What the data for this category looks like
Typical entities in dairy processing are liquid milk, yogurt, milk powder, and dairy ingredient manufacturers. Daily associated documents include raw milk acceptance records, standardized ingredient lists, pasteurization or UHT heat treatment records, CIP cleaning records, filling records, and reserved samples and microbial inspection reports. Data sources cover raw milk testing systems, MES manufacturing execution systems, homogenization and heat treatment equipment, online temperature and flow collection systems, CIP cleaning systems, and LIMS laboratory information management systems. Data synchronizes in real time for each milk tank and batch. Single-batch data includes raw milk antibiotic and physicochemical indicators, heat treatment time and temperature, aseptic filling parameters, and cleaning verification results. Full-link association is completed using batch ID.
What constraints these characteristics create for source citation and traceability
Real-time batch-level data updates for this category require traceability to match batch IDs exactly. Cross-batch confusion must be avoided. Data from multiple systems must be linked and integrated via batch IDs. Without this, complete audit basis cannot be formed. Errors in core audit links have serious consequences. Cited traceability data must accurately correspond to the current batch. Unrelated data must not be included. Liquid biological raw materials are perishable. Traceability response speed must match production rhythm. Excessive delays are unacceptable. Single-batch data volume is large. The scope of cited content must be controlled reasonably. Information overload that interferes with audit judgments must be avoided.
Configuration Settings
This configuration guide is written for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 8000–12000 token | Matches the average character volume of full-link documents for single-batch dairy processing, ensuring key data such as raw milk testing and heat treatment parameters is fully retained |
responseData | Enable association of three data source types: raw milk acceptance, heat treatment, and CIP cleaning | Covers core traceability scenarios for supplier audits and process quality control, ensuring cited data covers all production links |
detail | Recall the top 3 high-match batch-level documents | Focuses on valid data for the current milk tank or batch, avoiding redundant information interfering with auditor judgments |
Three common configuration errors
- Empty detection field errors occur. The cause is that the
quoteMaxTokenvalue is set too low, truncating key raw milk physicochemical or microbial test data in single-batch documents. - The number of context items viewed on the page does not match the number of items actually recalled and sent to the calling interface. The cause is that cross-system data sources are not linked via batch IDs, only documents from some systems are recalled, and full-link data is not covered.
- Generated audit reports include traceability data from non-current milk tank batches. The cause is that the batch matching rule for
detailis not configured, and document content from unrelated batches is recalled.
How to verify correct configuration
- Retrieve full-link documents for a single batch, count the total character volume, and confirm that the
quoteMaxTokenvalue covers the complete data without truncation. - Check the returned associated data source list, and confirm that it includes the three core document types: raw milk acceptance, heat treatment, and CIP cleaning.
- Verify the batch IDs of recalled documents, and confirm that they exactly match the current milk tank or production batch being audited.
- Initiate a raw milk acceptance audit request, view the returned cited content, and confirm that it only includes valid data for the current batch.
The values provided are common starting points and should be measured against the reader's own samples.