Data Profile for This Category
The primary data sources are factories producing bread, pastries, biscuits, instant noodles, and frozen steamed products. Daily documents include formulas and feeding lists, production records, baking or steaming curves, metal detection logs, cleaning and disinfection records, and factory release inspection reports. Data comes from raw and auxiliary material qualification certificates, ERP/MES systems, weighing systems, production equipment, laboratory test data, and food traceability ledgers. Updates run per batch, per shift, or daily. Fields include feeding quantity, baking duration, packaging date, shelf life, and similar metrics. Common units are kilograms, minutes, days, and other standard units.
Constraints for Multi-turn Dialogue and Prompt Configuration
Data sources for this category are scattered, update frequency is high, and fields have strong interconnections. These traits create multiple constraints for multi-turn dialogue and prompt configuration. First, multi-source data requires gradual alignment of field differences across ERP, production equipment, and laboratory systems via multi-turn dialogue. This avoids cross-system data conflicts. Second, frequent product line changes and batch updates require limiting the context window to a reasonable range. This prevents redundant data from interfering with current batch ledger summary work. Third, priority requirements for allergen control and foreign matter inspection demand that prompts first guide users to input batch identifiers. Then the system can retrieve corresponding production records and test reports, to ensure efficient verification for core links.
Configuration Settings
The following configurations are adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
messages | First 8 turns of dialogue context | Batches in this category are updated frequently. Excessively long context disrupts current batch data recognition. 8 turns cover the multi-stage verification process for a single batch |
variables | Bind two required variables: batch number, production line number | Frequent line changes in this category require variables to anchor production ledgers and test reports for the target batch, to avoid data confusion |
| Maximum context length | 1200–1500 characters | Core ledger data volume per batch is moderate. This range fully carries key information from formulas, baking curves, and test reports, while avoiding redundant content |
| Dialogue trigger rule | Trigger by batch number | Data in this category updates per batch. Triggering by batch number accurately retrieves production records for the corresponding production line, and prevents cross-batch data mixing |
chatId | Bind current production line session ID | When multiple production lines run simultaneously, chatId isolates dialogue contexts for different lines, to prevent data cross-interference |
Three Common Misconfigurations
- Phenomenon: Dialogue logs are not recorded after calling external applications or plugins. Cause: The dialogue log synchronization switch is not enabled in workflow configuration. Cross-application call interactions are not included in the current session context as a result.
- Phenomenon: Form input node dialog boxes are hidden in standalone workflows, but remain visible when nested into other workflows. Cause: Display parameters adapted for embedded scenarios are not set in the nested workflow’s node configuration. The outer workflow’s interaction rules are not followed as a result.
- Phenomenon: No corresponding content displays in the interface when attempting to render web pages or output text-to-image results in dialog boxes. Cause: Rich text rendering configuration for the dialogue window is not enabled, and text-to-image model call binding is not configured. Non-text content cannot be generated or rendered as a result.
How to Verify Proper Configuration
- Enter a test batch number. Check whether the dialogue automatically retrieves formula, production record, and other data for the corresponding batch. This confirms variable binding takes effect.
- Call an external plugin. Check whether the session log fully records this interaction. This confirms the dialogue log synchronization configuration is correct.
- Test the form input node in a nested workflow. Check whether the dialog box hides or displays as expected. This verifies configuration adaptability for embedded scenarios.
- Send a command containing a rich text or image request. Check whether the dialogue window normally renders the corresponding content. This verifies rich text and model binding configuration.
The values provided here are common starting points, and should be evaluated against the reader’s own samples.