What this type of data looks like
Typical data sources include the national integrated government service platform item database, administrative licensing item list, departmental business approval systems, and electronic certificate repository. The update frequency is daily. Documents processed daily include service guides, application forms, acceptance notices, correction notices, administrative licensing approval decisions, and license certificates. These documents have fixed fields such as legal item number, legal basis, handling conditions, application material list, handling process, and certificate style. Some documents are semi-structured with forms or official stamps.
What constraints do these characteristics impose on the document parsing and chunking link?
Daily updated multi-source data requires parsing and chunking workflows to adapt to format differences across document types. This prevents loss of key fields like legal basis and handling conditions due to format incompatibility. Administrative licensing documents must strictly match the boundaries of legal items. Chunking operations must not break the binding relationship between items and their corresponding basis or materials. Semi-structured form and certificate documents require accurate extraction of field information. Inaccurate extraction causes content deviations in subsequent matching links. This affects the accuracy of service consultation and response, and may lead to consequences such as overdue completion or license revocation via reconsideration.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapt to the paragraph length of service guides, retain the integrity of core content such as legal basis and handling conditions |
chunkSplitter | Split by title + paragraph | Match the structured title hierarchy of administrative licensing documents, avoid breaking the association between items and corresponding rules during splitting |
customPdfParse | Enabled | Adapt to the form and stamp formats of government-related PDFs, accurately extract field information from application forms and acceptance notices |
PARSE_FILE_TIMEOUT_SECONDS | 600–900 seconds | Cover the parsing time of large service guide PDFs or multi-page certificate collections, avoid timeout errors |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapt to batch-uploaded administrative licensing item list Excel files or multi-volume certificate PDFs |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types such as service guides and decision documents, meet the requirements of legal content matching |
Three common mistakes
- Phenomenon: The platform returns timeout-related errors when parsing government PDFs with more than 100 pages. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted, and the default value was used, causing parsing failures for time-consuming documents. - Phenomenon: When retrieving administrative licensing application material data for a region, the returned results are fewer than the actual entries in the Excel file. Cause: Complete data entries spanning cells were truncated during chunking, or the associated information of regional fields was not retained.
- Phenomenon: Corresponding content cannot be retrieved in the knowledge base after uploading a PDF. Cause:
customPdfParsewas not enabled, and the default parsing cannot recognize the form or stamp formats of government-related PDFs, leading to failed field extraction.
How to confirm the configuration is properly set
- Upload a single-page acceptance notice PDF. Check if the parsed data includes fixed fields such as acceptance number and application item, confirm that the
customPdfParseconfiguration takes effect. - Upload a service guide PDF with more than 150 pages. Wait for parsing to complete and check the system log. Confirm no timeout errors occur, verify that the
PARSE_FILE_TIMEOUT_SECONDSconfiguration is valid. - Import an administrative licensing item list Excel file. Retrieve entries for a specific region, confirm that the returned results match the actual number of entries in the file, verify that chunking did not truncate data.
- Adjust the
chunkSizeparameter to 600 characters. Check if the chunked text retains complete legal basis paragraphs, confirm that the chunking logic meets business requirements.
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.