What the data for this category looks like
The core data for this category comes from local public data open platforms, integrated big data platforms, departmental business databases, and electronic certificate repositories. The update frequency is monthly. Commonly processed documents include public data resource catalogs, data open lists, data item descriptions, desensitization rules, interface documentation, update frequency descriptions, and similar materials. Document structures include structured tables, field description paragraphs, interface address snippets, and desensitization requirement entries. Fields cover data item names, open scope, desensitization rules, interface call permissions, update cycles, and other categories. There is no unified fixed format specification. Some documents contain multi-table nesting from cross-departmental summaries.
Constraints for document parsing and chunking
The monthly update requirement means the parsing process must balance stability and adaptability. It does not need frequent iterations, but must adapt to monthly added multi-format documents. The multi-table nesting and structured field document structure means the chunking logic must not break the complete context of a single data item. It must avoid separating data items from their open conditions and desensitization rules. Large format differences across documents from different sources require support for multiple upload types including Word, Excel, PDF, and others. Large file parsing takes significant time, so sufficient processing time must be reserved. It is also necessary to avoid data leaks or inconsistencies between the catalog and actual data caused by incorrect chunking.
Configuration settings
In FastGPT v4.17.0, reference the following configurations for document parsing and chunking in this scenario:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Public data catalog documents contain structured tables and field descriptions. This range preserves the complete context of a single data item, preventing key information from being split apart |
chunkSplitter | Split by paragraph + table | Adapts to the multi-table, multi-description paragraph structure of documents in this category, avoiding broken associations between data items and their corresponding open conditions |
customPdfParse | Enable structured parsing | For PDF-format interface documentation and desensitization rules, extract text and table structures to reduce garbled text and format loss |
UPLOAD_FILE_MAX_SIZE | 15 MB | Matches the 10–15 MB Word files uploaded by users, preventing upload requests from being blocked by the system |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large file parsing takes a long time. This duration covers the parsing process for most documents in this category, reducing timeout failures |
chunkSettingMode | Manual configuration | Adjust chunking rules for different document types such as Excel data lists and PDF interface documentation to adapt to the multi-format documents in this category |
Three common mistakes
- When uploading a 10–15 MB Word-format data open list, parsing times out and fails. The cause is failure to adjust the
PARSE_FILE_TIMEOUT_SECONDSparameter to a sufficient duration. The default duration is insufficient to complete full parsing of large files. - When importing an Excel-format data item description document, the chunking result merges multiple rows of data items into one chunk. The cause is failure to adapt to the single-row data item format. The default chunking logic does not recognize entry boundaries.
- When submitting a query that precisely matches a single data item, the corresponding chunk cannot be retrieved. The cause is accidental splitting of the data item's desensitization rule field into different chunks during parsing, leading to missing context and inability to match the complete query conditions.
How to verify correct configuration
- Upload a single 10–15 MB Word-format data open list, check whether the parsing progress completes within the duration set by
PARSE_FILE_TIMEOUT_SECONDS, with no timeout errors. - Import an Excel-format data item description document, verify that the chunking result has one chunk per single-row data item, with no cross-row splitting.
- Upload a PDF-format interface documentation, check whether the parsed text retains table structures and field associations, with no garbled text or format errors.
- Submit a query that precisely matches a single data item, confirm that the corresponding chunk can be retrieved normally, with no matching failures.
The values listed 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.