What This Category's Data Looks Like
Organizations source cosmetics manufacturing process and standard data from registered and filed formulas, raw material safety documents, weighing and emulsification equipment, ERP/MES systems, laboratory test records, and packaging material version archives. Teams update this data per production batch and each line change. Daily documents include formula process sheets, weighing and feeding records, emulsification and filling records, cleaning and site clearance records, semi-finished and finished product test reports, and label review forms. Core fields cover raw material restricted substance content, emulsification temperature, production batch number, and packaging material version number, with corresponding units of percentage, degrees Celsius, batch number, and version number.
Constraints on Workflow Orchestration
Organizations update cosmetics production data per batch and each line change, and the data must adhere to filing compliance requirements. Workflows must bind batch dimension variables to associate corresponding production data. Multi-source, heterogeneous document types require workflows to support calling data sources from different systems across nodes. Teams must add verification links to the process to ensure consistency between formulas, labels, and filed data. Errors in production links directly affect product compliance. Teams must configure exception retry and fallback processing logic in workflows to avoid interrupting production-related Q&A processes due to single-node failures. Process issue descriptions often involve multiple sets of parameters. Teams building workflows must support context association to ensure Q&A coherence.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind three types of fields: production batch number, raw material name, and emulsification temperature threshold; store the first 3 rounds of conversation context | Cosmetics production data is updated per batch, and batch dimension association is required to verify filing consistency. Context is used for coherent Q&A on process issues |
| Question Optimization | Enabled, with the optimization goal of accurately matching filed raw materials and process parameters | Process procedure questions are scattered in expression, and optimization can improve the accuracy of knowledge base recall |
| Single Search Limit | Top 8 entries | Cosmetics filing data has clear entries, and too many results will increase the AI processing load |
| Node Trigger Condition | Trigger in nodeId order; trigger 2 retries for abnormal nodes | Production processes must strictly follow the process sequence, and retries can reduce the impact of single-node abnormalities on the process |
| Maximum Context Length | 800–1200 characters | Cosmetics process issues involve multiple sets of parameters, and overly long context will cause AI processing timeouts |
Three Common Mistakes
- After a workflow starts, a team calls a third-party API but receives no valid result, and the node status shows timeout. The cause is that the team did not configure parameter verification logic for API calls, and did not pass production batch-related
variablesinto the request, resulting in missing parameters. - A workflow stops after running to the knowledge base search node, and no subsequent output appears in the dialog box. The cause is that no trigger connection between nodes is configured, or no fallback processing logic is set when the search result is empty.
- Historical conversation records cannot be passed as variables to code nodes, and there is no historical conversation option in the variable selection list. The cause is that the context storage configuration for
variablesis not enabled, and historical records are not mapped to callable variable fields.
How to Confirm a Valid Configuration
- Submit a process question that includes a specific production batch number, and check whether the workflow nodes trigger in
nodeIdorder and return corresponding filed data. - Simulate a third-party API call scenario, and verify whether the batch parameters stored in
variablesare correctly passed into the request. - Trigger an abnormal node, such as simulating an empty search result, and check whether the preset fallback processing logic is triggered.
- View the node logs in FastGPT v4.17.0, and confirm that the execution order of each node conforms to the preset workflow orchestration.
Note: The values listed above are common starting points. They should be evaluated against the reader's own samples and use cases.