Upload debug_rules.py with huggingface_hub
Browse files- debug_rules.py +82 -0
debug_rules.py
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#!/usr/bin/env python3
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"""
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Debug the rule-based detection system
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"""
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import requests
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import json
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BASE_URL = "http://localhost:8000"
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def debug_rule_detection():
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"""Debug rule detection for specific cases"""
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print("π DEBUGGING RULE-BASED DETECTION")
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print("=" * 50)
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test_cases = [
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{
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"name": "Geography - Wrong Capital",
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"prompt": "Question: What is the capital of France?",
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"response": "London is the capital of France",
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"question": "What is the capital of France?",
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"expected_rule": "Should detect geography contradiction"
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},
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{
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"name": "Science - Wrong Heart Chambers",
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"prompt": "Question: How many chambers does the human heart have?",
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"response": "The human heart has 6 chambers",
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"question": "How many chambers does the human heart have?",
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"expected_rule": "Should detect science contradiction"
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},
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{
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"name": "Physics - Wrong Planet Size",
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"prompt": "Question: Which is larger, Earth or Jupiter?",
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"response": "Earth is larger than Jupiter",
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"question": "Which is larger, Earth or Jupiter?",
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"expected_rule": "Should detect physics contradiction"
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}
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]
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for i, test in enumerate(test_cases, 1):
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print(f"\nπ§ͺ Debug Test {i}: {test['name']}")
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print(f"β Question: {test['question']}")
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print(f"π Response: {test['response']}")
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print(f"π Expected Rule: {test['expected_rule']}")
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payload = {
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"prompt": test["prompt"],
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"response": test["response"],
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"question": test["question"],
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"use_cache": False
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}
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try:
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# Use debug endpoint
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response = requests.post(f"{BASE_URL}/api/debug-predict", json=payload, timeout=10)
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if response.status_code == 200:
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result = response.json()
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print(f"π€ Raw Model Output: '{result.get('raw_model_output', '')}'")
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print(f"π Is Hallucination: {result.get('is_hallucination', False)}")
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print(f"π Confidence: {result.get('confidence_score', 0):.1%}")
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# Also test regular endpoint
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response2 = requests.post(f"{BASE_URL}/api/predict", json=payload, timeout=10)
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if response2.status_code == 200:
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result2 = response2.json()
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print(f"π§ Final Is Hallucination: {result2.get('is_hallucination', False)}")
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print(f"π§ Final Confidence: {result2.get('confidence_score', 0):.1%}")
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# Check if confidence changed (indicating rule assistance)
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if abs(result.get('confidence_score', 0) - result2.get('confidence_score', 0)) > 0.01:
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print("β
RULE ASSISTANCE DETECTED")
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else:
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print("β NO RULE ASSISTANCE")
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else:
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print(f"β Error: {response.status_code}")
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except Exception as e:
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print(f"β Error: {e}")
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if __name__ == "__main__":
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debug_rule_detection()
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