What the data for this category looks like
Core data sources for this category include animal quarantine information, supplier batch ledgers, production traceability records, cold chain temperature collection data, metal detection results, and laboratory microbial test reports. Daily generated documents include quarantine certificates, slaughter and cutting records, ingredient marination logs, thermal processing parameter records, cold chain temperature ledgers, and microbial test sheets. Data updates occur per production batch and per shift. Temperature control data is collected continuously. Most document fields include batch numbers, quarantine numbers, temperature values, test indicators and results. Some documents require association with biosecurity-related identifiers. Two primary formats are used: structured tables and semi-structured logs.
What constraints these characteristics impose on document parsing and chunking
Batch-associated data for this category requires that chunking retain contextual links between adjacent batches. Do not split cross-batch associated records, to prevent failure to establish connections between batches and corresponding quarantine or test information during Q&A. Continuously collected temperature control data uses time-series formatting. Chunking must avoid breaking the complete chain of temperature changes, to ensure full temperature control processes can be restored during subsequent Q&A. The coexistence of multiple document types requires the parsing workflow to adapt to fixed formats of quarantine certificates, semi-structured fields of test sheets, and table layouts of ledgers. Frequently updated data requires the parsing workflow to have low latency, to prevent real-time query demands for production links from being disrupted by parsing timeouts. Biosecurity-related identifiers must be accurately identified, to avoid parsing errors that lead to compliance risks.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | This category’s documents include long-form production records and time-series temperature control data. This range retains batch association context while avoiding overly fragmented chunks |
chunkSplitter | Split by paragraph and batch number delimiters | Documents include structured tables and semi-structured logs. Splitting by paragraphs preserves semantic integrity. Pairing with batch number delimiters prevents cross-batch chunking |
customPdfParse | Enabled | Quarantine certificates and test sheets for this category use fixed formats. Custom PDF parsing can accurately extract dedicated fields |
PARSE_FILE_TIMEOUT_SECONDS | 120–180 seconds | Parsing some large temperature control ledgers and batch test sheets requires extended time. This range covers most document parsing needs |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Archived files for batch production records in this category can reach large volumes. This setting allows complete uploads |
chunkSettingMode | Manual configuration | Adjustment of chunking parameters for different document types is required, to adapt to special needs of batch association and time-series data |
Three Common Configuration Mistakes
- Uploading non-standard documents with modified file extensions (such as renaming a Java interface file to TXT) results in no parsing output. Core documents for this category are fixed-format production ledgers and quarantine certificates. The parsing logic is not adapted for code-like documents. Modifying file extensions does not change the actual document structure, leading to parsing failure.
- Using chunk mode to call the pushdata API for uploads results in long-term display of "indexing". This occurs when
chunkSizeis set too large orPARSE_FILE_TIMEOUT_SECONDShas an insufficient value. This causes the parsing workflow to fail to complete within the expected time frame. - Temperature data and quarantine identifiers in uploaded PDF documents are not extracted. This happens when the
customPdfParseconfiguration is not enabled. The default PDF parsing cannot accurately recognize the dedicated field formats of documents for this category.
How to Verify Correct Configuration
- Upload a single typical document (such as a single-batch temperature control ledger). Verify the number of parsed chunks and their semantic integrity. Confirm that chunking has not broken batch associations or time-series data.
- Call the pushdata API to upload a test file. Check the update duration of the index status. Confirm that long-term unresponsive situations do not occur.
- After enabling
customPdfParse, upload a quarantine certificate sample. Verify that extracted fields include core information such as quarantine numbers and batch numbers. - Upload different types of documents (such as test sheets and temperature control records). Confirm that the format adaptability of parsing results meets business requirements.
The values provided are common starting points, and should be evaluated against the reader’s own samples.