What Data for This Category Looks Like
Cloud billing and cost accounting daily documents include billing details, cost allocation tables, resource utilization reports, and optimization suggestion sheets. Data primarily comes from cloud billing systems, tag data, order systems, and resource monitoring platforms. Most updates occur on a daily or monthly basis. Document structures typically combine fixed-format structured tables and explanatory text. Fields include resource ID, cost amount, time range, tag key-value pairs, allocation ratio, and more. Units include yuan, hours, GB, and others. Some documents include cross-field associated calculation logic.
What Constraints Do These Characteristics Impose on Document Parsing and Chunking
Cloud billing and cost accounting documents often contain structured tables. Parsing and chunking must preserve relational connections between table fields. Splitting cross-field content will break cost allocation logic. Monthly billing files have large sizes and long parsing times. Sufficient processing time must be reserved. Field density varies widely across documents. Detail-type documents have dense fields. Report-type documents have relatively loose fields. Chunking granularity must be adjusted to match these differences. Abnormal expense troubleshooting documents may include scattered abnormal annotations and calculation processes. Key information must be extracted accurately to avoid losing troubleshooting basis.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of single billing detail records and associated table headers, avoids splitting cross-field content |
chunkSplitter | Split by Markdown tables + paragraphs | Adapts to the mixed structure of structured tables and explanatory text in daily documents, retains table integrity |
customPdfParse | Enabled | Adapts to the fixed table layout of cloud billing PDFs, accurately extracts fields and associated information |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Adapts to the parsing needs of large files such as monthly bills, avoids timeout interruptions |
chunkSettingMode | Manual configuration | Allows adjustment of chunking rules for detail-type and report-type documents separately, adapts to different field densities |
Three Common Misconfigurations
- Phenomenon: When uploading a file in a local deployment version, the parsing node shows no workflow logs, and the status displays waiting timeout. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The monthly bill file exceeded the default timeout threshold. - Phenomenon: Only partial data is captured after importing a database table, and fields are missing. Cause: The
chunkSizesetting is too small. Splitting truncates table row data spanning pages or chunks. - Phenomenon: Markdown tables output by the model are truncated, with content hidden as
...[hide X char]. Cause: Table recognition rules forchunkSplitterwere not configured. The table is split as ordinary paragraphs, losing its complete structure.
How to Verify Correct Configuration
- Upload a single monthly billing PDF. Check in the FastGPT v4.17.0 parsing results to confirm chunks retain complete table rows and associated explanatory text.
- View parsing logs to confirm the
PARSE_FILE_TIMEOUT_SECONDSparameter is active, with no timeout-related error messages. - Import a standardized cost allocation table database file. Confirm all fields are fully extracted, with no truncation or missing data.
- Cross-check configuration parameters and preset rules. Confirm
customPdfParseandchunkSettingModesettings match the requirements of the currently processed document type.
The values provided 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 2026-10-19.