What the data for this category looks like
Data for this category typically comes from senior care service information platforms, civil affairs statistics systems, fire safety inspection records, and facility operation ledgers. Commonly processed documents include senior care facility registration materials, operation subsidy application files, service quality inspection forms, safety hazard rectification ledgers, and elderly admission records. Updates for this category’s data occur on a monthly basis. Core processing steps include verifying facility registration and bed data, checking service quality and safety hazards, reviewing subsidy disbursement and rectification materials. Fields involved include facility name, number of beds, service level, rectification deadline, and similar. Units used are mostly bed counts, person-times, rectification deadlines, and similar.
Constraints Imposed on Document Parsing and Chunking by These Characteristics
Monthly batch document updates require the parsing and chunking workflow to have stability and batch adaptability, to avoid repeated processing or task interruptions. Different document types have significant structural differences. Registration materials use fixed form formats, rectification ledgers are sequential records, and service inspection forms are short item summaries. The chunking logic must adapt to multiple structural scenarios. Fields include numerical content such as the number of beds. Chunking must retain associated context, to avoid splitting numerical values from explanatory text and causing information loss. Most fire safety inspection records are short items. Overly fine chunking will break semantic connections, so chunk granularity must be controlled reasonably. Senior care facility registration materials involve qualification-related fields. Chunking must not split complete qualification-related information, to ensure the effectiveness of subsequent oversight reviews.
Configuration Settings
The following configurations follow the official setting specifications for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to long paragraph service records and registration information in senior care facility documents, avoiding semantic fragmentation |
chunkSplitter | Split by paragraph + title | Adapts to the structured formats of registration materials and rectification ledgers, retaining field associations |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Addresses large ledger files uploaded in monthly batches, avoiding parsing timeouts |
customPdfParse | Enabled | Adapts to scanned PDF registration materials submitted by senior care facilities, improving recognition accuracy for non-editable PDFs |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch uploading of monthly summary operation ledgers and inspection records, adapting to batch processing needs |
Three Common Misconfigurations
- Symptom: After uploading some senior care facility registration PDF files, the parsing result shows empty content, while some files are recognized normally. Cause: The
customPdfParseconfiguration is not enabled. The basic parsing engine cannot recognize scanned PDF files. - Symptom: After modifying the file suffix of a Java interface document to TXT and importing it, the parsing result has no valid data. Cause: The document is code-based structured text, and no matching chunking rules are used. Modifying the file suffix does not change the original code structure, so the parsing engine cannot recognize valid fields.
- Symptom: After using the chunking mode configured via
chunkSettingModeto call the pushdata API to upload data, the interface shows "indexing" for a long time. Cause: No reasonablePARSE_FILE_TIMEOUT_SECONDSparameter is set. Batch data parsing times out before completion, blocking the indexing process.
How to Verify Proper Configuration
- Upload a single senior care facility registration PDF, check if the parsing result includes complete facility qualification and bed information fields, to confirm the chunking configuration matches the document structure.
- Batch upload monthly summary rectification ledger files, check the timeout status of parsing tasks, to confirm the timeout parameter adapts to batch processing needs.
- Import structured documents with modified suffixes, test parsing results under different chunking rules, to confirm the chunking logic adapts to the document type.
- Call the pushdata API to upload chunked data, check task progress status, to confirm the chunking mode configuration matches the API call format.
The values provided here 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.