What Data for This Category Looks Like
The core documents for this category are version release notes, change logs, version tags, and release checklists. Data is sourced from Git repository tags, merged commit records, CI build artifacts, and Issue milestones. Updates align with software version releases, typically once per version. Document structures usually include fields such as version number, change category, associated change entries, and artifact verification information. Some documents include breaking change descriptions and rollback steps. Supported formats include plain text, Markdown, tables, and other formats.
What Constraints These Characteristics Impose on Document Parsing and Chunking
Data sources are scattered, and formats are inconsistent. Parsing processes must support multiple document formats to prevent loss of change entries due to format differences. The update rhythm aligned with version releases requires parsing tasks to have lightweight execution capabilities, to match fast release cycles. Documents contain high-risk content such as breaking changes and rollback steps. Chunking must keep key information intact without splitting it. Associated change entries must be grouped into logical units to avoid information fragmentation during compliance reviews. Some documents include structured fields such as verification hashes and PR numbers. Chunking rules must balance proper division of structured content and unstructured descriptions.
How to Configure
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the average length of change entries and version descriptions, prevents single chunks from being overloaded or too fragmented |
chunkSplitter | Split by paragraph + semantic meaning | Adapts to structured entries in change logs, preserves complete logic of change descriptions |
customPdfParse | Enabled | Compatible with PDF format change documents exported from CI artifacts, preserves original layout and table structures |
PARSE_FILE_TIMEOUT_SECONDS | 120–180 seconds | Adapts to parsing duration for batch version documents, prevents timeouts caused by overly long single tasks |
chunkSettingMode | Manual configuration | Adjusts chunking rules for the fixed structure of version documents, meets requirements for retaining key fields in security and compliance reviews |
Three Common Misconfigurations
- Symptom: After importing Markdown format change logs, chunking results show breaking change descriptions split across paragraphs. Cause:
chunkSplitteris not configured to split by semantic meaning. The default character-based splitting causes critical risk information to be split. - Symptom: Timeout errors triggered by
PARSE_FILE_TIMEOUT_SECONDSoccur when batch parsing multiple versions of Release Notes. Cause: The timeout parameter is not adjusted. The default duration for general small-file parsing is used, which cannot match batch large-volume version documents. - Symptom: After importing Excel format release checklists, structured table content is split into scattered character chunks. Cause: Corresponding format parsing rules are not configured, leading to failure to correctly identify table structures.
How to Verify Configurations Are Correct
- Upload a single version change log. Using the FastGPT v4.17.0 interface, check if chunking results retain complete breaking change description paragraphs, with no cross-paragraph splits.
- Batch upload 3 to 5 versions of Release Notes. Wait for parsing to complete, then check task logs to confirm no timeout errors occur.
- Import an Excel format release checklist. Confirm that parsed content retains the original table row and column structures, with no scattered character stacking.
- Adjust the
chunkSizeparameter, then re-upload the test document. Compare changes in chunk length to confirm the configuration takes effect.
The values provided 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.