What Data for This Category Looks Like
Data for this category primarily comes from client-delivered corpora, annotation results produced by internal annotation platforms, supporting vocabularies, and feedback results from quality inspection sampling. Daily processed documents include annotation specification manuals, bulk sample packages, quality inspection reports, and issue feedback forms. Data updates follow daily batches or single annotation task cycles. Most document structures are structured tables, segmented explanatory text, and labeled corpus fragments. Fields include annotation content, tag type, quality inspection result, feedback remarks, and more. There are no unified fixed units; field units adjust flexibly based on the annotation task type.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Stage
The data characteristics of this category impose multiple constraints on the document parsing and chunking stage. Diverse document sources and formats require the parsing module to support multiple text types including annotation specifications, sample packages, and quality inspection reports, to avoid losing tag fields or structured information due to format adaptation issues. The high-frequency daily or single-task update cycle requires the parsing process to have batch processing capabilities, to meet the rapid delivery needs of single-task batches. The mixed document structure of structured tables and segmented explanatory text requires the chunking strategy to retain semantic boundaries, avoiding splitting cross-page annotation rules or cross-paragraph sample explanations. Additionally, the pre-requisite requirement for compliance review requires the parsing stage to extract sensitive field metadata simultaneously, to facilitate subsequent compliance verification.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Aligns with the semantic unit length of annotation text, avoiding splitting individual tag explanations or sample fragments |
chunkSplitter | Split by paragraph + heading | Matches the structured hierarchy of annotation documents, retaining full context of annotation rules |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Adapts to the parsing duration of bulk sample packages, avoiding timeout interruptions due to large task volumes |
customPdfParse | Enabled | Targets the PDF format of annotation specifications, retaining original text layout and tag positions to avoid parsing distortion |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Meets the upload requirements of bulk sample packages, supporting complete import of large-volume single-batch tasks |
chunkSettingMode | Manual configuration | Flexibly adjusts chunking parameters for different annotation task document structures, meeting the metadata extraction needs of compliance review |
Three Common Mistakes
- Symptom: An out-of-memory error is prompted when deploying
customPdfParse, and the parsing service cannot start. Cause: GPU memory allocation parameters were not adjusted for the batch processing needs of annotation documents, leading to single-batch parsing resource usage exceeding hardware limits. - Symptom: After importing a Word-format sample package, domain information associated with images is lost, and no image metadata appears in the chunking results. Cause: Parsing rules adapted to Word documents were not configured; the default parsing process only extracts plain text content and does not retain external resource association information.
- Symptom: Other devices on the local area network cannot access the login page of the parsing service, returning an ERR_INCOMPLETE error. Cause: The service listening address was not configured as 0.0.0.0, only allowing local loopback access, preventing devices on the local area network from connecting.
How to Confirm Proper Configuration
- Upload a single annotation specification PDF document, check if the parsed text retains the original heading hierarchy and segmented structure, to verify the configuration effect of
chunkSplitter. - Upload a bulk sample package, check if the completion duration of the parsing task falls within the range set by
PARSE_FILE_TIMEOUT_SECONDS, with no timeout errors. - Check if the service listening address is configured as 0.0.0.0, try accessing the parsing service page from another device on the local area network, and confirm normal loading.
- Review the metadata fields of the chunking results, confirm that key information such as annotation tags and quality inspection results is included, to verify that the
chunkSizesplitting logic does not damage semantic integrity.
The values provided 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 2026-10-19.