modified code and add files

app.py

@@ -41,9 +41,9 @@ async def predict(symptoms: Symptoms):
     similarity_vectors = model.similarity(query_embedding, corpus)[0]
     scores, indicies = torch.topk(similarity_vectors, k=len(corpus))
     # id_ = df.iloc[indicies].reset_index(drop=True)
-    df = df.iloc[indicies]
+    ls = df.iloc[indicies].copy()
     # id_ = id_.drop_duplicates("label")
-    df["scores"] = scores
+    ls["scores"] = scores
     # scores = scores[id_.index]
     # diseases = label_encoder.inverse_transform(id_.label.values)
     # id_ = id_.label.values
@@ -51,5 +51,5 @@ async def predict(symptoms: Symptoms):
                       "name": value[1],
                       "url" : value[2],
                       "score" : value[3]})
-                      for value in zip(df.index, df["name"], df["url"], df["scores"])]
+                      for value in zip(df.index, ls["name"], ls["url"], ls["scores"])]
     return diseases