Update pages/type_text.py

pages/type_text.py

@@ -3,10 +3,8 @@ import pandas as pd
 from io import StringIO
 import json
 import torch
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM #AutoModelForTokenClassification
+from transformers import pipeline, # AutoTokenizer, AutoModelForCausalLM, AutoModelForTokenClassification
 from sentence_transformers import SentenceTransformer, util 
-#import lmdeploy
-#import turbomind as tm 
 
 import os
 os.getenv("HF_TOKEN")
@@ -30,15 +28,13 @@ def convert_json(df:pd.DataFrame):
     #st.json(json_string, expanded=True)
     return json_string
 
-#st.title("📘SBS mapper")
-
 INTdesc_input = st.text_input("Type internal description and hit Enter", key="user_input") 
 
 createSBScodes, right_column = st.columns(2)
 createSBScodes_clicked = createSBScodes.button("Map to SBS codes", key="user_createSBScodes")
 right_column.button("Reset", on_click=on_click)
-
-numMAPPINGS_input = 5
+"""
+#numMAPPINGS_input = 5
 #numMAPPINGS_input = st.text_input("Type number of mappings and hit Enter", key="user_input_numMAPPINGS")
 #st.button("Clear text", on_click=on_click)
 
@@ -128,4 +124,5 @@ if INTdesc_input is not None and createSBScodes_clicked == True:
         textbutton = st.download_button(label="📥 Download .txt", data=convert_df(dfALL), file_name= "results.text", mime='text/plain',  key='text_b')
     with b3:
         #jsonbutton = download_button(results, "results.json", "📥 Download .json")
-        jsonbutton = st.download_button(label="📥 Download .json", data=convert_json(dfALL), file_name= "results.json", mime='application/json',  key='json_b')
+        jsonbutton = st.download_button(label="📥 Download .json", data=convert_json(dfALL), file_name= "results.json", mime='application/json',  key='json_b')
+"""