What data for this category looks like
Data for this category primarily comes from ticketing systems, customer interview records, CRM customer profiles, and product roadmap documents. The update cadence is weekly or per version release. Daily processed documents include requirement pool lists, requirement assessment forms, customer feedback summaries, and version planning notes. Common fields include customer identifiers, requirement priority, compliance check markers, and version association numbers. Most documents use mixed structures with nested tables and paragraphs, and some customer feedback is submitted as unstructured text or screenshots.
What constraints do these characteristics impose on the document parsing and chunking link
Since data sources are scattered and formats vary, documents mixing tables and paragraphs can cause table misalignment in standard chunking logic. Frequently updated documents require parsing processes with lightweight adaptation capabilities, to avoid disrupting requirement pool synchronization due to frequent configuration adjustments. Fields related to compliance reviews need precise matching; chunking must retain field associations to prevent loss of compliance check markers after splitting. Dispersed customer feedback text increases the difficulty of determining chunk boundaries, which can easily lead to content truncation or redundancy.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the mixed table and paragraph structure of requirement pool documents, avoiding loss of field association after splitting |
chunkSplitter | Paragraph + table delimiter | Targets the mixed format of requirement pool documents, preserving table integrity and paragraph semantics |
customPdfParse | Enabled | Adapts to uploaded PDF requirement assessment forms, preventing table misalignment from native parsing logic |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the average parsing duration of single requirement pool documents, preventing parsing timeouts for large files |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch uploads of version planning documents, meeting batch requirements for weekly or version updates |
chunkSettingMode | Manual configuration | Flexibly adjusts chunking rules for documents from different sources, aligning with compliance review field matching requirements |
Three common configuration mistakes
- Table content in uploaded PDF requirement assessment forms is displayed misaligned. This occurs because
customPdfParseis not enabled, and native parsing logic cannot adapt to nested table structures. - Uploading a file after API integration returns a parsing failure status. This occurs because
customPdfParseis not configured, orUPLOAD_FILE_MAX_SIZEhas been exceeded. - Waiting for more than the preset time without a response after uploading a large requirement pool document. This occurs because
PARSE_FILE_TIMEOUT_SECONDShas not been adjusted to a suitable duration.
How to verify correct configuration
- Upload a PDF requirement assessment form that contains nested tables, and check if the parsed text retains table row and column structure without misalignment.
- Upload a single version planning document with a size of 800 MB, and confirm that the upload and parsing processes have no errors.
- View the backend parsing logs in FastGPT v4.17.0, and confirm that the
PARSE_FILE_TIMEOUT_SECONDSconfiguration did not trigger timeout interception. - Manually adjust
chunkSizeto different ranges, and verify if chunked content retains the association of core fields such as customer ID and compliance markers.
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.