What This Category of Data Looks Like
Typical data for this category comes from construction quality and safety supervision stations, construction enterprises, supervision enterprises, and construction clients. Core data sources include engineering quality and safety supervision systems, on-site real-name management platforms, supervision logs, and test reports. Daily generated documents include supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Update frequency is weekly. Most document structures mix structured tables and unstructured paragraphs, with fields covering supervision targets, inspection times, hidden danger descriptions, rectification requirements, closed-loop status, and more. Some documents embed on-site photos and test data attachments, with no unified fixed format.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Link
The data characteristics of this category impose multiple constraints on the document parsing and chunking process. Data from multiple sources with no unified format requires support for multi-type document parsing to avoid splitting critical structured content. The weekly batch update feature requires reasonable timeout settings for parsing tasks to accommodate the parsing duration of large completion acceptance reports. Documents with embedded on-site photos and test attachments need complete extraction of image content or associated attachment indexes, otherwise complete information cannot be provided for business process guidance. Chunking of hidden danger rectification documents must retain the association between rectification requirements and closed-loop status to avoid breaking critical information.
How to Configure Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapted to the paragraph length of supervision inspection records and rectification notices to avoid splitting critical rectification requirements |
chunkSplitter | Split by paragraph + title | Retain the structured hierarchy of documents, such as chapters of supervision plans and rectification items of rectification notices |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Matches the task duration of weekly batch parsing to avoid parsing timeout for large test reports |
customPdfParse | Enabled | Adapt to PDF documents with embedded images and structured tables, retain original typesetting information |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Support upload and parsing of large completion acceptance supervision reports |
chunkSettingMode | Manual mode | Adjust chunking rules for different document types to adapt to the special structure of supervision documents |
Three Common Misconfigurations
- Phenomenon: An error indicating unrecognized data source and parsing failure is returned when parsing a publicly shared Yuque link. Cause: The link is not confirmed to be fully publicly accessible, and no adaptation rules for web page parsing are configured.
- Phenomenon: After importing Excel and multi-dimensional documents from a Feishu folder, the parsing result is empty or has missing fields. Cause: The cross-file batch parsing permission for the Feishu knowledge base is not enabled, or the export format of multi-dimensional documents does not adapt to FastGPT's parsing rules.
- Phenomenon: Parameter parsing works normally when calling an HTTP tool, but no actual request is executed. Cause: The request timeout parameter for the tool is not configured, or the request address is not added to the system whitelist, resulting in request interception.
How to Confirm Correct Configuration
- Upload a single supervision inspection record PDF, check the parsed chunked content to confirm that the rectification requirement paragraph is not split.
- Upload a hidden danger rectification notice with embedded images to confirm that the parsing result includes text descriptions or associated indexes of the images.
- Submit a weekly batch parsing task to check whether the parsing progress is completed within the time set by
PARSE_FILE_TIMEOUT_SECONDS. - Configure an HTTP tool call test to confirm that the request can be sent normally and return expected results.
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 2026-09-28.