What data looks like for this category
Daily documents for forging and die forging include forging process specifications, cutting stock cards, heating furnace records, forging process cards, mold life records, heat treatment work orders, and ultrasonic testing reports. Data sources include raw material quality certificates, heating furnace systems, press collection data, MES, and non-destructive testing instruments. Data update frequency is per forging piece, per batch of forgings, or per furnace run. Document fields include forging batch number, heating temperature (℃), holding time (seconds), mold number, defect type, and others. Each field must match the unit and format requirements of the corresponding business scenario.
What constraints these characteristics impose on the tool calling and plugins workflow
Dispersed data sources require real-time pulling of the latest furnace and batch data, so plugins must support connecting to multiple types of system interfaces. The high-frequency update business feature requires tool calling to adapt to small-batch, real-time pulling logic to avoid redundant data loading. The need for standardization of multiple fields and units requires plugins to complete field mapping and format verification, ensuring that generated process documents and exception reports comply with industry specifications. The serious consequences of errors require tool calling to configure failure retry and exception interception mechanisms to prevent erroneous data from entering production links.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapts to the multi-tool calling scenario of forging process document drafting, automatically selects matching plugins to complete data pulling and format conversion |
| Workflow/API function-call configuration | enabled | Supports plugins to generate standardized exception report fields, matching required items for ultrasonic testing reports and forging process cards |
| Tool calling timeout duration | 120–180 seconds | Forging data pulling involves multiple system interface interactions, this duration covers the response cycle of most conventional interfaces |
| Bulk data pull limit | Top 10 entries | The associated testing data volume per furnace forging is limited, this limit avoids context overload affecting model processing |
| Parameter verification switch | Enabled | Verifies the units and value ranges of fields such as heating temperature and holding time, complying with the technical requirements of forging processes |
Three Common Errors
- Phenomenon: Tool calling works normally in debug mode, but triggers an interface error in runtime mode. Reason: The runtime mode does not configure access permissions for production environment system interfaces, and only the debug mode uses local test addresses to complete calls.
- Phenomenon: Connection failure error occurs when calling document parsing plugins. Reason: The deployed Docker container does not map the corresponding port of the plugin service, or the intranet firewall blocks the communication link between the plugin and FastGPT services.
- Phenomenon: gpt-4o-mini calling error logs appear during workflow operation. Reason: No context truncation rules for tool calling are configured, causing the loaded forging data to exceed the token limit supported by the model and trigger an error.
How to Confirm Configuration Is Complete
- Manually trigger tool calling to pull heating furnace record data for a single furnace run, and check that the returned fields match the requirements of the forging process specification.
- Simulate a forging piece exception scenario to trigger the plugin to generate an exception report, and verify that the report includes required items such as forging batch number, defect type, and processing suggestions.
- Check the FastGPT v4.17.0 runtime logs to confirm that the request parameters for tool calling match the configuration items, and there are no unauthorized interface access records.
- Pull forging testing data for 3 furnace runs in bulk, and confirm that the number of results returned by the plugin meets the configured bulk limit requirements.
The values provided are common starting points and should be measured against the reader's own samples.