What this category’s data looks like
Data for this category comes from design history files, device and material batch records, MES systems, clean environment monitoring equipment, sterilization equipment, and inspection and calibration systems. Updates are made after each production batch or each device is completed, with data synced in accordance with fixed environmental monitoring plans. Daily documents include production process specifications, batch production records, clean zone operation records, sterilization batch records, inspection reports, software version records, and adverse event traceability materials. Fields include unique device identification, sterilization batch number, temperature and humidity monitoring values, and biocompatibility test results, with professional units such as degrees Celsius and minutes attached.
What constraints do these characteristics impose on the "document parsing and chunking" link
A single document can reach 100,000 Chinese characters or ten-thousand-row tables. This requires the parsing module to support large file processing to avoid timeouts. Documents contain both structured batch data and non-standardized process text. Chunking logic must balance table row groups and paragraph semantics to avoid breaking critical associated information. Professional fields such as unique device identification and sterilization parameters must be fully retained, and chunk boundaries must avoid interrupting these fields. Frequently updated batch data requires incremental sync after chunking to reduce resource consumption from repeated full document parsing. For bidding scenarios, compliant document fragments must accurately match bidding review requirements, so chunking must prioritize retaining core content such as controlled inspection and sterilization validation.
How to set the configuration
The following configurations are formulated based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapt to the upload needs of single 100,000-word Word or ten-thousand-row Excel documents, avoid large files being blocked |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Cover the parsing time of large-volume documents, avoid task termination due to mid-parsing timeout |
chunkSplitter | Hybrid chunking mode | Adapt to document types with mixed structured tables and unstructured text, retain complete field association integrity |
chunkSize | 800–1200 characters | Balance professional field integrity and vector retrieval accuracy, adapt to long paragraphs and table row groups in medical device documents |
chunkSettingMode | Manual configuration | Adjust chunking parameters for category-specific document structures, no need to rely on general default configurations |
customPdfParse | Enabled | Retain table formats and field typesetting in PDF documents, avoid loss of structured information after parsing |
Three common mistakes
- Phenomenon: Timeout error returned when parsing 100,000-word Word or ten-thousand-row Excel documents, or task status shows parsing failed. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, the default duration is insufficient to cover the parsing time of large-volume documents. - Phenomenon: Chunked fragments exceed the length limit supported by the vector model, leading to fragment truncation or reduced matching accuracy during retrieval. Cause: The
chunkSizeparameter is not adjusted according to the professional field length of category documents, using general chunking lengths results in overly long fragments. - Phenomenon: Batch data JSON arrays exported from the database cannot be directly used for chunking, additional code is required to complete field extraction. Cause: Structured data parsing nodes are not enabled, passing raw JSON data directly causes the chunking module to fail to recognize structured field associations.
How to confirm the configuration is correct
- Upload a typical 100,000-word Word process specification document for the category, verify that the parsing task completes within the configured
PARSE_FILE_TIMEOUT_SECONDSduration, with no timeout errors. - Import ten-thousand-row Excel batch data, check that the parsing result retains complete structured fields and associated information.
- Adjust the
chunkSizeparameter, randomly extract chunked fragments, confirm that key professional fields such as unique device identification and sterilization parameters are not truncated. - Submit new batch record data, verify that the chunking module only processes incremental content, with no full repeated parsing behavior.
The values provided are common starting points and should be measured against the reader's own samples.