What the Data for This Category Looks Like
Core data for the elderly care service institution supervision scenario comes from the civil affairs elderly care service information platform, civil affairs statistics system, fire inspection records, and institution operation ledgers. Commonly processed documents include filing materials, operation subsidy applications, service quality inspection forms, safety hazard rectification ledgers, and elderly admission files. The data update frequency is monthly. Most documents contain fixed structured fields such as institution name, filing number, bed count, inspection items, and subsidy amount. Some documents include tables and image annotations, with an overall structured format but diverse types.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Link
The low update frequency of monthly updates means there is no need for high-frequency parsing task triggers. However, the differences across multiple document types require parsing rules to be flexible. The presence of structured fields requires that chunking preserves the association between fields, avoiding splitting the filing number and bed data of the same institution into different chunks. Improper parsing of documents with tables can lead to disordered row and column information, affecting subsequent data verification. The presence of image annotations requires the parsing link to simultaneously extract text information associated with images, avoiding missing key content. The verification process for supervision documents is time-consuming, so chunking should preserve contextual associations as much as possible to reduce the information splicing cost during subsequent retrieval.
How to Configure Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Elderly care supervision documents mostly include associated fields. This length preserves the contextual association of key information such as institution name and filing number, calibrated through scenario-based testing |
chunkSplitter | By paragraph + custom rules | Supervision documents have fixed headers and structured paragraphs. Custom rules can preserve the row and column associations within tables, avoiding splitting key inspection items |
customPdfParse | Enabled | Elderly care filing materials are mostly in PDF format with tables. Enabling this preserves table structure and avoids text disorder after parsing |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Operation ledger files for large elderly care institutions are large in size. This duration ensures complete parsing without timeouts |
chunkSettingMode | Manual mode | Chunking rules need to be adjusted for different document types such as filing materials, inspection forms, and ledgers, to adapt to the field extraction needs of the supervision scenario |
Three Common Misconfigurations
- Phenomenon: After uploading a Word or Excel file, no results appear in knowledge base searches, and the interface shows a parsing error. Cause: The parsing rules for Office files are not configured, or the corresponding parsing capability is not correctly enabled, causing table content to be incorrectly split into meaningless fragments and preventing valid chunks from being generated.
- Phenomenon: After entering relevant keywords for knowledge base search testing, only text content is returned without the image information from the document. Cause: The image OCR parsing configuration is not enabled, or the text annotations associated with images are discarded during chunking, causing image content to not be included in the knowledge base.
- Phenomenon: The filing information of the same elderly care institution is split into multiple scattered chunks, and complete data cannot be obtained in a single search. Cause:
chunkSizeis set to less than 500 characters, causing paragraphs with associated fields to be split excessively, requiring splicing multiple chunks to obtain complete information during retrieval.
How to Confirm the Configuration Is Correct
- Upload a typical elderly care service quality inspection form, check the parsed chunk results, and confirm that fields such as inspection date, institution name, and rectification requirements within the table are not split into different chunks.
- Run the knowledge base search test function, enter "filing information of a certain elderly care institution", and confirm that single or associated chunk content containing complete filing number and bed count data is returned.
- Upload an institution operation ledger larger than 100MB, and confirm that the parsing task completes within the duration set by
PARSE_FILE_TIMEOUT_SECONDSwithout timeout error prompts. - Upload a PDF of an elderly admission file with image annotations, and confirm that the parsed result includes the text annotation information corresponding to the images without missing content.
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.