Data Characteristics
Infection control data sources typically include internal policy documents, Standard Operating Procedures (SOPs), training manuals, case analysis reports, and relevant laws and regulations. These documents are often stored as PDFs, Word files, or scanned images. Update frequency is relatively low, primarily occurring after policy and regulatory adjustments, the introduction of new medical technologies, or significant infection control incidents. Document structures often feature chapters, clauses, and appendices for policy documents, while SOPs usually contain step-by-step lists, diagrams, and tables. Fields and units may involve infection rates (percentage), microbial types (text), antibiotic dosages (mg/kg), and disinfectant concentrations (ppm), requiring strong professionalism and standardization.
Constraints on Workflow Orchestration
The characteristics of infection control regulation data impose specific requirements on workflow orchestration. First, the professional and structured nature of the documents requires knowledge base chunking to maintain contextual integrity, preventing critical clauses from being split. Second, the low update frequency means knowledge base re-indexing does not need to be frequent. However, any update requires accurate and timely full or incremental updates. Third, diverse file formats, especially scanned documents, challenge document parsing capabilities, potentially requiring pre-processing steps. Finally, questions involving specific numerical values and units require the model to have numerical reasoning capabilities and accurately match relevant data points during retrieval to ensure rigorous answers.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 500–800 characters | Balances the completeness of regulatory clauses with model processing efficiency. |
Chunk Overlap | 100 characters | Ensures contextual continuity and prevents information loss. |
Recall Count | 5–8 chunks | Balances retrieval accuracy with model input length, covering multi-dimensional information. |
Similarity Threshold | 0.75–0.85 | Suitable for highly specialized content requiring high semantic similarity. |
Rerank Count | 3 chunks | Focuses on the most relevant key information, reducing model interference. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses the parsing needs of large or complex regulatory documents. |
Common Mistakes
- During workflow debugging, model response speed is noticeably slower than direct chat testing. This often happens because the workflow introduces additional tool calls or complex logical branches, increasing processing time.
- The system prompt for the model's chat component fails to display the current date correctly. This is usually due to incorrect referencing of the system time variable provided by the platform, leading to the variable not being parsed or being parsed incorrectly.
- Workflows combining RAG knowledge bases and tool calls sometimes fail to trigger tools correctly. This is often due to improper tool trigger conditions or parameter configurations, preventing the model from recognizing and invoking the tool.
Verification Steps
- Submit questions containing specific regulatory clauses, SOP steps, and numerical queries. Check if the model's answer accurately cites the original content from the knowledge base and verifies the correctness of numerical values and units.
- Simulate a regulation update scenario by uploading a new version of a document. Observe whether the workflow correctly identifies the updated content and reflects the latest information in subsequent questions and answers.
- Test the knowledge base with various file formats (e.g., PDF, Word, scanned documents). Ensure all document formats are correctly parsed and indexed by the workflow and can be effectively retrieved.
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.