Document Parsing and Chunking for Water Treatment Research Knowledge Base Construction

Water treatment research data sources include real-time water quality monitoring station data, water plant operation logs, industry technical standard

What the data for this category looks like

Water treatment research data sources include real-time water quality monitoring station data, water plant operation logs, industry technical standard documents, patent literature, operation manuals, and project feasibility study reports. Update rhythms vary significantly: real-time monitoring data updates per minute, industry standards and patent literature iterate quarterly or annually, and project documents only update during project cycles. Document structures include structured tables, long technical descriptions, equipment operation records with parameters, and professional measurement items such as pH value, turbidity NTU, COD mg/L, and flow rate m³/h.

Multi-source heterogeneous document types and update rhythms require the parsing workflow to adapt to both short-cycle real-time logs and long-cycle large reports. Structured tables with unit-bearing values and identification fields must retain complete field association relationships to avoid losing business meaning after splitting. The presence of professional terms and complex charts requires parsers to have precise format recognition capabilities to prevent incorrect disassembly of professional content. High-frequency updated real-time data also requires the parsing workflow to support incremental processing, avoiding repeated parsing of historical data.

How to set the configurations

Configuration ItemRecommended SettingRationale
minerU_enableEnable via checkboxAdapt to parsing needs for complex tables, professional charts, and formulas in water treatment documents, replacing basic PDF parsing capabilities
parse_chunk_size800–1200 charactersWater treatment documents include long technical descriptions and numerical tables with units. This range balances context completeness and retrieval accuracy
parse_overlap_ratio10%–15%Prevent loss of logical connections between adjacent sections when long technical paragraphs are split, adapting to the continuous recording characteristics of operation logs
PARSE_TABLE_VECTORIZEEnableWater treatment documents require water quality indicator and chemical dosage tables to retain field and unit associations, avoiding table content being scattered into meaningless text
PARSE_FILE_TIMEOUT_SECONDS600 secondsComplete reports for large water treatment projects may include multi-page charts and data. This duration covers the full parsing process
UPLOAD_FILE_MAX_SIZE2000 MBAdapt to batch uploads of historical monitoring data sets and large project documents

The parameter values provided on this page are conventional recommendations used to determine the starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.

Three common configuration mistakes

  • Enabling minerU_enable via the interface causes parsing failure and returns a 504 timeout status code. Cause: The locally deployed minerU container does not expose the corresponding port, or FastGPT does not configure the minerU API access address.
  • Water quality indicator table fields are empty in the parsed document. Cause: The PARSE_TABLE_VECTORIZE configuration is not enabled, and the basic parser scatters table content into fragmented text.
  • Duplicate long paragraphs appear in post-chunking search results. Cause: parse_overlap_ratio is set too high, leading to excessive overlap between adjacent chunks and generating redundant search results.

How to confirm correct configuration

  • Execute a curl command to access the local minerU API port and confirm that a normal response is returned.
  • Upload a PDF test document containing a water quality table and verify that the parsed result retains complete field and unit information.
  • Check the logs of the knowledge base parsing task to confirm that parsing time does not exceed the configured PARSE_FILE_TIMEOUT_SECONDS threshold.
  • Search for professional terms in the test document and confirm that chunked content can be accurately recalled without obvious logical breaks.

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.