What Data Falls Under This Category?
This category of data comes from EHS departments and inspection and maintenance teams of manufacturing enterprises such as chemical and metallurgical plants. It covers documents including risk identification records, hot work permits and confined space work tickets, environmental monitoring ledgers, hazardous waste disposal lists, and more. Data sources include regulatory standards, online environmental monitoring systems, gas detectors, personnel qualification documents, equipment isolation lists, and supervision platforms. Update frequencies include new records generated for each operation, real-time synchronization of monitoring data, and regular ledger updates. Documents contain structured tables and unstructured text. Fields include work order numbers, gas concentration values, qualification validity periods, disposal volumes, and more, with units such as ppm, cubic meters, and days.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Stage?
Mixed document types include structured tables and unstructured text. Chunking rules must preserve field integrity. This avoids splitting that breaks associated information in work tickets and ledgers. Diverse data sources and high-frequency update rhythms require parsing processes to support efficient batch processing. They also require controlling single-file parsing duration. Clear business fields and units require retaining contextual associations during chunking. This ensures precise matching of key information such as work order numbers and monitoring values during retrieval. Different import formats are supported, such as PDF work tickets and Excel monitoring sheets. Parsing tools must adapt to these formats to avoid field loss.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the text length of work tickets and monitoring records. It preserves complete context for a single work order. |
chunkSplitter | Split by paragraph + table | Separates structured table data and unstructured text. It avoids splitting that breaks field associations. |
customPdfParse | Enabled | Accurately extracts form fields from work tickets and rectification reports. It preserves format and content associations. |
UPLOAD_FILE_MAX_SIZE | 100 MB | Supports batch uploads of quarterly monitoring reports and annual hazardous waste ledgers. It prevents upload failures. |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Processes PDFs with multi-page monitoring data or large Excel sheets. It prevents parsing timeouts. |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types. These include work tickets, ledgers, and monitoring data, to match business fields. |
Three Common Configuration Mistakes
- After uploading an Excel-format hazardous waste ledger, knowledge base retrieval cannot extract hazardous waste generation volume values from the table. The cause is failure to configure table-based chunking rules. Splitting only by text lines leads to loss of table fields.
- Uploaded hot work ticket PDFs display normally in the knowledge base. Generated responses do not include gas detection value content from the work tickets. The cause is failure to enable
customPdfParse. This leads to incomplete parsing of form fields in the PDF. - Documents chunked locally with one vector model are uploaded to a FastGPT v4.17.0 server. When a different vector model is used, retrieval results include a large number of irrelevant entries. The cause is that the local chunking context boundary does not match the embedding logic of the server-side model. This leads to broken semantic associations.
How to Verify Proper Configuration
- Upload a single hot work ticket PDF. Check if the parsed text includes complete fields such as work order number, gas detection values, and approver.
- Import a hazardous waste ledger Excel file. Verify that structured data such as hazardous waste name, generation volume, and disposal unit can be extracted from the table during retrieval.
- Batch upload 10 different types of EHS documents. Check if upload and parsing tasks complete within the time set by
PARSE_FILE_TIMEOUT_SECONDS. - Switch the vector model. Retrieve the same document fragment. Verify that the relevance of semantic matching results meets business expectations.
The values listed here are common starting points. They should be evaluated against the reader's own samples.