Data Characteristics in This Category
R&D documentation in supplier audit scenarios primarily originates from quality management system files, production process regulations, batch production records, inspection reports, equipment validation files, and change control records provided by suppliers. Document updates typically follow audit cycles or trigger upon significant supplier changes, occurring quarterly, semi-annually, or annually, or revised due to unforeseen events. Document structures are complex, often containing numerous tables, nested lists, charts, and scanned images. PDF is the predominant format, followed by Word documents. Fields include material codes, batch numbers, production dates, expiration dates, test indicators, tolerance ranges, equipment models, and calibration dates. Units are diverse, including milligrams (mg), milliliters (mL), degrees Celsius (°C), Pascals (Pa), and percentages (%), often with custom abbreviations.
Constraints Imposed by These Characteristics on "Document Parsing and Chunking"
The complex structure of supplier audit documents demands high-precision document parsing, especially for accurate extraction of table content and nested lists. The presence of scanned images necessitates OCR technology, ensuring the OCR output's text layout aligns with the original document's logic. Uncertain update frequencies require the system to have efficient incremental update and version management capabilities to avoid redundant processing or missing the latest information. The diversity of fields, units, and custom abbreviations means chunking must pay close attention to contextual relevance, ensuring information within a single chunk is complete and understandable, preventing truncation that leads to critical data losing context. Furthermore, numerous specialized terms and abbreviations require chunking strategies to identify and retain this key information, reducing ambiguity in subsequent retrieval.
Configuration Settings
| Configuration Item | Recommended Value | Rationale for Recommendation |
|---|---|---|
Chunk size (Chunk Length) | 800–1200 characters | Balances contextual completeness and retrieval efficiency, avoiding excessively long chunks that lead to information redundancy or excessively short chunks that result in incomplete semantics. |
Chunk overlap (Chunk Overlap) | 100–200 characters | Ensures semantic continuity at chunk boundaries, especially when tables or long sentences span across chunks. |
File Type Whitelist | pdf, docx, xlsx | Prioritizes common audit document formats, considering content richness. |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Accommodates the parsing time for large or complex PDF documents, preventing parsing failures due to timeouts. |
OCR_ENABLED | true | Ensures text content from scanned images or pictures can be extracted and indexed. |
MAX_FILE_SIZE_MB | 100 MB | Covers the size of most audit documents, preventing inability to upload and parse due to excessive file size. |
Three Common Mistakes
- Image content does not display in conversations: This often occurs when image URLs are not correctly processed during parsing, possibly because image paths are relative and not converted to accessible absolute URLs during the parsing stage.
- Other machines on the local network cannot access the platform login page: This manifests as a
net::ERR_INCOMPerror, typically because the FastGPT service is not correctly bound to an externally accessible IP address, or a firewall is blocking relevant ports. - Critical data is lost or context is incomplete after chunking: This is common with complex tables or nested lists where the chunking algorithm fails to effectively identify structural boundaries, leading to data truncation or separation from its description.
How to Confirm Correct Configuration
- Upload a supplier audit document containing complex tables and scanned images. Check if the parsed text content is complete and well-structured, especially if table data is correctly extracted.
- Randomly select several parsed chunks. Check the semantic completeness of each chunk, ensuring critical fields (e.g., batch number, test results) and their units are within the same chunk.
- Test with documents containing pictures or charts. Verify that parsed image links are accessible and display correctly in conversations.
- Check system logs to confirm no error messages such as
TimeoutErrororParsingFailedErroroccurred during file parsing.
Note: The values provided are common starting points and should be measured against your 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 2026-09-21.