What this category's data looks like
This category's data comes from daily business documents of skincare, haircare, makeup, and special cosmetics manufacturing enterprises. These include formula process sheets, weighing and feeding records, emulsification or filling records, cleaning and site clearance records, semi-finished and finished product inspection reports, and label review documents. Data sources cover registered and filed formulas, raw material safety materials, production equipment, ERP/MES systems, laboratory data, and packaging material version information. Updates are triggered per production batch or each line change. Core fields include restricted substance lists, production parameters, batch numbers, and packaging material versions.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Since data for this category updates per production batch or line change, multi-turn dialogue must bind exclusive context for the corresponding batch to avoid mixing cross-batch data. Core fields such as restricted substance lists, production parameters, batch numbers, and packaging material versions must be precisely matched to the current production stage’s document content via prompts. Multiple data sources require that variables from different systems can be called during dialogue. Additionally, label and formula filing constraints require that dialogue output strictly adheres to compliant fields and does not exceed the scope of filed information.
Configuration settings
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Method | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current production batch | Ensure each batch’s dialogue context is independent, preventing cross-batch production data mixing |
messages | Store full dialogue and document association records for the current batch | Fully retain full-link data of the review process to support subsequent traceability |
variables | Bind formula, raw material, and packaging material variables for the current batch | Directly call uploaded filed data and production parameters to reduce repeated input |
| Context window | 1200–1800 tokens | Match the average length of single-batch production documents to prevent context overflow |
| Prompt template | Link to the current batch’s filing compliance requirements | Ensure dialogue output strictly adheres to registered and filed fields and rules |
Three common mistakes
- Phenomenon: Forced concatenation of outputs from two AI dialogues results in logical confusion. Cause: The
variablesparameter was not used to bind unified context variables for the current batch, causing outputs from different sessions to not associate with the same production batch data. - Phenomenon: Full dialogue records cannot be retrieved for batch review. Cause: Full storage configuration for the
messagesparameter was not enabled, only single-turn or partial dialogue content was retained. - Phenomenon: Uploaded production process images cannot be correctly interpreted. Cause: Associated prompts for image analysis were not configured, or image variables were not bound to the dialogue workflow.
How to verify a correct configuration
- Initiate a dialogue for the corresponding batch, check if
chatIdmatches the current production batch’s identifier. - Call the dialogue log interface to confirm that full
messagesrecords for the current batch can be retrieved. - Upload the current batch’s formula document, check if dialogue output associates with filed restricted substance information.
- Test concatenating two dialogue outputs from the same batch, confirm logical coherence without conflicts.
The values provided are common starting points and should be evaluated against relevant samples.