Data Characteristics
Lead compound screening data primarily originates from internal R&D standard operating procedures (SOPs), technical guidelines, internal quality control documents, and relevant regulatory policies. These documents typically exist as PDFs, Word files, or within internal knowledge bases. Document update frequency is relatively low, with revisions mainly occurring due to changes in regulations, technological innovations, or internal process optimizations. Document structures are rigorous, containing extensive specialized terminology, flowcharts, tables, and chemical structural formulas. Common fields include compound numbers, screening methods, detection indicators, judgment criteria, and risk assessment levels. These fields often include specific units, such as nM (nanomolar), μM (micromolar), and % (percentage). The precision of these units is critical for content understanding.
Constraints on Document Parsing and Chunking
The rigorous structure and specialized terminology of lead compound screening protocol documents require the document parser to accurately identify sections, headings, and paragraph levels to maintain semantic integrity. The presence of flowcharts and tables necessitates additional image recognition or table parsing capabilities to ensure effective extraction of non-textual information. The low update frequency makes high-quality one-time parsing more critical, reducing subsequent repetitive work. The dense occurrence of measurement units and chemical structural formulas demands finer-grained chunking. Overly large chunks can dilute critical information, while overly small chunks may break contextual associations, such as separating a compound name from its corresponding screening concentration.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 500–800 characters | Balances contextual relevance of specialized terms with information density, preventing critical information from being split. |
Overlap Length | 100–150 characters | Ensures sufficient semantic overlap between adjacent chunks, improving retrieval recall, especially in process descriptions. |
Custom Chunking Rules | Chunk by specific headings, sections | Lead compound screening protocol documents often have clear chapter structures; chunking by chapter maintains semantic integrity. |
Parsing Type | Structured parsing preferred | Document structures are rigorous; structured parsing better preserves document hierarchy and table information. |
Image Parsing | Enable | Flowcharts and chemical structural formula images contain critical information and require parsing for extraction. |
Max File Size | 50 MB | SOP documents may contain many charts and diagrams, so this ensures large files can be uploaded. |
Common Pitfalls
- Flowcharts in uploaded PDF documents are not retrievable because image parsing is not enabled. This prevents image content from being converted into searchable text.
- Key compound concentration values in search results do not match corresponding screening standards. This occurs when
Chunk Lengthis too large, merging semantically distinct paragraphs and breaking information associations. - Table data in imported Word documents is not correctly recognized as independent entries. This happens when the document parser fails to correctly process complex table structures in Word documents. Check the parsing type settings.
Verification Steps
- After uploading a typical lead compound screening protocol document, use knowledge base search tests. Input key terms and compound numbers from the document to check if relevant, complete paragraphs are recalled.
- For flowcharts or table content within the document, attempt to search using textual information from the charts or tables to confirm the effectiveness of
Image Parsing. - Examine the chunked content returned in search results. Ensure each chunk contains a complete semantic unit, such as compound name, screening method, and corresponding judgment criteria, without critical information being truncated.
- Compare the original document with the chunked content in the FastGPT knowledge base. Verify that custom chunking rules work as expected, for instance, if chapter headings serve as independent chunks or chunk starting points.
Note: The values provided are common starting points. Measure them 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.