What the data for this category looks like
Data originates from official documents, employee handbooks, training materials, meeting minutes, and similar documents stored in government and enterprise internal office systems. Updates are triggered on demand, with files uploaded synchronously when department announcements or training materials are revised. Document structures include fixed-format official letterhead documents, multi-page long PDFs, Word reports with tables, and other types. Fields include issuing unit, document number, effective date, main body content, and more. Common measurement units are pages, characters, and copies.
Constraints for Document Parsing and Chunking
Fixed-format official letterhead documents include non-content redundant elements such as headers, footers, and document number sections. Parsing must accurately filter these elements to avoid disrupting subsequent chunking logic. Parsing time for multi-page long PDFs grows with page count, and may exceed the system’s default timeout threshold. Timeout parameters must be adjusted to accommodate this. Word documents with tables must retain their table structure; chunking must not break logical content connections. The varied formats of internal documents require flexible chunking rules to prevent splitting critical business information. On-demand update scenarios require parsing configurations to support batch processing of files of varying sizes.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the main body density of government and enterprise internal documents, avoids single chunks being too long to cause embedding failure or too short to break context |
chunkSplitter | Split by paragraph + semantics | Adapts to office documents with tables and fixed formats, retains complete content logical integrity |
customPdfParse | Enabled | Adapts to multi-page PDFs and official documents with headers/footers commonly used in government and enterprises, filters non-main-body redundant information |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports large-volume documents uploaded in batches by government and enterprises, avoids upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600–900 seconds | Adapts to parsing time of hundreds-page long PDFs, avoids mid-process timeout interruptions |
chunkSettingMode | Manual configuration | Adapts to the diverse formats of government and enterprise documents, allows flexible adjustment of chunking rules |
Three Common Mistakes
- Phenomenon: After integrating a custom PDF parsing tool, large-volume documents remain in a waiting state with no results, eventually triggering a timeout. Cause: No reasonable timeout parameters and batch queuing mechanism configured; long document parsing time exceeds the system's default threshold.
- Phenomenon: Calling the document parsing tool to process hundreds-page PDFs returns an error, while processing tens-page PDFs works normally. Cause: Long document parsing exceeds the single-processing limit of the tool; no timeout configuration adjusted to adapt to long documents.
- Phenomenon: After locally deploying a custom PDF parsing component, the calling page displays an error about unable to read an undefined property. Cause: The compatible versions of FastGPT v4.17.0 and the custom parsing tool are not matched; dependency package version conflict exists.
How to Confirm Configurations Are Properly Set
- Upload a single government and enterprise office PDF with fewer than 100 pages, check if the parsing result retains the main body, tables, and fixed format information, confirm the parsing logic is effective.
- Upload a single document with a volume matching the
UPLOAD_FILE_MAX_SIZEconfiguration, verify the upload process is not blocked, confirm the upload limit configuration is correct. - Trigger a long document parsing task, wait for the duration set in
PARSE_FILE_TIMEOUT_SECONDS, check if the task completes without timeout errors, confirm the timeout configuration adapts to business needs. - After adjusting the
chunkSizeparameter, check if the length of the chunked results matches expectations, confirm the chunking rules are effective.
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 2026-09-28.