What Data Looks Like for This Category
Data for this category typically originates from crowdsourcing platforms, annotation quality databases, annotator training and exam records, and financial settlement systems. Commonly processed documents include personnel access rules, standardized training materials, monthly performance reports, and settlement statements. Data updates follow daily or monthly cycles. Most documents include fixed fields such as personnel identifiers, qualification status, assessment scores, and settlement amounts. No unified cross-project format specification exists.
Constraints Imposed on Document Parsing and Chunking
Document sources are scattered, and formats are inconsistent. Parsing workflows must adapt to multiple types of non-standard tables and text paragraphs. Daily updated performance and settlement data have strict timeliness requirements. Parsing timeout durations must be controlled to avoid delaying settlement processes. Fields vary widely across different document types. Chunking must avoid splicing content across fields to prevent semantic confusion, which disrupts subsequent compliance reviews. Training materials often combine text and images. Extraction of both text and embedded compliance information must be supported. Chunking must also avoid breaking the logical continuity of training steps.
How to Configure Settings
This guide is written for FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the single-paragraph field length of performance reports and settlement statements, avoids splitting cross-field content |
chunkSplitter | Split by paragraph + title | Matches the structured hierarchy of training materials and access rules, preserves document logical structure |
customPdfParse | Enabled | Adapts to multiple types of PDF training materials and settlement documents, preserves original layout and embedded content |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Meets parsing timeliness requirements for daily batch data, avoids interrupting batch processing workflows due to timeouts |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to monthly performance summary and settlement files imported in batches |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types, adapts to format differences between access rules and settlement statements |
Three Common Configuration Mistakes
- Parsing calls fail when processing specific service-related documents, with only some services parsing successfully. The root cause is failure to configure the
customPdfParseparameter for the special format of this document type, which prevents recognition of non-standard tags. - After importing training materials containing images, question-and-answer testing cannot generate responses related to images. The root cause is failure to enable the supporting image parsing module, and failure to retain context associations for image links during chunking.
- Some fields appear empty when importing settlement statements in batches. The root cause is that
chunkSizeis set too small, splitting complete field combinations within table rows and resulting in lost field information.
How to Verify Configurations Are Correct
- Upload a single personnel access rule PDF. Confirm that parsed chunks retain the hierarchical relationship between titles and paragraphs, with no random splitting.
- Upload a batch of performance report files. Confirm that parsing time does not exceed the preset
PARSE_FILE_TIMEOUT_SECONDSthreshold, with no timeout errors. - Import training materials containing images. Verify that parsed results include image link fields, and that associated context is complete.
- Upload a test settlement statement. Check that all preset fields are fully extracted, with no omissions or breaks.
The values listed here are common starting points, and should be evaluated 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.