update code

app.py

@@ -36,8 +36,8 @@ def greet_json():
 @app.post("/", response_model=list[Disease])
 async def predict(query: str):
     query_embedding = model.encode(query).astype('float')
-    similarity_vectors = model.similarity(query_embedding, all_embeddings)
-    scores, indicies = torch.topk(similarity_vectors, k=len(all_embeddings))
+    similarity_vectors = model.similarity(query_embedding, corpus)
+    scores, indicies = torch.topk(similarity_vectors, k=len(corpus))
     id_ = df.iloc[indicies]
     id_ = df.drop_duplicates("label")
     scores = scores[id_.index]