What This Category of Data Looks Like
Data for this category comes from government information disclosure platforms, official archive systems, document management systems, departmental business ledgers, and standardized documents related to government information disclosure. Common processed documents include government information disclosure application forms, supplementary notice letters, third-party opinion solicitation letters, response letters, service receipts, and administrative reconsideration response materials. Data updates follow no fixed cycle, and are generated based on individual application and processing progress. Most documents use standardized template structures, with fixed fields such as applicant information, application items, document numbers, and remedy channels. There is little unstructured free-form content.
Constraints on Document Parsing and Chunking
Since most documents in this category are standardized official papers with fixed fields and template structures, chunking must avoid splitting core related fields such as document numbers and remedy channels. This ensures subsequent process guidance can accurately link application items and corresponding content. Data sources are scattered, and updates follow no fixed cycle. Parsing must support format differences from exports of different systems, including electronic documents with watermarks, headers and footers, or scanned copies. Individual application documents are generally small in size. Parsing must accurately extract content directly related to application items, and exclude irrelevant internal circulation annotations. Chunked content must also be linkable to specific application numbers and processing stages.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Most documents in this category are standardized official papers, with core fields closely linked to application items. This range avoids splitting key information while adapting to the content density of most individual application documents. |
chunkSplitter | Split by paragraph + fixed template blocks | Standardized official papers have fixed structures. Splitting by paragraphs and template blocks preserves field relevance, and prevents core information from being separated across chunks. |
customPdfParse | Enabled | Documents in this category often contain formatted content such as official document numbers and remedy channels. Enabling this preserves key information from the original layout, and improves chunking accuracy. |
UPLOAD_FILE_MAX_SIZE | 100 MB | Single documents in this category are generally small in size. This upper limit meets the demand for batch uploading of archived materials, while avoiding resource waste. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Some scanned documents require OCR processing. This duration covers the parsing process for complex formats, and prevents timeout interruptions. |
chunkSettingMode | Manual configuration | Chunking rules must be adjusted for the structure of standardized official papers. Manual configuration accurately matches the field association requirements of documents in this category. |
Three Common Mistakes
- After uploading standardized Word or Excel format documents, the parsing result shows missing fields or garbled text. The cause is failure to enable the custom parsing switch for the corresponding format, or failure to adapt to the standardized table structure of documents in this category.
- After importing application disclosure documents, knowledge search tests return no results and show parsing errors. The cause is that
PARSE_FILE_TIMEOUT_SECONDSis set too short, so scanned documents are terminated before OCR parsing is completed, orchunkSizeis set too large, causing core information to be truncated. - Relevant settings for high-precision document parsing cannot be found. The cause is that the installed FastGPT version does not support this function. Upgrade to FastGPT v4.17.0 or later.
How to Confirm Proper Configuration
- Upload a standardized government information disclosure application form, review the parsed chunked results, and confirm that core fields such as document numbers and application items are not split across chunks.
- Upload a scanned response letter with a watermark, confirm that OCR parsing has no obvious garbled text, and that key remedy channel content is fully extracted.
- Test uploading a single archived material under 100 MB, confirm that the parsing process completes within 600 seconds with no timeout errors.
- Enter the knowledge search test stage, enter keywords related to the uploaded document, and confirm that the content of the corresponding chunked segment can be retrieved.
The values listed above are common starting points. Adjustments should be made based on individual use cases.
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.