Data Profile for This Category
Typical entities in this category include liquid milk, yogurt, milk powder, and dairy ingredient enterprises. Daily generated documents include raw milk acceptance records, standardized ingredient lists, pasteurization or UHT heat treatment records, CIP cleaning records, filling records, reserved sample and microbial test reports. Data sources cover raw milk testing systems, MES production systems, homogenization and heat treatment equipment, online temperature and flow sensors, CIP systems, and LIMS laboratory information management systems. Data updates occur per milk tank, per batch, or in real time. Most documents are structured tables and time-series logs, with specific fields and corresponding units such as antibiotic indicators, temperature-time parameters, and batch numbers.
Constraints on Document Parsing and Chunking
The characteristics of dairy processing documents impose multiple constraints on the parsing and chunking process. First, high-frequency data updated in real time or per tank or batch requires chunking to retain batch association, and prevents splitting of records across multiple batches. Second, multi-source heterogeneous document types including structured test reports, equipment time-series logs, and work order records require adapting parsing rules for different formats. Third, fields include specific units (e.g., ℃ for heat treatment temperature, seconds for time). Parsing must retain the original field precision to avoid losing critical traceability information. Fourth, traceability timeliness requirements for perishable raw materials mean parsing and chunking processes must complete within a reasonable timeframe to avoid delaying problem troubleshooting.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field-dense structure of dairy processing documents, avoids splitting single test indicators or equipment logs |
chunkSplitter | Split by paragraph + batch label | Matches the update rhythm per milk tank or batch, ensures each chunk only corresponds to content from a single batch |
customPdfParse | Enable structured parsing | Adapts to the table formats of raw milk acceptance records and microbial test reports, fully extracts fields and unit information |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports bulk upload of large documents such as batch-wide CIP cleaning records and multi-tank raw milk test reports |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers the parsing time required for large heat treatment time-series logs, avoids mid-process timeout interruptions |
chunkSettingMode | Manual configuration | Adjusts chunking rules separately for different document types (equipment logs, test reports, work orders) |
Three Common Misconfigurations
- Uploading audio or video files results in parsing failure, with an unsupported file format prompt. The cause is that non-structured audio and video parsing is not enabled in the current configuration, and only text and table-based documents are supported.
- Calling the workflow API to upload images returns a parameter error. The cause is that the transfer format and path of image parameters were not configured per the official interface documentation, resulting in a non-compliant request body.
- Chunk results include records across multiple batches. The cause is that
chunkSplitteris not configured to split by batch labels, causing documents from adjacent batches to be merged into the same chunk, which affects subsequent traceability accuracy.
How to Verify Correct Configuration
- Upload a single raw milk acceptance record PDF, check that the parsed chunks retain complete fields and corresponding units for each test indicator.
- View the parsing log of the uploaded file, confirm that the duration set by
PARSE_FILE_TIMEOUT_SECONDScovers the actual parsing time of the file, with no timeout errors. - Call the FastGPT v4.17.0 workflow API to upload a test image, verify that the returned parsing result includes the image text content, and that parameter transfer meets the requirements of the official interface documentation.
- Bulk upload multiple CIP cleaning records, check that each chunk only corresponds to cleaning content from a single batch, with no mixed records across batches.
The values provided are common starting points and should be measured against the reader's own samples.