Add inference script

hindi_embeddings.py

@@ -510,6 +510,13 @@ class HindiEmbedder:
         Returns:
             Similarity scores
         """
+        # Convert single strings to lists for consistent handling
+        if isinstance(texts1, str):
+            texts1 = [texts1]
+        
+        if texts2 is not None and isinstance(texts2, str):
+            texts2 = [texts2]
+            
         embeddings1 = self.encode(texts1)
         
         if texts2 is None:
@@ -522,10 +529,15 @@ class HindiEmbedder:
             
             if len(texts1) == len(texts2):
                 # Compute pairwise similarity when the number of texts match
-                return np.array([
+                similarities = np.array([
                     cosine_similarity([e1], [e2])[0][0]
                     for e1, e2 in zip(embeddings1, embeddings2)
                 ])
+                
+                # If there's just one pair, return a scalar
+                if len(similarities) == 1:
+                    return similarities[0]
+                return similarities
             else:
                 # Return full similarity matrix
                 return cosine_similarity(embeddings1, embeddings2)