What the data for this category looks like
This category of data mainly comes from the ecological environment law enforcement system, online monitoring platforms, automatic pollution source monitoring data, and reports submitted by third-party testing institutions. Commonly processed documents include on-site inspection records, sampling records, monitoring reports, order for rectification decisions, and administrative penalty decisions. The data update frequency is daily. Most document structures contain fixed law enforcement process fields. For example, on-site inspection records mark inspection points and equipment operating conditions. Monitoring reports specify sampling points, pollutant concentrations, and judgment standards. Some documents use standardized law enforcement document formats.
What constraints do these characteristics impose on the document parsing and chunking link
Batch law enforcement and monitoring documents updated daily require parsing and chunking to support batch processing with controllable time consumption. Fixed fields and standardized document formats require chunking to retain the contextual association of law enforcement processes, avoiding splitting that breaks the complete chain of law enforcement evidence. Format differences between third-party testing reports and online monitoring data require the parsing module to adapt to multiple types of document structures, while accurately extracting key numerical fields such as concentrations and judgment results. The seriousness of law enforcement documents requires that core information such as penalty basis and rectification requirements not be lost in chunked content. Losing this information will affect the use of evidence in subsequent office links.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapt to the paragraph length of law enforcement documents and monitoring reports, avoid splitting that breaks the contextual association of law enforcement processes |
chunkSplitter | Split by paragraph + heading | Match the standardized format of documents, retain the chapter structure of on-site inspection records and monitoring reports |
customPdfParse | Enabled | Adapt to the complex typesetting of third-party testing reports, accurately extract tables and numerical fields |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Address the time consumption requirements of batch document parsing, avoid timeout interruptions of law enforcement data processing |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different types of documents, such as on-site records and penalty decisions, to adapt to differentiated content structures |
Three common errors
- Symptom: The marker parsing module returns split-related error logs, and the document parsing status is abnormal. Cause: The
chunkSplitterparameter is not configured correctly, or the chunk size is set beyond the compatible range of the module, causing the splitting logic to fail to match the document structure. - Symptom: In the docker-deployed FastGPT v4.17.0 version, after uploading a file, the parsing result is empty, and no corresponding text chunks are generated. Cause: The
customPdfParseconfiguration is not enabled, or the file parsing module is not correctly mounted, resulting in failure to extract content from PDF-format law enforcement documents and monitoring reports. - Symptom: Calling the parsing interface takes too long, exceeding the business processing time limit. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set too short, or the number of batch-uploaded documents exceeds the processing capacity of the current deployment resources, resulting in timeout interruption of the parsing task.
How to confirm the configuration is correct
- Upload a standard on-site inspection record document, check whether the parsed text chunks retain core fields such as inspection points and working condition descriptions, with no content missing.
- View the logs of the parsing module, confirm that no split-related errors occur, and the file parsing process is completed normally.
- Adjust the
chunkSizeparameter, compare the chunking results under different values, and confirm that the chunk length matches the actual length of the document paragraphs. - Test batch uploading multiple monitoring reports, confirm that the parsing task does not have timeout exceptions, and meets the time requirements of business processing.
The values given are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.