What the data in this category looks like
Data for this category comes from daily work documents of privacy compliance teams, security consulting departments, and legal affairs departments. It includes four core document types: personal information inventories, processing rules, impact assessment reports, and user authorization texts. Data sources include business system exports, App permission lists, privacy policy documents, and user request records. Updates occur quarterly or when product versions change. Document structures vary widely: some are plain text authorization statements, while others include tabular personal information inventories and impact assessment reports. Core fields include compliance-related details such as personal information type, processing purpose, and legal basis.
What constraints these characteristics impose on document parsing and chunking
Structural differences across the four core document types require parsing logic to adapt to multi-format content, and prevent missing key compliance fields in tables. Data sources include non-standardized business system exports, which may have misaligned or missing fields. Standardized processing is needed during parsing. Update frequency is relatively high, so chunking logic must support incremental synchronization to avoid re-parsing full document sets. This category focuses on processing information that identifies individual natural persons. During chunking, ensure all personal information-related content is fully covered. Chunk units must not break the link between processing purpose and personal information type.
Configuration Settings for FastGPT v4.17.0
For FastGPT v4.17.0, the following configuration items support document parsing and chunking for this scenario:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | `800–1200 characters | Compliance documents contain long paragraphs of processing rules. Chunk length must cover complete compliance logic units to avoid breaking the association between processing purpose and personal information type |
chunkSplitter | By paragraph + title anchor | Compliance documents have clear hierarchy, including title nodes such as personal information inventories and processing rules. Splitting by title preserves document structural integrity |
customPdfParse | Enable table recognition + Chinese encoding adaptation | Compliance documents often include tabular user authorization texts and impact assessment reports. Accurate extraction of personal information fields in tables and adaptation to Chinese encoding are required |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Large impact assessment reports take longer to parse. Timeouts cause parsing failures, so the setting must accommodate large file parsing needs |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compliance documents may include batch user request records, so support for large file upload parsing is required |
chunkSettingMode | Manual configuration | Compliance documents have special structures, so custom chunk rules are needed to match retention requirements for core compliance fields |
Three Common Misconfigurations
- Phenomenon: After importing an Excel-format personal information inventory, table content displayed in the knowledge base does not match the source file, and corresponding column personal information cannot be matched during retrieval. Cause: The table field mapping function of
customPdfParseis not enabled, so the correspondence between column headers and data is not retained during parsing. - Phenomenon: When parsing Chinese privacy policy documents, a large number of garbled characters appear in returned results, and compliance content cannot be read normally. Cause: Chinese encoding adaptation rules of
customPdfParseare not configured, so the Chinese encoding format of the document is not correctly identified during parsing. - Phenomenon: When batch parsing multiple user authorization texts, some documents fail to parse and time out, with task status showing failure. Cause: The configured value of
PARSE_FILE_TIMEOUT_SECONDSis too low, and it does not adapt to parsing time requirements of large authorization texts.
How to Confirm Configuration Correctness
- Upload a typical compliance document such as a personal information inventory, check parsed text content to confirm core compliance fields are not split or lost.
- Run a chunking test to verify chunked content covers complete compliance logic units, with no chunking across paragraphs or titles.
- Upload the largest single compliance document to confirm parsing task completes within the configured timeout period, with no timeout errors.
- Import Excel-format compliance tables to check if column correspondence of the table in the knowledge base matches the source file.
The values provided are common starting points and should be measured 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 2026-10-19.