What This Category of Data Looks Like
Data for this category primarily comes from internal enterprise monitoring systems, ticketing systems, service contracts, and customer communication records. Daily processed documents include standardized SLA clauses, monthly service reports, availability statistics reports, and customer review minutes. Data updates follow monthly or quarterly cycles. Most document structures include fixed-cycle service metrics, event details, and contract terms. Fields cover service cycles, customer identifiers, SLA compliance items, and abnormal event attribution results, among others. Field units vary based on the corresponding metric type, with no unified fixed format.
Constraints on Document Parsing and Chunking
Mixed document formats, inconsistent fields, and concentrated batch processing needs create multiple constraints for parsing and chunking. Multi-column tables frequently appear in monthly service reports and availability statistics. Accurate identification of column alignment relationships is required to avoid incorrect field splitting. Documents from dispersed sources have format differences, requiring adaptation to plain text, PDFs with embedded images, and structured table documents. Fixed-cycle batch data updates require parsing processes to support stable batch triggering, avoiding single-document parsing timeouts that disrupt overall progress. Nested SLA clause structures require retention of contextual associations. Chunking must not split the agreement and actual execution records of the same compliance item.
Configuration Settings
The following configurations are based on the technical logic of FastGPT v4.17.0, and are tailored to the document characteristics of SLAs and service reports:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of SLA clauses and service metric paragraphs in this category of documents, avoiding splitting of cross-associated content |
chunkSplitter | Split by paragraph + heading | Matches the structured hierarchy of monthly service reports and SLA clauses, retaining contextual associations |
customPdfParse | Enable image recognition mode | Adapts to monthly report documents with embedded charts and screenshots, restoring visual service data |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses large-volume service report documents uploaded in batches, avoiding parsing timeouts that interrupt tasks |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compatible with quarterly summary multi-page service report documents, meeting batch processing requirements |
chunkSettingMode | Manual configuration mode | Tailors chunking rules to different document types based on the structured characteristics of this category of documents |
Three Common Misconfigurations
- Phenomenon: Fields are misaligned or content is merged after parsing multi-column tables. Cause: No adapted table parsing rules are configured for the structured monthly reports in this category, and the default chunking logic cannot recognize multi-column aligned service metrics.
- Phenomenon: Embedded availability statistics charts in PDFs are not recognized, only blank text is returned. Cause: The image recognition switch for
customPdfParseis not enabled, resulting in failure to extract embedded visual data. - Phenomenon: Parsing timeout errors occur when batch uploading quarterly service reports. Cause: The
PARSE_FILE_TIMEOUT_SECONDSconfiguration value is too low, not adapting to the size and parsing complexity of quarterly summary documents.
How to Verify Proper Configuration
- Upload a monthly service report containing multi-column tables, verify that parsed table fields align with the original document, and confirm chunking does not split table content.
- Upload a PDF document with embedded charts, verify that parsed results include text descriptions or recognized content corresponding to the charts, and confirm the image recognition switch is active.
- Upload a single large-volume quarterly service report, check the execution status of the parsing task, and confirm no timeout errors occur.
- For different document types (such as SLA clauses, customer review minutes), adjust chunking configuration and compare parsing results to confirm contextual associations are retained.
The values listed above are common starting points and should be evaluated against sample documents relevant to the specific deployment.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.