Ib Summarizer

Examples

# Basic usage
python scripts/main.py /path/to/IB.pdf

# Output to JSON file
python scripts/main.py /path/to/IB.pdf -o summary.json -f json

# English output
python scripts/main.py /path/to/IB.docx -l en -o summary.md

Output Structure

Markdown Format

# IB Safety Information Summary

## Basic Drug Information
- **Drug Name**: XXX
- **Version**: X.X
- **Date**: YYYY-MM-DD

## Core Safety Information

### Known Adverse Reactions
| System Organ Class | Adverse Reaction | Incidence | Severity |
|-------------|---------|--------|---------|
| ... | ... | ... | ... |

### Contraindications
- ...

### Warnings and Precautions
- ...

### Drug Interactions
- ...

### Special Populations
| Population | Precautions |
|-----|---------|
| Pregnant women | ... |
| Lactating women | ... |
| Children | ... |
| Elderly | ... |
| Hepatic/renal impairment | ... |

### Overdose
- Symptoms: ...
- Management: ...

### Safety Update History
| Version | Date | Update Content |
|-----|------|---------|
| ... | ... | ... |

JSON Format

{
  "drug_info": {
    "name": "Drug Name",
    "version": "Version Number",
    "date": "Date"
  },
  "core_safety_info": {
    "adverse_reactions": [...],
    "contraindications": [...],
    "warnings": [...],
    "drug_interactions": [...],
    "special_populations": {...},
    "overdose": {...},
    "safety_updates": [...]
  }
}

Dependencies

• Python 3.8+
• PyPDF2 / pdfplumber (PDF parsing)
• python-docx (Word parsing)
• Optional: openai / anthropic (for AI-enhanced extraction)

Installation

pip install -r requirements.txt

Notes

1. Input documents should be readable PDF or Word format
2. Scanned PDFs require OCR processing first
3. For complex table structures, manual verification may be needed
4. Information extracted by this tool is for reference only and does not constitute medical advice

Risk Assessment

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support