This page configuration is based on FastGPT v4.17.0.
Data Profile for This Category
Data for this category originates from formulation and process libraries, raw material batch ledgers, reactor DCS systems, weighing systems, LIMS laboratory management systems, and warehouse systems. Updates are triggered per production batch and each key process step. Daily associated documents include batch production instructions, feeding review slips, reaction process records, cleaning records, inspection reports, deviation and change orders. Document fields include feeding amount, reaction temperature, batch number, cleaning verification results, and others. Supported units include kilograms, liters, degrees Celsius, and batch numbers.
Constraints Imposed on Tool Calling and Plugins
The multi-batch, multi-step update rhythm requires tool calling to bind to a single batch context, preventing cross-batch data mixing. The need to review multiple document types requires plugins to support bulk pulling of structured data from disparate systems, and to adapt to field formats for document types such as batch production instructions and feeding review slips. Dispersed data sources require plugins to configure permission mappings for cross-system data pulling. Meanwhile, the business requirement for formulation confidentiality restricts tool calling output content. The step switching logic of batch synthesis requires tool calling to support conditional triggering, only starting the next review round after the current process step completes.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapt to dynamic tool calling requirements for multiple document types |
| Workflow/API function-call configuration | Call only preset plugins | Adapt to review processes for fixed process steps |
| Bulk execution node cycle limit | 10 times | Match the typical number of process steps for batch synthesis |
| Sensitive information hiding toggle | Enabled, hide formulation parameters | Comply with business requirements for formulation confidentiality |
| Interface timeout threshold | 600 seconds | Adapt to delay scenarios for reactor DCS data pulling |
| Single batch data pull limit | 500 MB | Adapt to document storage limits of warehouse systems |
| Single tool calling token limit | 8000 token | Adapt to context limits of large models |
| Context association identifier | Batch number | Avoid mixing data across batches |
Three Common Misconfigurations
- The symptom is that tool call output does not display tool input and response fields. The cause is that the tool detail display toggle is not enabled, or sensitive information hiding rules are incorrectly configured, causing core fields to be hidden.
- The symptom is that bulk execution nodes complete the full process in online debugging, but fail to finish execution when called via API. The cause is that the API call does not configure the cycle timeout threshold for bulk nodes, or does not bind the batch number as a context identifier, causing the cycle to fail to terminate normally.
- The symptom is that after calling the workflow via the interface, the running data fields in the conversation log are empty, or the custom plugin output download address keeps jumping and returns results with delay. The cause is that the tool calling log recording toggle is not enabled, or the plugin is not configured with synchronous calling mode, or the timeout threshold is set incorrectly, causing delayed data return.
How to Confirm Proper Configuration
- Initiate a test call for a single batch, check if the tool call output includes core data such as the feeding review slip and reaction process record for the corresponding batch
- View the conversation log, confirm that the running data fields are filled with the system pulling results for the corresponding batch
- Verify that the number of cycles for the bulk execution node matches the number of process steps for the current test batch
- Check that the sensitive information hiding configuration only hides confidential fields such as formulations and raw material batches, and does not affect necessary review fields
The values provided are common starting points and should be measured against the reader's own samples.