Update main.py

main.py

@@ -673,7 +673,7 @@ from underthesea import word_tokenize
 from nltk.tokenize import word_tokenize as word_tokenize_en
 from numpy import zeros,zeros_like
 from scipy.spatial.distance import cosine
-
+import warnings
 async def validate_similarity(request):
     req = await request.json()
     sent1, sent2 = req['sentences']
@@ -699,8 +699,14 @@ async def validate_similarity(request):
             vect2 += w2v_vi.get_vector(t)
 
     # Calculate similarity using cosine similarity: This metric measures the cosine of the angle between two embedding vectors. A higher cosine similarity indicates more similar sentences.
-    sim = 1 - cosine(vect1, vect2) >= 0.8
-    return JSONResponse({"isSimilar": str(sim)})
+    with warnings.catch_warnings():
+        warnings.simplefilter('error', RuntimeWarning)
+        try:
+            sim = 1 - cosine(vect1, vect2) >= 0.8
+        except RuntimeWarning as e:
+            return JSONResponse({"isSimilar": "False"})
+            
+        return JSONResponse({"isSimilar": str(sim)})
 
 async def get_cached_img_from_disk(request):
     _fn = request.path_params['fn']