What the Data for This Category Looks Like
Internal office documents for pharmaceutical distribution primarily originate from procurement contracts, drug regulatory compliance documents, cold chain temperature and humidity inspection records, employee job manuals, and training materials. Document update cadence varies by business scenario: procurement contracts are updated with each batch of procurement tasks, regulatory documents are updated irregularly alongside policy adjustments, temperature and humidity records are updated daily per inspection cycles, and employee manuals and training materials are updated annually or when job roles are adjusted. Document structures include structured tables such as drug lists and procurement ledgers, long-text policy explanations, and semi-structured inspection records. Exclusive fields include generic drug names, production batch numbers, cold chain temperature thresholds, purchase order numbers, and others. Units include milligrams, degrees Celsius, batch numbers, and other professional measurement identifiers.
Constraints Imposed by These Characteristics on Document Parsing and Chunking
Pharmaceutical distribution documents mix structured ledgers, unstructured policies, and semi-structured inspection records. Parsing must accurately extract exclusive fields such as drug batch numbers and temperature thresholds to avoid field misalignment or information loss. Long policy texts and short batch inspection records coexist. Chunking must balance the coherence of long content and the integrity of short content, avoiding overly long chunks that reduce retrieval efficiency or overly fragmented chunks that cause semantic breaks. Documents are updated frequently alongside procurement, inspection, and other business activities. The parsing process must support rapid batch processing to avoid overall efficiency loss from prolonged single-task execution. Some documents include embedded tables and job-specific annotations. Parsing must retain the original format hierarchy to ensure compliance documents match the original content and formatting.
Configuration Settings
The following configurations apply to FastGPT v4.17.0, optimized for document characteristics in pharmaceutical distribution scenarios:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the mixed length of long policy texts and short inspection ledgers in pharmaceutical distribution documents, avoiding overly long or overly fragmented chunks |
chunkSplitter | Split by paragraph + title | Retains document hierarchy structure, compatible with documents with mixed formats such as regulatory policy titles and procurement ledger entries |
customPdfParse | Enable MinerU adaptation mode | Adapts to complex tables and embedded annotations in pharmaceutical distribution PDF documents, improving parsing accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Prevents task interruptions from excessive parsing time when processing batch procurement ledgers and long policy documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to batch-uploaded cold chain temperature and humidity record compressed packages and large regulatory files |
chunkSettingMode | Semi-automatic mode | Adjusts chunking parameters for different document types (ledgers, policies, records), balancing versatility and accuracy |
Three Common Mistakes
- Scenario: After uploading some properly formatted docx documents, the parsing task returns no results or displays a parsing failure. Cause: The document contains pharmaceutical distribution-specific annotation fields or nested tables, and the default parsing engine cannot adapt to these non-general formats.
- Scenario: After uploading a PDF of a drug procurement ledger, the chunking result splits table content into scattered text, failing to retain column alignment and field correspondence. Cause: Chunking parameters are not optimized for structured table documents, or the mixed format parsing mode is not enabled.
- Scenario: When batch uploading cold chain temperature and humidity record PDFs, tasks time out or prompt insufficient video memory. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted to adapt to large-volume batch documents, and the deployment environment is not properly configured with GPU acceleration resources.
How to Verify Proper Configuration
- A single pharmaceutical regulatory policy PDF under 100 MB is uploaded, and the parsed text is checked to confirm retention of the original title hierarchy and paragraph structure.
- A docx document containing a drug procurement ledger is uploaded, and the chunking result is checked to confirm that table fields are complete, with no scattered split column content.
- The parsing task log is reviewed to confirm that the
PARSE_FILE_TIMEOUT_SECONDSparameter does not trigger a timeout error, and that the deployment environment's GPU resources are being called normally. chunkSettingModeis adjusted to semi-automatic mode, chunk length is tested separately for different document types, and content coherence is confirmed to meet business requirements.
The values listed are common starting points and should be evaluated against samples from the relevant use case.
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.