What Data for This Category Looks Like
Typical entities include bread, pastry, cookie, instant noodle, and frozen pastry factories. Daily documents include formula and feeding lists, production records, baking or steaming curves, metal detection records, cleaning and disinfection records, and factory inspection reports. Product line changes happen frequently, so document update frequency is every batch, shift, or daily. Data sources cover raw and auxiliary material qualification certificates, ERP/MES systems, weighing systems, oven or frying line equipment, laboratory test results, and food traceability ledgers. Document fields include core verification items such as allergen material labels, production batch numbers, baking/steaming parameters, and shelf life.
Constraints Imposed by These Characteristics on Source Citation and Traceability
Data for this category updates every batch, shift, or daily, and is tied to production batch numbers. Traceability links must support real-time matching of documents for the corresponding batch. This prevents formula or parameter errors from cross-batch citations. There are diverse document types with sensitive verification fields like allergen labels and baking parameters. Traceability must accurately filter core parameters while supporting parsing of multi-format documents. Products are directly sold to consumers, so traceability accuracy directly relates to food safety risks. Source citations must be complete and traceable, with no missing key test or production records. This category also has prominent requirements for allergens and cleaning switching. Traceability must link corresponding cleaning and disinfection records and material usage to avoid cross-contamination risks.
Configuration Settings
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Matches the average content length of a single process document for this category, to avoid truncating core parameters |
responseData | Enabled | Supports outputting cited original knowledge base snippets in the answer body |
detail | Enabled | Displays specific document fields and batch information for cited sources |
| Single Recall Limit | Top 5 entries | Meets retrieval needs for multi-batch documents of this category, to avoid redundant information interfering with answers |
| Batch Association Switch | Enabled | Binds production batch numbers to accurately match corresponding process and inspection records |
| Encoding Parsing Rule | Configured as UTF-8 | Adapts to upload requirements for .csv format feeding lists and test records for this category |
Three Common Configuration Mistakes
- Phenomenon: Garbled characters appear in cited fragments in answers, or cited source fields are empty. Cause: No correct encoding parsing rule configured for .csv format feeding lists and test records of this category, or no encoding format specified during upload.
- Phenomenon: Cited content is too long, causing messy answer formatting and poor visual effect. Cause: The
quoteMaxTokenparameter is not set, or the value falls outside the reasonable range. - Phenomenon: Retrieved citations are not tied to the corresponding production batch, making it impossible to trace specific production links. Cause: The batch association matching configuration is not enabled, or filter fields do not include batch information.
How to Verify Correct Configuration
- Upload a .csv format feeding list for this category. Submit a question involving allergen materials. Check that the answer includes the correct cited fragment with no garbled characters.
- Submit a question involving baking parameters. Check that the token count of the cited content matches the preset
quoteMaxTokenrange. - Submit a question tied to a production batch. Check that the cited source displays the corresponding batch number and production record fields.
- View the
responseDatafield returned by the system. Confirm that it contains complete cited source information.
The values provided are common starting points and should be measured against the reader's own samples.