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"""
Quick Setup Script for Professional Hallucination Detector
This script helps you:
1. Install dependencies
2. Configure detection method
3. Test the installation
"""
import os
import sys
def main():
print("""
╔════════════════════════════════════════════════════════════╗
║ Professional Hallucination Detector Setup ║
╚════════════════════════════════════════════════════════════╝
This upgrade improves hallucination detection:
📊 Before (LLM-as-a-Judge):
• Accuracy: 60-75%
• Speed: 2-5 seconds per check
• Cost: High (LLM API calls)
📊 After (Vectara + NLI):
• Accuracy: 85-95%
• Speed: 0.3-0.8 seconds per check
• Cost: ~90% reduction
════════════════════════════════════════════════════════════
Steps to complete setup:
1️⃣ Install dependencies:
python install_hallucination_detector.py
2️⃣ Configure detection method (optional):
Edit hallucination_config.py
Choose: 'vectara', 'nli', or 'hybrid' (recommended)
3️⃣ Test the detector:
python test_hallucination_detector.py
4️⃣ Compare with old method:
python compare_hallucination_methods.py
════════════════════════════════════════════════════════════
The system will automatically:
• Use professional detector if available
• Fallback to LLM method if needed
• No changes to your existing code required!
════════════════════════════════════════════════════════════
""")
print("\n🚀 Ready to start? Run:")
print(" python install_hallucination_detector.py\n")
if __name__ == "__main__":
main()
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