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Upload app.py
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app.py
CHANGED
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@@ -1365,7 +1365,7 @@ def analyze_news(news_text):
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# Step 6: Format the final results
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real_confidence = combined_confidence
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fake_confidence = 1 - combined_confidence
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# Step 7: Check if result should be added to knowledge base (using only Gemini confidence for RAG)
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gemini_real_confidence, gemini_fake_confidence = extract_gemini_percentage(gemini_analysis)
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gemini_max_confidence = max(gemini_real_confidence, gemini_fake_confidence)
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@@ -1393,7 +1393,7 @@ def analyze_news(news_text):
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print(f"π DEBUG: gemini_max_confidence = {gemini_max_confidence}")
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print(f"π DEBUG: RAG_CONFIDENCE_THRESHOLD = {RAG_CONFIDENCE_THRESHOLD}")
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print(f"π DEBUG: Should save? {ENABLE_ENHANCED_RAG and gemini_max_confidence > RAG_CONFIDENCE_THRESHOLD}")
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if ENABLE_ENHANCED_RAG and gemini_max_confidence
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try:
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from rag_news_manager import add_news_to_rag
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# Step 6: Format the final results
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real_confidence = combined_confidence
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fake_confidence = 1 - combined_confidence
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# Set to 0 to avoid errors
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# Step 7: Check if result should be added to knowledge base (using only Gemini confidence for RAG)
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gemini_real_confidence, gemini_fake_confidence = extract_gemini_percentage(gemini_analysis)
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gemini_max_confidence = max(gemini_real_confidence, gemini_fake_confidence)
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print(f"π DEBUG: gemini_max_confidence = {gemini_max_confidence}")
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print(f"π DEBUG: RAG_CONFIDENCE_THRESHOLD = {RAG_CONFIDENCE_THRESHOLD}")
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print(f"π DEBUG: Should save? {ENABLE_ENHANCED_RAG and gemini_max_confidence > RAG_CONFIDENCE_THRESHOLD}")
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if ENABLE_ENHANCED_RAG and gemini_max_confidence >= RAG_CONFIDENCE_THRESHOLD:
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try:
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from rag_news_manager import add_news_to_rag
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