What the data for this category looks like
Data sources for aquaculture investment research include on-site monitoring logs from farmers, market briefings released by industry associations, aquaculture experiment reports from research institutes, aquatic product price data from e-commerce platforms, and publicly available aquaculture technical documents. Update frequencies cover real-time water quality monitoring data, daily feeding records, monthly stockout and price reports, and annual industry development analyses. Document types include structured tabular reports, plain-text farming logs, and case documents with disease diagnosis images. Fields involved include dissolved oxygen, water temperature, feeding amount, stocking density, and others. Units include mg/L, ℃, kg, mu, cubic meters, and others.
What constraints these characteristics impose on the "document parsing and chunking" link
Mixed document types require parsing logic that adapts to structured tables, plain text, and content with images. This avoids information loss caused by a single parsing mode. Frequently updated short documents and infrequently updated long documents coexist. This requires flexible adjustment of chunk granularity: chunks that are too long lead to retrieval redundancy, while chunks that are too small break the coherence of professional terminology. Case documents with disease diagnosis images require the parsing link to support image OCR extraction. Without this, the large language model cannot access the lesion description information in the images. Scenarios with mixed imports of public web pages and PDF documents require configuring allowed data source domains. This prevents unauthorized links from being parsed.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_MODE | auto | Covers mixed document types including structured reports, text logs, and image-containing case documents, automatically adapts parsing logic for different document types |
CHUNK_SIZE | 800–1200 characters | Balances contextual coherence for short aquaculture monitoring records and long technical passages, adapts to conventional retrieval needs |
IMAGE_OCR_ENABLE | true | Disease diagnosis cases account for a high proportion of aquaculture documents, requires extracting text from images for use by the large language model |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large aquaculture research reports require longer processing time to avoid interrupting the parsing process due to timeout |
ALLOWED_URL_DOMAINS | *.yuque.com, *.agri.gov.cn | Allows parsing of public industry reports and Yuque aquaculture record links, filters unauthorized data sources |
TABLE_EXTRACT_MODE | keep_structure | Retains the table structure of aquaculture reports, prevents structured values and units such as dissolved oxygen and feeding amount from being separated |
The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Issue: After uploading an aquaculture disease diagnosis PDF, the parsing result does not include the lesion description text from the image. Cause: The
IMAGE_OCR_ENABLEconfiguration is not enabled, or the configuration item is set tofalse, so image OCR extraction is not triggered. - Issue: After importing a publicly shared Yuque aquaculture record link, the system prompts "unable to parse this URL" or returns a 403 error. Cause: The
yuque.comdomain is not added to theALLOWED_URL_DOMAINSconfiguration list, or the link is not set to publicly accessible permissions. - Issue: After parsing an aquaculture feeding report, the dissolved oxygen value and mg/L unit are displayed separately in the chunked content. Cause: The
keep_structuresetting forTABLE_EXTRACT_MODEis not enabled, causing the table structure to be broken down into plain text.
How to Confirm the Configuration Is Correct
- Upload a PDF document containing structured aquaculture reports, check whether the parsing result retains the row and column structure of the table and the corresponding numerical units.
- Upload an aquaculture technical document with disease diagnosis images, confirm that the parsing result includes the OCR-extracted text from the images.
- Import a Yuque link that has been set to publicly shared permissions, confirm that the system does not throw parsing errors and successfully pulls the document content.
- Select a long aquaculture log document, test the chunking effect under different
CHUNK_SIZEconfigurations, and select the value range that fits the business retrieval logic.
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.