This document is compatible with FastGPT v4.17.0.
What this category of data looks like
Data for this category comes from cell banks and seed lots, process analytics systems, cleanroom monitoring equipment, MES, LIMS, and equipment integrity test results. Daily documents include cell bank or seed lot records, culture and purification records, aseptic filling records, environmental monitoring data, media fill simulation reports, sterility test results, and batch release documentation. Data updates are triggered per production batch cycle, real-time monitoring events, and fixed monitoring schedules. Document fields include batch numbers, process parameter values, environmental cleanliness grades, test result values, and additional relevant fields.
What constraints these characteristics impose on workflow orchestration
Data sources are scattered, and update schedules vary widely. Workflows must support scheduled pulling and real-time trigger configuration for multiple data sources. Document structures include both structured parameters and unstructured reports. Workflows need to distinguish parsing rules for different document types. Batch production-related data is tied to fixed batch numbers. Workflows must retain batch association relationships during variable transfer. Exception data from aseptic manufacturing requires rapid circulation. This requires that latency between workflow nodes is kept within a reasonable range, and that branch jumps for exception triggers are supported.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Knowledge base search trigger condition | Match by batch number in variables | All data in this category is tied to fixed batch numbers, requiring precise association with process and test documents for the corresponding production batch |
| Variable storage method | Store fixed parameters in global variables | Some process baseline parameters are global default values, and do not need to be reset for each conversation |
| Knowledge base association rule | Bind knowledge base for the corresponding production link by nodeId | Different production links correspond to independent document sets, requiring precise matching of data sources |
| Single search result limit | Top 6-10 entries | Need to cover multiple data types including process parameters, environmental monitoring, and test results, to avoid information overload |
| Timeout threshold | 200-400 seconds | Adapts to standard response times for systems such as LIMS and MES, to prevent process blocking |
Three common misconfigurations
- The symptom is an empty knowledge base search return, with the interface showing no matching content. The cause is failure to use batch numbers as the search matching condition, instead using generic keyword searches that do not associate with exclusive documents for the current production batch.
- The symptom is that global default process parameters are cleared, and subsequent processes cannot read fixed values. The cause is failure to store fixed parameters in global variables, instead mistakenly storing parameters in conversation temporary variables, which are reset each time a conversation starts.
- The symptom is that multiple variables after an HTTP request cannot be bound to the corresponding knowledge base, and a configuration trigger error occurs. The cause is failure to bind exclusive variables for each link's knowledge base by
nodeId, leading to matching conflicts from mixed variable use.
How to confirm proper configuration
- Trigger the workflow for the corresponding production batch, check that the batch number in
variablesis correctly passed to the knowledge base search node - View the global variable storage list, confirm that fixed process baseline parameters have not been automatically cleared
- Verify the knowledge base binding configuration for each production link node, confirm that
nodeIdcorresponds one-to-one with link types - Simulate an exception data trigger, check that the workflow jumps to the exception report drafting branch according to preset rules
The values provided are common starting points and should be measured against the reader's own samples.