and daily quality summaries).
Document fields cover raw material ratio parameters, kiln thermal parameters, laboratory test indicators, equipment operating status, and more. Corresponding units include degrees Celsius, megapascals, tons, and others.
Constraints for Tool Calling and Plugins Workflow
This category has multi-source heterogeneous data with large differences in update frequencies. Tool calling must support connecting to multiple types of data source plugins, and adapt to task triggers with varying update frequencies.
Document structures vary significantly across file types. Plugins must support content extraction for tabular documents (such as raw meal batching plans), plain text records (such as kiln operation logs), and structured reports (such as quality control notices).
Business errors directly cause production shutdowns and quality returns. The tool call result verification step must add parameter rationality checks to prevent abnormal data from entering subsequent audit processes. Real-time data calls must ensure low latency to meet real-time adjustment requirements for kiln thermal systems.
How to Configure
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapt to the calling needs of multiple data source types and document structures, automatically match the execution scenario of the current task |
| Text content extraction node context count | Top 6 chat records | Match common plugin node configuration habits among community users, cover complete task context |
| Maximum response duration for single tool call | 30–60 seconds | Meet latency requirements for real-time kiln temperature data calls and daily report audits, calibrated based on actual testing |
| Tool call result verification rules | Match business parameter threshold ranges | Based on conventional parameter ranges for raw meal batching and kiln thermal systems, filter abnormal data |
| Workflow/API function-call configuration | Enabled | Force structured output of tool call results to facilitate automatic parsing in subsequent audit processes |
| Multi-data source plugin parallel call switch | Disabled | Avoid excessive system load caused by simultaneous requests from multiple data sources, adapt to existing server configurations of cement enterprises |
Three Common Misconfigurations
- Phenomenon: The result returned after tool call trigger does not match the preset cement production data source, and general knowledge base content is called instead. Cause: The
toolChoiceparameter is not configured correctly, causing the call scope to not be limited to the exclusive data source plugins for this category. - Phenomenon: The workflow is configured with a text content extraction plugin using 6 chat records as context, and the extraction result has redundancy or missing content after execution. Cause: The context count is not adjusted for the multi-source data scenario of this category, and the context range is not reduced in real-time data scenarios, causing data interference.
- Phenomenon: A format error prompt is returned when calling a multimodal tool for equipment inspection photos. Cause: The conventional resolution and format requirements for inspection photos of this category are not adapted, and the input parameters of the plugin are not configured correctly.
How to Verify Proper Configuration
- Perform a single tool call test, check whether the returned result includes core data fields of this category such as raw meal batching and kiln temperature.
- View the running logs of the plugin node, confirm that the context count matches the configured value, and no redundant data interferes with the extraction result.
- Trigger a multimodal image call test, check whether the returned result can correctly parse the content of inspection equipment photos.
- Adjust the
functionCallparameter, confirm that the tool call result is output in a structured format to facilitate subsequent audit process processing.
The values provided here are common starting points and should be evaluated against the reader's own samples.