What data in this category looks like
Daily documents for database cloud service operations include instance change tickets, backup and recovery records, performance diagnosis reports, and parameter adjustment records. Data comes from cloud database consoles, slow logs, monitoring metrics, and ticketing systems. Update frequency is daily or after each change. Most documents have standardized headers, numerical metrics, and instance identification fields. These fields include instance ID, change time, slow SQL statements, backup paths, and more. Units include seconds, MB, percentage, and others.
What constraints these characteristics impose on document parsing and chunking
Documents in this category contain long SQL statements, multi-table monitoring data, and standardized instance identifiers. Avoid chunking that breaks semantic connections. Documents update frequently and may have large individual sizes. Control parsing duration and file upload limits. Some documents include multi-tenant permission fields. Retain contextual boundaries during chunking to prevent cross-tenant information mixing. Operation and maintenance documents use fixed table structures. General parsing logic often causes misalignment. Adjust parsing rules specifically for this use case.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Most documents in this category include long SQL statements and monitoring metric rows. This range avoids splitting to break semantic integrity |
customPdfParse | Enabled | Most documents in this category have standardized tables and instance numbers. Local parsing preserves table formatting and field associations |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | A single backup and recovery record may include multiple days of monitoring data, requiring sufficient time to complete full parsing |
chunkSplitter | Split by paragraph + header | Documents in this category include performance report headers and slow SQL blocks. Splitting by headers preserves grouped semantics |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Operation and maintenance documents may include archived slow log batch files. Relax the upload limit to accommodate these files |
chunkSettingMode | Manual mode | Adjust chunking rules for different document types such as instance change tickets and performance reports |
Three common configuration errors
- Symptom: Parsing fails after uploading a PDF file, and the console returns a 413 status code. Cause: The
UPLOAD_FILE_MAX_SIZEparameter is not adjusted, and the file size exceeds the default limit. - Symptom: Parsed table documents show misalignment, and chunking results are disorganized. Cause:
customPdfParseis not enabled. General chunking logic cannot recognize the standardized table structure of operation and maintenance documents. - Symptom: File parsing times out during conversation after API integration. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set too short, unable to process documents containing multiple days of monitoring data.
How to verify correct configuration
- Upload an archived slow log file under 1000 MB, check if parsing completes within 300–600 seconds.
- Upload a performance diagnosis report with multiple tables, check if parsed chunks retain the association between headers and corresponding data rows.
- Test uploading an instance change ticket, check if chunks retain the complete context of ticket numbers and change content.
- View the local parsing logs of FastGPT v4.17.0, confirm there are no external network transmission records, verifying that parsing is handled locally.
The values listed here are common starting points. Adjust configurations based on your own specific samples and 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 2026-10-19.