What data for this category looks like
Data sources for aquaculture profit yield related information include scaled aquaculture IoT terminals, regional aquatic product wholesale market public quote APIs, and aquaculture entities' bookkeeping systems. Data update rhythms fall into two categories: real-time water quality monitoring and feeding records update every 15 minutes to 1 hour. Daily costs and purchase price quotes update daily in the early morning. Document structures primarily use structured CSV and Excel files, supplemented by JSON logs uploaded from IoT devices. Core fields include pond ID, aquaculture species, feeding volume, dissolved oxygen concentration, seedling cost, purchase unit price, and more. Units include kilograms, milligrams per liter, yuan, and others.
What constraints these characteristics impose on deployment and upgrade
Multi-source heterogeneous data sources require adapting to different access protocols during deployment, and compatibility with new IoT device data formats during upgrades. Mixed real-time and daily update rhythms require configuring layered scheduled tasks to avoid resource conflicts or data delays caused by unified scheduling. Structured data with multiple fields requires completing field mapping verification in advance during deployment, and updating field association rules synchronously when new aquaculture species are added during upgrades. Large-capacity bulk aquaculture data files require adjusting resource configurations for storage and parsing to avoid timeouts or storage overflow.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates upload requirements for aquaculture monthly feeding records, bulk market reports, and similar files, to avoid large file transfer failures |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Reserves sufficient parsing time when processing structured aquaculture data files with multiple fields, to avoid premature parsing termination |
CHUNK_SIZE | 600–1000 characters | Adapts to text lengths of aquatic market data and water quality monitoring logs, balancing context coherence and recall accuracy |
SIMILARITY_THRESHOLD | 0.75–0.85 | Distinguishes market and cost data for different aquaculture species, filtering low-correlation recall results |
RECALL_TOP_N | Top 8–12 entries | Covers association requirements for multi-source aquaculture data, avoiding missing key fields for profit yield calculation due to insufficient recall entries |
OCR_ENABLED | Enabled | Processes scanned copies of paper aquaculture records to extract structured fields such as feeding volume and purchase price |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on internal samples before finalizing settings.
Three Common Configuration Mistakes
- Issue: Local deployment of version 4.8.12 fails to correctly parse profit yield calculation formulas, returning abnormal results. Cause: The formula parsing module in this version does not support multi-dimensional cost association formulas unique to aquaculture. Upgrading to version 4.9.0 or later resolves this issue.
- Issue: Calls using third-party API keys return a
401 Unauthorizederror, while calls using local models return amodel not founderror. Cause: API key permission scope is not configured correctly, or the specified local model was not pulled in advance. Corresponding model services must be started after pulling the image. - Issue: After deploying the marker tool, logs show
ocr errorand text content from paper aquaculture records cannot be extracted. Cause: Required OCR engine dependencies are not installed, or scanned copies have insufficient clarity leading to recognition failure.
How to Confirm Proper Configuration
- Upload a test structured aquaculture data file, verify that extracted fields after parsing cover core items such as aquaculture species, feeding volume, and purchase price, with no field mapping errors.
- Trigger a profit yield calculation task, verify that the returned result includes complete associated calculation logic, with no syntax or missing field prompts.
- Test cross-source data association, confirm that real-time water quality data and daily market data can be correctly pulled and used for calculations.
- Review system operation logs, confirm no error prompts appear during file upload, parsing, and model invocation 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.