What the data for this category looks like
The data sources for this category are special equipment safety supervision systems, inspection and testing institution systems, user account books, and operator certificate databases. Daily processed documents include use registration certificates, periodic inspection reports, maintenance records, hidden danger rectification notices, accident reports, and operator certificates. Data updates occur monthly. Core fields include device unique identifier, inspection cycle, maintenance cycle, operator qualification number, rectification closed-loop status, and more. Most document structures use fixed form formats. Some reports include multi-level directories and embedded images. Some older archived documents are in scanned file format.
What constraints do these characteristics impose on the "document parsing and chunking" link
Diverse document formats from multiple system sources—fixed forms, scanned files, and reports with embedded images—require the parsing module to support multiple input types. The monthly batch update feature requires the chunking process to support batch scheduling, to avoid single-processing timeouts. Core fields such as device identifiers and inspection cycles must be accurately matched to corresponding document paragraphs. Chunking across devices or cycles will lead to errors in subsequent process guidance. Scanned document files cannot extract text directly. An additional OCR parsing link must be configured, otherwise fields will be empty.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the average length of core fields and paragraphs in documents of this category, avoiding chunking across business units |
chunkSplitter | Split by title hierarchy | Adapts to the multi-level directory structure of periodic inspection reports and maintenance records, ensuring complete chunk semantics |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers the OCR parsing time for batch scanned document files, avoiding timeout failures |
customPdfParse | Enabled | Compatible with PDF format reports with embedded images and attachments, fully extracting document content |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports upload and parsing of large accident reports and batch archived documents |
Three common mistakes
- After uploading a document with multi-level directories, only the first-level content is parsed, and text from subdirectories cannot be retrieved. The cause is that the chunking rule of splitting by title hierarchy is not configured. Only fixed character length truncation is used, causing subdirectory paragraphs to be split into unrelated chunks.
- Calling the API to upload a document shows success but returns no parsing results. The cause is that a reasonable value for
PARSE_FILE_TIMEOUT_SECONDSis not set. Result callback is not triggered after batch document parsing times out. - Core fields are empty after parsing batch scanned maintenance records. The cause is that
customPdfParseand the OCR parsing link are not enabled. Text content in scanned files cannot be extracted.
How to confirm the configuration is complete
- Upload a periodic inspection report with multi-level directories, check if the parsed chunks include all text content under subdirectories.
- Upload a scanned format maintenance record of around 100MB, verify that the parsing time is within the range of the set
PARSE_FILE_TIMEOUT_SECONDS. - Call the API to upload a single standard-format use registration certificate, confirm that the returned result includes a list of parsed text chunks.
- Check the switch status of
customPdfParsein the system settings, confirm that the parsing mode for documents with images has been enabled.
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.