What the data for this category looks like
The data for this category typically comes from elderly care service information platforms, civil affairs statistics systems, fire safety inspection records, and institution operation ledgers. Commonly processed documents include elderly care institution filing materials, operation subsidy application documents, service quality inspection forms, safety hazard rectification ledgers, and elderly admission files. Data updates occur monthly. Most documents mix structured tables and semi-structured text. They contain fields such as filing number, bed count, inspection date, and rectification requirements. Field units include bed count, duration, and similar metrics. No fixed unified format exists for these documents.
What constraints do these characteristics impose on the document parsing and chunking process
Monthly batch-processed document volumes are large. Support for batch parsing of multi-source files is required. Documents mix structured tables and semi-structured text. Traditional plain text chunking often splits table-related data. Targeted measures are needed to preserve field integrity. Some documents embed fire safety inspection photos and on-site institution photos. Parsing for image content must be supported. Large format differences exist across documents. Compatibility is needed for Word format filing materials, Excel spreadsheets for subsidy applications, and PDF files for rectification ledgers. This avoids loss of key supervision data during parsing.
How to configure the settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of semi-structured text and table fields in documents of this category, avoiding splitting key supervision data |
chunkSplitter | Separate by paragraphs and tables | Matches the mixed semi-structured text and table characteristics of documents, preserving field association integrity |
customPdfParse | Enabled | Adapts to multi-source PDF format filing and rectification ledger files, improving parsing accuracy |
UPLOAD_FILE_MAX_SIZE | 500 MB | Covers the maximum volume of single-batch bulk uploaded institution filing materials and ledger files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Meets the full parsing duration requirements for large ledger files, avoiding timeout interruptions for batch tasks |
Three common mistakes
- Parsing tasks return timeout errors with a 504 status code. This happens when the
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted to match the parsing duration of large elderly care institution ledger files. - Parsing results are empty after uploading documents with image links. This happens when the configuration for adapting image content parsing is not enabled, and only basic text parsing logic is used.
- Some documents are not correctly chunked after bulk file upload. This happens when
chunkSplitteris set to pure character splitting, without adjusting the splitting rules for mixed documents. This leads to incorrect splitting of tables and text.
How to confirm the configuration is correct
- Upload a single PDF of elderly care institution filing materials. Check if the parsed text fully retains key fields such as filing number and bed count.
- View background task logs to confirm that all monthly ledger files uploaded in bulk have completed parsing, with no timeout error records.
- After enabling the
customPdfParseconfiguration, upload fire safety inspection records with embedded images. Confirm that the text associated with the images is correctly extracted. - Test adjusting the
chunkSizeparameter. Confirm that the character length of the chunk results falls within the preset range, with no excessive truncation or overly long chunks.
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 2026-09-28.