Data Profile for This Category
Typical entities include construction quality and safety supervision stations, construction contractors, supervision units, and project owners. Daily documents include supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Data sources are project quality and safety supervision systems, on-site real-name management platforms, supervision logs, and test reports. Update frequency is weekly. Document structures cover structured tables and unstructured paragraphs. Fields include professional engineering information such as project identifiers, inspection content, rectification requirements, and acceptance conclusions. Supported formats include standard PDF, scanned documents, Word documents, and other common types.
Constraints on the "Document Parsing and Chunking" Workflow
Documents for this category come from scattered sources and use mixed formats. They include both standard files exported from internal systems and non-standard PDFs created by scanning handwritten on-site records. This places high demands on parsing engine adaptability. The weekly batch update requirement creates a need for large-scale batch parsing, which requires stable parallel processing of multiple files. Document structures vary widely: some files list rectification requirements in tables, while others record inspection processes in paragraphs. Chunking must preserve both the integrity of professional terminology and contextual connections. Additionally, some documents are lengthy—for example, completion acceptance supervision reports may include extensive attachments. The length of individual chunks must be controlled appropriately to maintain subsequent retrieval accuracy.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Most documents contain engineering professional terminology and coherent descriptions. Setting the chunk length within this range balances contextual integrity and retrieval accuracy |
chunkSplitter | Split by paragraphs + headers and footers | Documents often include header information such as project numbers and inspection dates. Following this splitting rule preserves the integrity of associated information |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Individual completion acceptance supervision reports are lengthy. Sufficient processing time must be reserved during batch parsing to avoid timeout errors |
customPdfParse | Enabled | Most on-site scanned documents are non-standard PDFs. Custom parsing can adapt to special formats such as tables and handwritten annotations |
UPLOAD_FILE_MAX_SIZE | 100 MB | Individual completion acceptance supervision reports and their attachments can reach tens of megabytes. The upload limit must be relaxed to support complete file parsing |
chunkSettingMode | Manual configuration | Chunking requirements vary across document types such as inspection records and rectification notices. Manual configuration allows flexible parameter adjustments |
Three Common Configuration Mistakes
- Issue: Timeout errors with status code 504 occur during batch parsing of weekly supervision inspection records. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default duration is insufficient to process individual lengthy files. - Issue: Table content in hidden danger rectification notices is lost or displayed abnormally after file enhanced parsing is enabled. Cause:
customPdfParsewas not enabled. The default parsing engine cannot adapt to the table structures of on-site scanned non-standard PDFs. - Issue: The file parsing tool cannot be triggered when calling DeepSeek-R1. Cause: The corresponding parsing module was not bound in the tool configuration, or the FastGPT version in use has abnormal tool calling logic.
How to Verify Correct Configuration
- Upload a single completion acceptance supervision report, and confirm that the parsed chunks include complete acceptance conclusion paragraphs and attachment lists.
- Batch upload 10 weekly supervision inspection records, and confirm that total parsing time stays within the preset
PARSE_FILE_TIMEOUT_SECONDSrange. - Call the file parsing tool, and confirm that table fields and hidden danger description content from hidden danger rectification notices can be extracted normally.
- Switch to FastGPT v4.17.0, and confirm that no abnormal errors occur during tool calls.
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.