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Fixed comparison bug
Browse files- comparison.py +6 -17
comparison.py
CHANGED
@@ -2,8 +2,7 @@ import json
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import numpy as np
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from typing import Dict, List, Tuple, Any
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from
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# from category_matching import hybrid_category_matching
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from similarity import hybrid_ingredient_matching
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from api_utils import process_in_parallel, rank_ingredients_openai
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@@ -96,16 +95,10 @@ def compare_ingredient_methods(products: List[str], ingredients_dict: Dict[str,
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chicory_data = chicory_results[product]
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if isinstance(chicory_data, dict):
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# Handle different response formats based on match type
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chicory_matches.append((ingredient, confidence))
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else: # categories
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category = chicory_data.get("category", "")
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confidence = chicory_data.get("confidence", 0)
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if category and confidence >= confidence_threshold:
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chicory_matches.append((category, confidence))
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comparison_results[product]["chicory"] = chicory_matches
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@@ -147,11 +140,7 @@ def compare_ingredient_methods(products: List[str], ingredients_dict: Dict[str,
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else:
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# Convert candidates to the expected format
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candidate_dict = {c[0]: c[0] for c in candidates}
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print(f"Expanded description: {expanded_descriptions.get(product, '')}")
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print(f"Expanded product: {expanded_product_desc.get(product, '')}")
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print(f"Categories: {candidate_dict}")
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results = hybrid_category_matching_voyage(
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products=[product],
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categories=candidate_dict,
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embedding_top_n=embedding_top_n,
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import numpy as np
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from typing import Dict, List, Tuple, Any
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from category_matching import hybrid_category_matching
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from similarity import hybrid_ingredient_matching
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from api_utils import process_in_parallel, rank_ingredients_openai
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chicory_data = chicory_results[product]
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if isinstance(chicory_data, dict):
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# Handle different response formats based on match type
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ingredient = chicory_data.get("ingredient", "")
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confidence = chicory_data.get("confidence", 0)
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if ingredient and confidence >= confidence_threshold:
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chicory_matches.append((ingredient, confidence))
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comparison_results[product]["chicory"] = chicory_matches
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else:
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# Convert candidates to the expected format
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candidate_dict = {c[0]: c[0] for c in candidates}
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results = hybrid_category_matching(
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products=[product],
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categories=candidate_dict,
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embedding_top_n=embedding_top_n,
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