What data for this category looks like
This category of data primarily comes from instrument assembly and commissioning sheets, calibration procedures, original calibration records, error curves, metrology certificates, and software version logs. Data sources include design documents, standard instrument and environmental monitoring data, calibration software, laboratory information systems, and customer range requirements. Data is updated per instrument and per calibration workflow. Each entry includes fields such as tested part number, calibration date, standard instrument parameters, ambient temperature and humidity, error calculation values, and metrology certificate number. Most units are internationally recognized units of measurement, such as pascals, degrees Celsius, and milliamps.
What constraints these characteristics impose on tool calling and plugin workflows
This category of data is updated per instrument and per calibration workflow. It requires tool calls to accurately bind to a single device’s single calibration workflow, to avoid mixing cross-batch data. Multiple data sources require plugins to connect to heterogeneous data sources including calibration software and laboratory information systems. Plugins must support different formats of calibration records and certificates. Data includes precision metrology fields and specialized units. Tool calls must correctly identify and pass unit parameters to prevent calculation deviations. Quality traceability requires fast retrieval of traceability chain information. Tool calls must reduce time spent on manual review steps, to fit the tight timeline of calibration workflows.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto or a specified calibration data query tool | This category requires precise calls to calibration data-related tools. The auto mode automatically matches tools, while the specified mode enforces association with instrument traceability tools, and complies with parameter rules for FastGPT v4.17.0 |
| Workflow/API function-call configuration | Enabled, with parameter verification threshold set to 90% | Ensures tool call parameters match calibration fields, avoids invalid calls, and maintains accuracy of quality traceability |
| Tool call timeout | 120–180 seconds | Calibration data retrieval collects multiple error values, which takes longer. Adjust values based on actual testing |
| Data source connection retry count | 3 times | Connections to calibration software and laboratory information systems may be affected by network fluctuations. Retries reduce the probability of connection failure |
| Variable parameter format verification | Match units of measurement and field types | This category of data includes precise measurement units. Verify that incoming variable units match field requirements to prevent calculation deviations |
| Number of results returned | Top 10 calibration records | Quality traceability requires retrieving recent calibration data. Excessive data increases context load and reduces call efficiency |
Three common configuration mistakes
- Symptom: Tool call returns a
tool_callsformat error, with logs showing400 Messages with role ' （extra leading and trailing spaces）| Cause: Leading and trailing spaces in the role field were not verified. Incoming role parameters contain hidden spaces, which do not meet tool call format requirements - Symptom: No output is generated when calling the database connection plugin after local deployment | Cause: The access whitelist for the local database was not configured, or the plugin did not map the correct database port, preventing connection establishment
- Symptom: Manual SQL execution works normally, but an error occurs when passing SQL parameters via variables | Cause: SQL parameters passed via variables were not escaped. Special characters such as single quotes break SQL statement structure, and matching between parameters and calibration data fields was not verified
How to verify correct configuration
- Call a tool to retrieve calibration records for a single instrument, and verify that returned fields match those on metrology certificates and original calibration records
- Pass a variable parameter with a unit of measurement, execute a tool call, and verify that the parameter was not altered and meets format requirements
- Simulate network fluctuations, disconnect the data source, then retry. Verify that the plugin executes reconnections according to the configured retry count
- View tool call logs in FastGPT v4.17.0, confirm that
toolChoiceorfunctionCallparameters take effect as configured, with no format errors
The values given are common starting points and should be measured against the reader's own samples.