Data Characteristics in this Category
Infectious disease protocols and SOP documents typically originate from guidelines, clinical pathways, and treatment plans published by official bodies such as the National Health Commission, the World Health Organization (WHO), and the U.S. Centers for Disease Control and Prevention (CDC). These documents are primarily in PDF and DOCX formats. They feature a rigorous structure, covering disease definitions, diagnostic criteria, treatment principles, and prevention and control measures. Update frequency is relatively high, especially with emerging infectious diseases or antibiotic resistance issues, potentially undergoing several revisions annually. Documents contain extensive medical terminology, drug names, dosage units (e.g., mg/kg, IU), time units (e.g., hours, days), and laboratory test indicators (e.g., CRP, PCT). Some documents also cite epidemiological data, including geographical distribution and population characteristics.
Constraints on "Deployment and Upgrade" due to these Characteristics
The specialized nature and high update frequency of infectious disease protocol documents impose specific requirements on FastGPT's deployment and upgrade processes. Accurate recognition of medical terminology necessitates optimized tokenization strategies to avoid ambiguity. High update frequency means the knowledge base must support rapid incremental updates and version management, ensuring retrieved information is current. Key information such as dosages, units, and time within documents requires the knowledge base to accurately extract and maintain contextual relevance during parsing, preventing numerical errors in Q&A. The rigorous structure and multi-level headings of documents require considering the logical integrity of document segmentation during vectorization to improve recall precision. Furthermore, sensitive disease information demands higher standards for private deployment and data security compliance.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk size (Chunk Length) | 800–1200 characters | Ensures completeness of medical concepts and logical units, reducing semantic fragmentation |
Recall count (Recall Count) | Top 5–8 entries | Covers multiple aspects of relevant protocols and SOPs, improving answer comprehensiveness |
Similarity threshold (Similarity Threshold) | 0.75–0.85 | Balances precise matching of professional terms with recall of semantically similar protocols |
Rerank result count (Rerank Return Count) | Top 3 entries | Focuses on the most relevant and important protocol entries, enhancing answer accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Handles large PDF/DOCX files, preventing parsing timeouts |
UPLOAD_FILE_MAX_SIZE | 256 MB | Accommodates protocol documents containing numerous charts and attachments |
Three Common Pitfalls
- After a knowledge base update, the model's responses still cite outdated protocol content. This occurs because the incremental update mechanism did not trigger correctly or the index was not rebuilt promptly.
- When a user asks about a specific drug dosage, the answer contains unit errors or numerical discrepancies. This happens because the document parsing failed to correctly identify and extract the association between numbers and units.
- After private deployment, file uploads result in a
permission deniederror. This is due to incorrect read/write permissions configured for the file storage path.
How to Verify Correct Configuration
- Upload the latest version of an infectious disease diagnosis and treatment guideline. Ask questions about key disease diagnostic criteria or treatment plans within it. Check if the answers align with the new content.
- Randomly select multiple protocol documents. Ask questions involving specific drug dosages or test indicator values. Verify the accuracy of numbers and units in the answers.
- Simulate high concurrent access. Observe system response speed and resource utilization to confirm system stability meets expected metrics.
- Inspect the file storage directory. Confirm uploaded documents are stored in the expected path and there are no permission access anomalies.
The values provided are common starting points and should be measured against specific 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.