Update app.py

app.py

@@ -53,7 +53,7 @@ def process_row(row, vendor_data, vendor_scores):
     for vendor_name, vendor_vectors in vendor_data.items():
         cosine_similarities = semantic_search(row[0], vendor_vectors)
         most_similar_index = np.argmax(cosine_similarities)
-        vendor_score = vendor_scores[vendor_name]  # Get the vendor's score
+        vendor_score = vendor_scores[vendor_name]['score']  # Get the vendor's score
         scores[vendor_name] = row['score_client'] * vendor_score  # Multiply vendor score with client priority
     row_scores = pd.Series(scores)
     combined_row = pd.concat([row, row_scores])