What this category of data looks like
This category of data comes from government information disclosure platforms, official archive systems, document management systems, and departmental business ledgers. Update frequency is irregular. Commonly processed documents include standardized government information disclosure application forms, supplementary notice letters, third-party opinion solicitation letters, response letters, service receipt forms, and administrative reconsideration response materials. Most documents have fixed structures, containing fields such as applicant information, application matters, response content, and delivery records. Some documents include paper materials in scanned form. The processing objects of this category are individual requests from specific applicants. This differs from actively disclosed information intended for the general public.
What constraints do these characteristics impose on the "document parsing and chunking" link?
The standardized nature and irregular update frequency of documents in this category require the parsing link to adapt to various formats of official documents and scanned materials. The length of different documents varies significantly. Some documents are only a few dozen words, such as application forms. Others span several pages, such as administrative reconsideration response materials. When chunking, balance the integrity of key fields. Avoid splitting core content such as applicant information and application matters. Paper materials in scanned form require triggering an OCR process. Handle possible Chinese recognition garbled characters. Scattered data sources lead to inconsistent document formats. Support batch parsing of files from different sources. Retain the association between application matters and response content. Prevent information misalignment during retrieval. Misalignment would affect subsequent public attribute judgment and response drafting work.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the core content length of standardized official documents in this category, avoiding splitting key fields such as applicant information and application matters |
chunkSplitter | Chunk by paragraph + semantics | Retains the logical integrity of official documents, aligning with reading and retrieval habits for government affairs documents |
customPdfParse | Enabled | Applies to the fixed format of standardized PDF official documents, accurately extracting text and layout information to reduce parsing errors |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses parsing time consumption for long documents such as administrative reconsideration response materials, preventing task interruption mid-process |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compatibility with batch-imported archive scanned material packages, meeting daily batch processing needs |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types, adapting to the diverse document structures of this category |
Three Common Misconfigurations
- Uploading scanned image files results in unrecognized content. The symptom is empty parsing results or Chinese garbled characters after uploading image format files. The cause is failure to configure OCR parameters adapted to government affairs scanned materials and enable the Chinese recognition model.
- No matching results are found when searching a single PDF document. The symptom is that when asking a question about a single imported response letter, the model returns that no relevant content was found. The cause is accidental splitting of the association between core response content and application matters during chunking.
- Field mapping fails after importing structured table data. The symptom is that irrelevant field content is returned when searching ledger data. The cause is failure to configure the dataset's field mapping rules and specify core fields to be searched such as application number and response document number.
How to Confirm Configurations Are Correct
- Upload a typical government information disclosure application form. Check whether the parsing result completely extracts the applicant information and application matter fields.
- Import a response letter in scanned form. Check whether the OCR result has no obvious Chinese garbled characters.
- Submit a targeted question about a single imported administrative reconsideration response material. Check whether the model can return the corresponding paragraph content.
- Upload a file package of the maximum allowed size. Check whether the parsing task completes within the set timeout period.
The values provided here are common starting points, and should be evaluated against the samples used in actual 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.