What the data for this category looks like
Data sources for aquaculture intelligent due diligence include real-time readings from pond water quality monitoring equipment, daily feed feeding records, seedling purchase vouchers, disease diagnosis photos, slaughter inspection reports, and satellite remote sensing pond images. Update frequencies vary significantly: water quality data updates hourly, feeding records are archived daily, and seedling and slaughter data are updated per breeding batch. Document formats include structured CSV/Excel spreadsheets, official PDF inspection reports, and JPG/PNG format on-site diagnosis photos. Fields include dissolved oxygen (unit: mg/L), pH value (dimensionless), feeding amount (unit: kg/mu), pond ID, breeding variety, and others. No unified fixed format template exists.
What constraints do these characteristics impose on workflow orchestration?
Multi-source heterogeneous data features require workflows to be configured with multi-format parsing nodes that support structured spreadsheets and unstructured image files. Data with different update frequencies require two trigger logics: scheduled nodes pull water quality data hourly and slaughter reports per batch, while also supporting manual triggering for temporary document supplements. Specific field units and value ranges require workflows to embed parameter verification links to prevent invalid negative dissolved oxygen values and non-standard unit feeding amounts from entering the process. Full-cycle due diligence requirements require knowledge base recall nodes to filter by pond ID and breeding cycle range, ensuring recalled data is strongly associated with the due diligence target.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_SUPPORTED_TYPES | csv,xlsx,pdf,jpg,png | Covers file formats required for aquaculture due diligence, including structured spreadsheets, inspection reports, and diagnosis photos |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Prevents parsing timeouts when processing files with multi-page inspection reports or high-resolution aquaculture photos |
Recall Count | Top 8–12 entries | Balances information completeness and redundancy of due diligence reports, adapting to the recall needs of multi-dimensional aquaculture monitoring data |
Similarity Threshold | 0.75–0.85 | Filters low-correlation historical breeding data, ensuring recalled pond monitoring records match the due diligence topic |
UPLOAD_FILE_MAX_SIZE | 500 MB | Accommodates large-volume files such as batch aquaculture monitoring logs and satellite remote sensing images |
Export Format | docx | Adapts to the commonly used delivery format for industry due diligence reports |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Symptom: After configuring dynamic knowledge base parameters, the AI response does not associate documents from the corresponding pond. Cause: The recall range is not filtered by the
pond IDfield in the knowledge base recall node, resulting in the recall of breeding data from irrelevant ponds. - Symptom: No download link is generated after the workflow completes execution. Cause: No export node is added at the end of the workflow and the download switch is not enabled, or
docxis not specified as the export format. - Symptom: Workflow nodes migrated in version 4.8 fail to run normally. Cause: The original workflow's knowledge base filtering parameter configuration is not retained, and the new version's node trigger logic is not adapted.
How to confirm proper configuration
- Upload a structured spreadsheet file for aquaculture, check whether the parsing node correctly extracts preset fields such as dissolved oxygen and feeding amount.
- Configure the pond ID as a filtering parameter to trigger the workflow, check whether the recalled documents from the knowledge base only include records from the corresponding pond.
- Trigger the workflow to the export stage, confirm that an accessible download link is generated.
- View the workflow execution logs, confirm that there are no timeout or error records in the parsing, recall, and export stages.
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.