What Data for This Category Looks Like
This category’s data originates from daily operations of baked goods, cookie, instant noodle, and frozen pastry factories. It includes formulas and ingredient lists, production records, baking/steaming curves, metal detection logs, cleaning and disinfection logs, factory inspection reports, and more. Data sources cover raw and auxiliary material qualification certificates, ERP/MES systems, weighing systems, oven and frying line equipment, laboratory test results, and food traceability ledgers. Data is updated per batch, per shift, or daily. Documents include fields such as material name, ingredient quantity, baking temperature, shelf life, allergen labeling, and others. Units include kilograms, degrees Celsius, days, and additional standard food industry units.
Constraints Imposed on Model Integration and Configuration
Multi-batch, high-frequency updated business data requires model integration to support incremental synchronization, preventing excessive system resource usage from full data pulls. Diverse document types require configuring multi-format parsing rules to ensure correct reading and parsing of files with varying structures, such as formulas and test records. The accuracy of sensitive fields like allergen labeling and shelf life requires enabling field verification during configuration, to avoid incorrect labeling or omissions in bid documents. Frequent product line changes leading to document modifications require flexible model context configuration adjustments, to adapt to different batch-specific business data scales.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Covers the context length of multi-batch formula, production record, and other business documents, and supports full data reference for bid documents |
maxTokens | 2500 token | Controls the output scale of a single bid quotation or document, aligning with paragraph-level output requirements for industry documents |
quoteMaxToken | 1200–1800 token | Limits the length of business data references, ensuring complete and compliant display of content such as raw and auxiliary material qualification certificates and test records |
| Workflow/API tool selection | auto | Automatically triggers tool calls to meet the need for real-time queries of production data and shelf life information during the bidding process |
temperature | 0.4 | Balances the accuracy and flexibility of generated content, preventing deviations in critical information such as allergens and shelf life |
AIPROXY_API_TOKEN | Fill in the value assigned by the platform | Completes identity verification for model integration, ensuring call permissions comply with platform specifications |
Three Common Misconfigurations
- Symptom: An error stating unconfigured or untriggerable MCP function appears when calling the MCP feature in a workflow. Cause: Tool call permissions were not enabled during model integration, or the MCP plugin was not linked to the currently configured model.
- Symptom: After enabling voice recognition, the interface displays that the browser does not support voice input. Cause: The browser compatibility mode for voice recognition was not enabled in platform configuration, or the current browser version does not support the Web Speech API.
- Symptom: After reordering the model, the Q&A session returns a reorder result of false. Cause: The reordering model was not associated with the current knowledge base retrieval link, or the number of recalled knowledge base results does not meet the minimum input requirement for the reordering model.
How to Verify Successful Configuration
- Confirm that the deployed FastGPT version is v4.17.0, to avoid configuration failures caused by version discrepancies.
- Submit a test bid document template, check if generated content correctly references business fields such as formulas and shelf life, and verify that field units and values align with expected standards.
- Trigger a tool call test, verify that real-time production data from ERP/MES systems can be correctly retrieved, and confirm no errors exist in the call link.
- Adjust the
temperatureparameter and observe changes in generated content consistency, confirming that parameter adjustments have the expected impact on output.
The values provided above are common starting points, and should be evaluated against your own specific samples.