Update app.py

app.py

@@ -7,6 +7,7 @@ from tools.final_answer import FinalAnswerTool
 import nltk
 import networkx as nx
 from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.metrics.pairwise import cosine_similarity
 from nltk.tokenize import sent_tokenize
 
 # Ensure necessary NLTK resources are downloaded
@@ -57,7 +58,7 @@ def extract_sent(doc: str, top_n: int = 3) -> list:
         sentence_vectors = vectorizer.fit_transform(sentences)
 
         # Step 3: Compute similarity matrix (cosine similarity)
-        similarity_matrix = (sentence_vectors * sentence_vectors.T).toarray()
+        similarity_matrix = cosine_similarity(sentence_vectors)
 
         # Step 4: Create a graph where nodes are sentences, and edges are similarities
         sentence_graph = nx.from_numpy_array(similarity_matrix)