Typical data for this category
Data typically originates from environment monitoring systems, access control systems, UPS monitoring equipment, and video inspection records. Update frequency is daily or real-time. Daily produced documents include inspection sheets, temperature and humidity logs, alarm records, and duty logs. Most document structures are tables or chronological entries. Fields included in these documents are device point numbers, temperature and humidity values, alarm levels, and timestamps. Common units are degrees Celsius, percentage, volts, and similar units.
Constraints for document parsing and chunking
Most data consists of chronological inspection and alarm records. Parsing and chunking must retain chronological links between entries. Do not split continuous records across time periods. Documents include many numerical fields with attached units. Parsing must accurately preserve the binding between fields and their units. Prevent separation of values and their units. Update frequency is daily or real-time. Parsing tasks must support short-cycle processing. Timeout settings must align with business response requirements. Most documents use table formats. Chunking logic must support table structures. Do not split complete information within a single cell.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of single or associated entries in inspection sheets and alarm records, retains complete binding between fields and units |
chunkSplitter | Split by chronological entries | Matches the chronological characteristics of documents, avoids splitting continuous inspection or alarm records across time periods |
customPdfParse | Enable structured parsing mode | Targets the table format of inspection sheets and temperature and humidity logs, accurately extracts fields and values within cells |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the file size of batch-uploaded inspection logs and historical alarm records |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Matches the parsing duration of real-time or daily updated documents, avoids timeout failures caused by large-volume log files |
chunkSettingMode | Manual configuration | Supports adjusting chunking parameters for different document types, adapts to business scenarios |
This configuration is based on FastGPT v4.17.0
Three common configuration errors
- Phenomenon: Some inspection record PDF files have no table content or missing fields after parsing. Cause: Structured parsing mode for
customPdfParseis not enabled, only the default text extraction logic is used, which cannot recognize the table structure of inspection sheets. - Phenomenon: Parsing tasks time out and fail when batch uploading daily updated alarm log files. Cause: The value set for
PARSE_FILE_TIMEOUT_SECONDSis too small, and does not match the parsing time required for large-volume log files. - Phenomenon: Parsed chunked content splits the value and unit of a single temperature and humidity record. Cause: The
chunkSizesetting is too small, orchunkSplitterdoes not split along field boundaries, resulting in separation of fields and their units.
How to verify correct configuration
- Upload a single inspection sheet PDF file, check if the parsed text retains the complete table structure and field units, and verify that
customPdfParseis enabled. - Upload a test large-volume alarm log file, confirm that the parsing task does not have timeout errors, and verify that the setting for
PARSE_FILE_TIMEOUT_SECONDSmatches the file volume requirements. - Randomly sample parsed chunked content, check that complete fields, values and units of single records are not split, and verify that the settings for
chunkSizeandchunkSplittermatch the document structure. - Check the total size of uploaded files, confirm that it does not exceed the
UPLOAD_FILE_MAX_SIZEsetting.
The values given 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 2026-10-19.