Data Characteristics for This Category
Lead compound screening data typically originates from high-throughput screening reports, compound library information, biological activity assay results, and structure-activity relationship (SAR) data. Data update frequency is irregular, potentially updating with batch screening progress or undergoing large-scale updates when new compound libraries are introduced. Document structures are diverse, including standardized data tables (CSV, Excel), PDF-formatted experimental reports, and compound structure files (SDF, MOL). Fields and units are highly specialized. For example, activity data might use IC50 (nM) or Ki (nM); compound structure data involves SMILES strings and InChIKey; physicochemical properties include LogP and molecular weight (Da). Data often contains redundant information or unstructured descriptions, requiring pre-processing.
Constraints Imposed by These Characteristics on "Deployment and Upgrade"
The diversity and specialized nature of lead compound screening data impose specific requirements on FastGPT's deployment and upgrade. The uncertain update frequency of data sources necessitates flexible scheduled task configurations, supporting on-demand or periodic synchronization with external databases or file systems. The variety of document structures, especially the inclusion of numerous unstructured experimental reports, requires FastGPT to integrate robust document parsing capabilities during deployment, such as support for PDF OCR and intelligent table recognition. Specialized fields and units constrain the precision of model training and retrieval recall, requiring specific embedding models and tokenization strategies to accurately understand biochemical terminology. Furthermore, the unique nature of compound structure data may require customized pre-processing scripts to convert structural information into vectorizable text or features, ensuring effective retrieval results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Accommodates high-throughput screening reports and large compound library files, ensuring successful uploads. |
maxContext | 3000 Tokens | Lead compound screening reports often contain extensive experimental details, requiring a longer context window to maintain information completeness. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large PDF reports and complex tables can take a long time; this prevents timeout interruptions. |
Chunk size | 800 characters | Balances the completeness of biological activity data and experimental descriptions, preventing truncation of critical information. |
Recall count | Top 8 entries | Increases retrieval result coverage, ensuring relevant compound information can be matched from multiple dimensions. |
Similarity threshold | 0.75 | Balances accuracy and recall rate, filtering out highly relevant lead compound data. |
Rerank result count | Top 5 entries | Refines results further through a reranking model based on initial recall, focusing on the most relevant information. |
Three Common Mistakes
- After updating knowledge base content, the AI assistant's responses still rely on old data. This happens because the scheduled synchronization task is incorrectly configured or the external data source connection is interrupted.
- When uploading large PDF experimental reports, the system displays a "request timeout" error. This occurs because
PARSE_FILE_TIMEOUT_SECONDSis set too short, preventing file parsing from completing. - When querying compound activity data, the results contain many irrelevant or low-similarity entries. This happens because the
Similarity threshold(similarity threshold) is set too low, or the text segmentation strategy does not adequately consider specialized terminology.
How to Confirm Correct Configuration
- Upload a lead compound screening report containing various data types (PDF, CSV, SDF). Verify all files are successfully parsed and imported into the knowledge base.
- Execute a complete knowledge base synchronization process. Then, query the most recently updated data to confirm the synchronization task works as expected.
- For typical lead compound structure or activity queries, test the AI assistant's responses. Compare the results with the original data to confirm retrieval accuracy and relevance.
The values provided are common starting points and should be measured against the reader's 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.