What the data for this category looks like
Aquaculture due diligence data primarily comes from pond monitoring logs, feed purchase ledgers, aquatic product quarantine reports, acquisition settlement statements, and similar records from aquaculture enterprises. Monitoring data is updated daily in CSV or Excel format, containing fields such as pond number, breeding cycle, water temperature, dissolved oxygen, feeding dosage, and others. Quarantine reports are mostly Word documents with embedded tables, recording batch disease conditions and medication records. Field units have clear industry-specific characteristics: water temperature is measured in ℃, dissolved oxygen in mg/L, feeding dosage in kg/mu, and some ledgers also include statistical items such as the number of aquatic organisms and total weight.
What constraints do these characteristics impose on the document parsing and chunking link
The multi-source heterogeneous nature of aquaculture due diligence data requires parsing tools to adapt to multiple formats including Excel tables, Word embedded tables, and plain text logs. Single due diligence documents may contain Excel ledgers with over 15,000 rows or Word reports with 100,000 Chinese characters. Fixed character count chunking easily breaks business relevance. Industry-specific field and unit binding relationships require the parsing process to retain the association between values and their corresponding units, to avoid information distortion after splitting. Batch pond or batch data also requires chunking to aggregate by business unit, rather than splitting solely by row or paragraph. Otherwise, business logic will break during subsequent RAG matching.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_EXCEL_TABLE_MODE | Split by business unit | Most aquaculture Excel files have a single header and multiple business rows. Splitting by pond or batch preserves field relevance and avoids fragmented single chunks |
maxChunkSize | 800–1200 characters | Aquaculture data has many fields with units. A single chunk that is too large may exceed model context limits, while one that is too small breaks business logic associations |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single due diligence documents may include multiple breeding ledgers. A 2000 MB maximum size supports bulk file upload requirements |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Parsing 15,000-row Excel files or 100,000-character Word reports takes significant time. 1200 seconds prevents mid-process timeout interruptions |
CHUNK_OVERLAP_RATE | 15–20% | Aquaculture data has strong field relevance. Overlapping portions ensure cross-chunk business information is not lost |
ENABLE_UNIT_AWARE_PARSING | Enabled | Aquaculture data includes many fields with units. Enabling this retains the binding relationship between fields and units |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- When uploading a 15,000-row aquaculture Excel file, the large language model returns "It appears that an incomplete command or request may have been entered". The cause is failure to adjust the
maxChunkSizeparameter. Single chunk data exceeds model context limits, resulting in parsed chunks that cannot trigger normal question answering. - Parsed chunks only display field values without corresponding units. For example, "dissolved oxygen" only shows "5.2" instead of "5.2 mg/L". The cause is failure to enable the
ENABLE_UNIT_AWARE_PARSINGconfiguration, so the binding relationship between fields and units was not retained. - When uploading a 100,000-character aquaculture due diligence Word document, the task shows a timeout failure. The cause is failure to increase the
PARSE_FILE_TIMEOUT_SECONDSparameter. The default timeout duration is insufficient to complete long document parsing.
How to confirm configurations are properly set
- Upload a single aquaculture ledger Excel file with over 10,000 rows, view the parsed chunk list, and confirm that each chunk contains complete single pond or single batch business data, rather than scattered row data.
- Randomly select chunk content, verify the binding relationship between fields and units, and confirm that values and their corresponding units appear in a single chunk.
- Upload a single 100,000-character aquaculture due diligence Word document, check the task status, and confirm that parsing completes without timeout errors.
- Initiate a classification matching task based on the parsed document, verify that the matching accuracy of returned results meets business expectations, and adjust relevant parameters until requirements are met.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.