Update app.py

app.py

@@ -103,7 +103,7 @@ def tokenize(tokenizer, input_texts, eod_id, max_length):
     batch_dict = tokenizer.pad(batch_dict, padding=True, return_tensors="pt")
     return batch_dict
 
-def compute_similarity(embedder: QwenEmbedder, text1: str, text2: str) -> float:
+def compute_similarity(embedder: QwenEmbedder, text1: str, text2: str, model_choice: str = None, embedding_dim: int = None) -> float:
     embeddings = embedder.get_embeddings([text1, text2])
     similarity = torch.cosine_similarity(embeddings[0:1], embeddings[1:2]).item()
     return round(similarity, 3)
@@ -693,7 +693,7 @@ def create_demo():
                             similarity_score = gr.Number(label="Similarity Score")
                         
                         similarity_btn.click(
-                            fn=lambda t1, t2, m, d: process_with_embedder('compute_similarity', t1, t2, m, d),
+                            fn=lambda t1, t2, m, d: process_with_embedder('compute_similarity', t1, t2),
                             inputs=[text1, text2, model_choice, embedding_dim],
                             outputs=similarity_score
                         )