What the data for this use case looks like
Core data for cloud resource compliance audit use cases comes from cloud audit logs, IAM permission configurations, CMDB resource inventories, and security baseline scan results. Daily produced documents include compliance checklists, permission audit reports, resource inventory lists, and rectification tracking forms.
Documents are divided into two categories: structured and semi-structured. Structured documents such as CSV-format resource inventories contain fields like instance ID, region, permission configuration, and others. Semi-structured documents such as PDF-format compliance checklists contain sections like check items, compliance status, rectification suggestions, and others.
Data update frequency is monthly or quarterly, and it is submitted to the system in bulk export form.
What constraints do these characteristics impose on document parsing and chunking?
The document sources and update rhythm of this scenario mean parsing and chunking must balance batch processing and structured association.
First, bulk exported cloud audit logs and resource inventories have large file sizes, so they need to adapt to parameter limits for large file upload and parsing. Second, structured documents contain multiple columns of associated fields. Chunking must avoid splitting content that spans associated fields, otherwise subsequent permission anomaly identification and rectification evidence verification will be affected.
In addition, semi-structured compliance checklists and rectification tracking forms need to retain the contextual association of natural paragraphs. Multiple formats such as CSV, PDF, and Feishu documents are used in this scenario, so corresponding parsing rules must be configured for each format.
How to configure settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Fits the single-chunk field coverage range of compliance checklists and resource inventories, avoiding splitting content that spans associated fields |
chunkSplitter | Chunk by paragraph + semantic grouping | Matches the natural paragraph structure of rectification tracking forms and permission audit reports, retaining contextual association |
customPdfParse | Enable external parser | Adapts to encrypted PDF or non-standard format compliance documents, matching the configuration requirements of the actual used external pdf-maker parser |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates quarterly bulk exported cloud audit log compressed packages, avoiding upload errors |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing time required for large resource inventories, avoiding mid-parsing timeout interruptions |
chunkSettingMode | Manual configuration | Adjust chunking rules for different document types such as CSV, PDF, and Feishu documents, meeting the parsing requirements of structured and unstructured documents |
Three common configuration mistakes
- Only the first two columns of data are extracted after a CSV-format resource inventory is uploaded. This occurs because the column range parameter for CSV parsing is not configured, and the default logic only loads the first two column fields.
- A 413 error is prompted when compliance audit documents are uploaded in Docker deployment mode. This occurs because the
UPLOAD_FILE_MAX_SIZEparameter is not adjusted, and the default value is insufficient to accommodate large bulk exported files. - PDF documents cannot be parsed normally after the external pdf-maker parser is enabled. This occurs because the corresponding key parameters for the parser are not correctly configured. Additionally, when Feishu multi-level directory documents are parsed, only the top-level content is retrieved, and embedded doc documents and images cannot be normally searched. This occurs because the full directory recursive parsing switch for Feishu documents is not enabled, and parsing adaptation rules for corresponding formats are not activated.
How to confirm configurations are correctly set
- A single compliance checklist PDF is uploaded, and the parsed chunks are checked to confirm they cover complete check items and rectification suggestions, with no content truncation or misalignment.
- A test CSV-format resource inventory is uploaded, and confirmation is made that all configured fields are extracted, with no forced truncation of the first two columns.
- The
PARSE_FILE_TIMEOUT_SECONDSparameter is adjusted, then a large cloud audit log compressed package is uploaded, and confirmation is made that there are no timeout interruption prompts during the parsing process. - A Feishu multi-level directory document is uploaded, and confirmation is made that subdirectory content, embedded doc documents, and images are all normally parsed and included in the search scope.
The values provided are common starting points and should be measured against the user’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.