What data for this category looks like
Dairy processing technical documents include raw milk acceptance records, standardized ingredient lists, pasteurization or UHT heat treatment records, CIP cleaning records, filling records, sample retention and microbial inspection reports, and more. Data sources include milk source testing systems, MES, homogenization and heat treatment equipment, online temperature and flow collection systems, CIP systems, and LIMS. Document update frequency is per milk tank, per batch, or real-time. Most documents are structured tables or reports with fixed fields, including raw milk physical and chemical and microbial indicators, process parameters, cleaning verification data, and more. Units match industrial metrology standards.
This explanation is based on FastGPT v4.17.0.
What constraints these characteristics impose on the document parsing and chunking step
Dairy processing documents are generated per batch or per milk tank. Chunking must avoid mixing content across batches, so documents must be split by batch. For documents with a high proportion of structured tables, parsing and chunking must retain original field alignment and table structure to avoid breaking the associated relationships of process parameters. Real-time updated documents require fast parsing responses, so reasonable timeout thresholds must be set to match the system update rhythm. In scenarios where multiple types of technical documents coexist, support is needed to adjust chunking rules for different document types, to adapt to documents of different formats such as raw milk acceptance records and CIP records.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the field density of single-batch technical documents, avoids splitting continuous sets of critical process parameters |
chunkSplitter | Split by fixed paragraphs + table blocks | Adapts to technical documents that are mostly tables or structured paragraphs, retains field integrity |
customPdfParse | Enable industrial report parsing mode | Adapts to standardized PDF reports exported from MES and LIMS, retains original table column alignment and field names |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates packaged uploads of multiple documents for a single batch’s full process, matches the usage habits of enterprise batch archiving |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Covers parsing time for large-volume batch documents, avoids timeouts triggered by too many single-tank records |
chunkSettingMode | Manual configuration | Allows adjusting chunking rules for different document types such as raw milk acceptance records and CIP records, adapting to multiple types of technical documents |
Three common misconfigurations
- Symptom: The interface shows file parsing stuck in a waiting state, or a timeout error is returned when calling the Q&A function. Cause: The
PARSE_FILE_TIMEOUT_SECONDSthreshold was not adjusted based on the volume of single-batch documents. Parsing time for large-volume CIP or filling records exceeds the default setting. - Symptom: Missing fields or misaligned table columns appear in the parsed document. Cause: The industrial report mode of
customPdfParsewas not enabled. General parsing cannot recognize the fixed field format of standardized industrial documents. - Symptom: Heat treatment time and temperature parameters from the same batch are split into two separate chunks. Cause: The
chunkSizesetting is too small, splitting continuous process parameter sets into multiple chunks, which affects context integrity during Q&A.
How to confirm configurations are correct
- Upload a single raw milk acceptance record PDF, check if the parsed text retains the complete table structure of milk tank number, inspection items, and corresponding results.
- Upload a single batch’s full process document package, verify that parsing time falls within the preset
PARSE_FILE_TIMEOUT_SECONDSrange, with no timeout prompts. - Adjust
chunkSizeto different ranges, compare the chunked results, and confirm that sets of process parameters are not split. - Test calling the technical Q&A function, enter process query questions for the corresponding batch, and check if the returned results include continuous relevant record chunks.
The values provided are common starting points and should be measured against the reader's own samples.