What the data for this category looks like
Data for this category mainly comes from the Random Inspection and Public Disclosure Supervision Platform, enterprise credit information disclosure system, industry supervision systems, and law enforcement officer directory. Daily processed documents include random inspection plans, inspection target lists, inspection item lists, on-site inspection records, rectification notices, and random inspection result announcements. The data updates monthly. Most document fields include unified social credit codes, inspection item codes, law enforcement officer IDs, and inspection batches. Some documents include quantitative units such as number of inspection personnel and rectification time limits.
Constraints on the document parsing and chunking link
Monthly updated batch documents require the parsing link to support batch scheduling, to avoid single-processing timeouts. Documents contain structured fields such as unified social credit codes and inspection item codes. Chunking must retain the association between fields and context, to prevent loss of field correspondence after splitting. Some documents include non-penalty inspection records. Chunking boundaries must avoid key supervision information nodes. Document format differences across multiple sources require the parsing component to support common formats such as PDF and DOCX, to prevent format parsing failures.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
chunkSize | 800–1200 characters | Matches the length of core paragraphs such as inspection items and inspection records in this category of documents, to avoid splitting key information units |
chunkSplitter | Split by paragraph + heading | Adapts to the document structure with hierarchical headings such as inspection plans and inspection lists, retaining content logical association |
customPdfParse | Enable structured parsing mode | Extracts tables and structured fields from PDF-format inspection result announcements and on-site records, improving parsing accuracy |
UPLOAD_FILE_MAX_SIZE | 100 MB | Covers the common size of single documents in this category such as batch inspection target lists, to avoid upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the time consumption requirements of batch document parsing, to avoid parsing process interruptions due to timeout |
chunkSettingMode | Manual configuration | Allows adjustment of chunking parameters for different document types such as inspection records and announcement lists, adapting to business scenarios |
Three common misconfigurations
- Phenomenon: When uploading documents in a server environment, the parsing node returns a 404 error, and parsing works normally in a local environment. Cause: The server-side file storage path permission or mapping is not configured, so the parsing component cannot access uploaded file resources.
- Phenomenon: When parsing PDF-format inspection result announcement documents, structured fields such as unified social credit codes are extracted as empty. Cause: The structured parsing mode of
customPdfParseis not enabled, or the selected large model has insufficient adaptation to structured table text extraction, leading to field extraction failure. - Phenomenon: After batch uploading monthly updated inspection target list documents, the parsing result chunks lose the association with batch numbers. Cause: The
chunkSizevalue is too small, splitting paragraphs containing batch numbers and corresponding target lists into multiple chunks, breaking information association.
How to confirm configurations are correctly set
- Upload a typical single document such as an on-site inspection record, and check whether the parsed chunk results retain the contextual association of core fields such as law enforcement officers and inspection time.
- Adjust the
chunkSizeparameter, compare chunking results under different values, and confirm that core paragraphs are not forcibly split. - Upload a document larger than the conventional size, and verify that the upload and parsing process does not trigger the
UPLOAD_FILE_MAX_SIZEorPARSE_FILE_TIMEOUT_SECONDSlimits. - Batch upload monthly updated batch documents, confirm that parsing tasks can be scheduled and completed normally without interruptions mid-process.
The values provided here 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.