Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Data for this category mainly comes from government portals, document management systems, government information disclosure directories, policy document repositories, and press conference materials, with a daily update frequency. Commonly processed documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. Most documents contain fixed fields such as document numbers, issuing units, drafting dates, public disclosure attributes, and security classification levels. Some column update records are structured table data.
Constraints on parsing and chunking workflows
The high daily update frequency requires that the parsing and chunking workflow has stable batch processing capabilities to avoid delays that impact release timelines. Structured table documents have multiple columns of fields. If the chunking logic does not adapt to table structures, column data may be split incorrectly or not fully recognized. Long policy-related text must be split according to chapter logic to avoid arbitrary truncation that breaks policy consistency. Additionally, documents contain sensitive fields such as public disclosure attributes and security classification levels. The chunking process must retain the contextual association of these fields to prevent missing sensitive information during review due to scattered distribution.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the chapter length of policy documents and interpretation drafts, avoids splitting that breaks policy logic units, and controls single-block retrieval precision |
chunkSplitter | Split by paragraph + title | Aligns with the hierarchical structure of government documents, retains contextual association of fields such as policy issuing units and drafting dates |
customPdfParse | Enabled | Adapts to interference from headers, footers, and stamp areas in government PDF documents, improving structured content extraction accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses large batches of uploaded policy document repositories, prevents task failure due to parsing timeouts |
chunkSettingMode | Manual mode | For structured table documents, chunking rules can be adjusted individually to support complete extraction of multi-column field data |
Three common configuration errors
- Symptom: After uploading a multi-column structured table document, only the first two columns of data can be matched during retrieval. Cause: The
chunkSettingModemanual mode is not enabled. The default chunking logic does not adapt to the field association of multi-column tables, causing subsequent column data to be truncated or ignored. - Symptom: Stamp areas, headers, and footers in PDF documents are mistakenly identified as main text, causing irrelevant information to be mixed into chunks. Cause: The
customPdfParseconfiguration is not enabled. The default parsing logic cannot filter non-main text interference elements in government PDF documents. - Symptom: Boolean data extracted from the HTTP component turns into a null value after processing by the conditional judgment component. Cause: The original data type of the field is not retained during the document parsing process, causing format loss when passing between components.
How to confirm configurations are correctly set
- Upload a single policy document, view parsed chunk results, confirm no chunk breaks the complete logic unit of the policy, and adjust
chunkSizebased on actual document length. - Upload a multi-column structured table document, verify the integrity of parsed data fields, confirm all columns are correctly recognized, and switch
chunkSettingModeto adjust adaptation rules as needed. - Batch upload the daily updated document queue, monitor parsing task execution status, confirm no timeouts or failures occur, and adjust the value of
PARSE_FILE_TIMEOUT_SECONDSas needed. - Test the extraction effect of sensitive fields, confirm fields such as public disclosure attributes and security classification levels are correctly associated with corresponding chunks, and enable
customPdfParseto optimize extraction accuracy.
The values provided here are common starting points and should be evaluated against the samples relevant to the specific deployment.
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.