What This Category of Data Looks Like
Data for this category primarily comes from code repositories, community forums, contribution statistics, and governance meeting minutes. Common processed documents include contribution guidelines, code of conduct, maintainer lists, and governance meeting minutes. Data is updated monthly or quarterly. Individual document sizes range from hundreds to tens of thousands of characters. Fields include role permission entries, rule clauses, contributor qualification records, and meeting resolution content. No unified fixed format exists. Some documents use mixed layouts with multiple paragraphs, multi-column tables, or embedded images.
Constraints on Document Parsing and Chunking
Data for this category comes from scattered sources and has diverse formats, including Markdown documents from code repositories, rich-text posts from community forums, structured contribution statistics tables, and non-standardized meeting minutes. This places requirements on the format adaptation capabilities of the parsing module. Document update frequency is low, but consistency of historical data must be maintained. When chunking, avoid destroying the integrity of core semantic units such as governance rules and role permissions. Some documents use mixed layouts with multi-column tables and embedded images. If chunking logic does not adapt to this structure, critical information may be split incorrectly. Data errors can lead to governance disputes, so chunking must retain contextual connections to prevent core clauses from being split apart.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of core semantic units such as rule clauses and permission entries in governance documents, avoiding splitting critical information |
chunkSplitter | Split by paragraph + heading | Matches the layout of most community documents, which are structured rules and meeting minutes, and retains contextual connections |
customPdfParse | Enable image text extraction mode | Adapts to scenarios where embedded images appear in some meeting minutes or public documents, fully extracting text content from images. Compatible with FastGPT v4.17.0 parsing logic |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Matches the size of monthly updated documents, avoiding parsing timeouts for large meeting minutes |
UPLOAD_FILE_MAX_SIZE | 100 MB | Limits the maximum size of a single uploaded document to prevent excessive resource usage |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types such as maintainer lists and contribution guidelines to ensure semantic integrity |
Three Common Misconfigurations
- Misaligned column data or lost merged cell content appears in parsed multi-column contribution statistics tables or maintainer lists. The cause is that the default chunking logic does not adapt to multi-column layouts, and table structured parsing configuration is not enabled.
- Text from embedded images is not extracted when uploading a governance meeting minute PDF, and only plain text is included in the output. The cause is that the image text extraction switch for
customPdfParseis not enabled. - Timeout errors occur when parsing large quarterly governance meeting minutes. The cause is that the
PARSE_FILE_TIMEOUT_SECONDSconfiguration value is less than the actual time required for document parsing.
How to Verify Correct Configuration
A maintainer list document containing a multi-column table may be uploaded. The column alignment of the parsed table is checked to confirm that chunking did not split column data. A governance meeting minute PDF with embedded images may be uploaded. The output content is checked to confirm whether it includes text from the images, verifying that the customPdfParse configuration is active. A large quarterly meeting minute document may be uploaded. The parsing process is checked to confirm no timeouts occur, verifying that the PARSE_FILE_TIMEOUT_SECONDS configuration is reasonable. A contribution guideline document may be uploaded. The chunked content is checked to confirm retention of complete rule clauses, verifying that the manual chunkSettingMode configuration adapts to the document type.
The values listed above are common starting points, and should be evaluated against the specific samples being used.
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.