What data looks like for this category
Data for this category comes from online composition analysis equipment, DCS systems, laboratories, kiln and grinding equipment, raw fuel ledgers, and energy metering devices. Data update cycles fall into three categories: real-time, shift-based, and daily. It covers multiple document types including raw material batching plans, kiln operation records, laboratory reports, quality control notices, equipment inspection records, and energy reports. Fields include raw material ratio parameters, equipment operation readings, laboratory indicator values, and energy consumption statistics. The field structure and naming vary across different documents, with no unified fixed format.
Constraints for tool calling and plugins
The scattered data sources and varied update cycles for this category require tool calling to adapt to multi-system data pulling and trigger requirements of different frequencies. Large differences in field structures across multiple document types demand plugins configured with flexible field mapping rules to accurately extract target parameters from different documents. Data anomalies may cause clinker quality fluctuations or equipment downtime, so tool calling must be set up with complete failure retry and exception alert mechanisms. Additionally, some tools use stream or SSE protocol modes, requiring adaptation to corresponding communication and result receiving logic to avoid missing results or failed data splicing.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | Specified by ledger type | Adapt to tool calling requirements for different documents |
| Workflow/API function-call configuration | Configured per field mapping rules | Accurately extract target parameters from ledgers |
| HTTP request timeout | 600 seconds | Matches the real-time data update interval of DCS systems |
| Number of returned entries per tool call | First 20 entries | Adapts to the upper limit of field count for a single ledger |
| Plugin import path | Local plugin package directory | Complies with directory specifications for FastGPT v4.17.0 and later private deployment versions |
| Context capacity | 8000 token | Supports aggregated data from multiple ledgers |
Three common mistakes
- Symptom: Unable to retrieve complete final results after setting the stream parameter to true when calling an HTTP interface. Cause: No logic was configured to wait for the stream to finish, and segmented returned data was not correctly spliced.
- Symptom: An internal server error prompt appears when importing plugins in a privately deployed FastGPT instance. Cause: The directory permissions of the plugin package do not match the private deployment server configuration, or an incompatible plugin format was used.
- Symptom: When using an MCP tool wrapped with the SSE protocol, the system prompts that only stdio processes are supported. Cause: The communication protocol type was not correctly specified in the plugin configuration, and adaptation to the tool's actual operating mode was not completed.
How to confirm correct configuration
- Run a tool calling test for a single ledger, and check if the returned results include the preset target fields.
- View system logs after importing plugins, and confirm there are no internal server error type error messages.
- Enable stream calling mode, and verify that all segmented data returned by the interface can be fully received.
- After configuring field extraction rules, compare with the actual content of ledger documents to confirm that extraction results match expected outcomes.
The values provided here are common starting points and should be measured against the reader's own samples.