Delete app.py

app.py

@@ -1,154 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Tue Nov 22 09:54:41 2022
-
-@author: luol2
-"""
-
-
-
-import streamlit as st
-import argparse
-from src.nn_model import bioTag_CNN,bioTag_BERT,bioTag_Bioformer
-from src.dic_ner import dic_ont
-from src.tagging_text import bioTag
-import os
-import time
-import json
-import sys
-
-
-st.set_page_config(
-    page_title="PhenoTagger",
-    page_icon=":shark:",
-    #  layout="wide",
-    initial_sidebar_state="expanded",
-    menu_items={
-        'Get Help': 'https://www.extremelycoolapp.com/help',
-        'Report a bug': "https://www.extremelycoolapp.com/bug",
-        'About': "# This is a header. This is an *extremely* cool app!"
-    }
-)
-st.title('PhenoTagger Demo')
-
-
-
-
-    
-
-
-# with st.spinner('Model is being loaded..'):
-  
-#   print('load model done!')
- 
-
-
-    
-with st.form(key="my_form"):
-        
-        @st.cache(allow_output_mutation=True)
-        def load_model():
-            ontfiles={'dic_file':'./dict_new/noabb_lemma.dic',
-                      'word_hpo_file':'./dict_new/word_id_map.json',
-                      'hpo_word_file':'./dict_new/id_word_map.json'}
-            
-            # if para_set['model_type']=='cnn':
-            #     vocabfiles={'w2vfile':'../vocab/bio_embedding_intrinsic.d200',   
-            #                 'charfile':'../vocab/char.vocab',
-            #                 'labelfile':'../dict_new/lable.vocab',
-            #                 'posfile':'../vocab/pos.vocab'}
-            #     modelfile='../models/cnn_p5n5_b128_95_hponew1.h5'
-            
-            # elif para_set['model_type']=='bioformer':
-            vocabfiles={'labelfile':'./dict_new/lable.vocab',
-                        'config_path':'./vocab/bioformer-cased-v1.0/bert_config.json',
-                        'checkpoint_path':'./vocab/bioformer-cased-v1.0/bioformer-cased-v1.0-model.ckpt-2000000',
-                        'vocab_path':'./vocab/bioformer-cased-v1.0/vocab.txt'}
-            modelfile='./vocab/bioformer_p5n5_b64_1e-5_95_hponew3.h5'
-            # else:
-            #     print('Model type is wrong, please select cnn or bioformer.')
-            #     sys.exit()
-            
-        
-            biotag_dic=dic_ont(ontfiles)    
-        
-            # if para_set['model_type']=='cnn':
-            #     nn_model=bioTag_CNN(vocabfiles)
-            #     nn_model.load_model(modelfile)
-            # elif para_set['model_type']=='bioformer':
-            nn_model=bioTag_Bioformer(vocabfiles)
-            session=nn_model.load_model(modelfile)
-            test_tag='1232'
-            return nn_model,biotag_dic,test_tag,session
-    
-    
-        #hyper-parameter
-        st.sidebar.header("Hyperparameter Settings")
-        sbform = st.sidebar.form("Hyper-paramiters")
-        # para_model=sbform.selectbox('Model', ['cnn', 'bioformer'])
-        para_overlap=sbform.selectbox('Return overlapping concepts', ['True', 'False'])
-        para_abbr=sbform.selectbox('Identify abbreviations', ['True', 'False'])
-        para_threshold = sbform.slider('Threshold:', min_value=0.5, max_value=0.95, value=0.95, step=0.05)
-        sbform.form_submit_button("Setting")
-        
-        st.write('parameters:', para_overlap,para_abbr,para_threshold)
-        nn_model,biotag_dic,test_tag,session=load_model()
-        
-        
-        input_text = st.text_area(
-            "Paste your text below (max 500 words)",
-            height=510,
-        )
-
-        MAX_WORDS = 500
-        import re
-        res = len(re.findall(r"\w+", input_text))
-        if res > MAX_WORDS:
-            st.warning(
-                "⚠️ Your text contains "
-                + str(res)
-                + " words."
-                + " Only the first 500 words will be reviewed. Stay tuned as increased allowance is coming! 😊"
-            )
-
-            input_text = input_text[:MAX_WORDS]
-
-        submit_button = st.form_submit_button(label="✨ Get me the data!")
-        
-        if para_overlap=='True':
-            para_overlap=True
-        else:
-            para_overlap=False
-        if para_abbr=='True':
-            para_abbr=True
-        else:
-            para_abbr=False
-        para_set={
-                  #model_type':para_model, # cnn or bioformer
-                  'onlyLongest':para_overlap, # False: return overlap concepts, True only longgest
-                  'abbrRecog':para_abbr,# False: don't identify abbr, True: identify abbr
-                  'ML_Threshold':para_threshold,# the Threshold of deep learning model
-                  }
-    
-    
-
-if not submit_button:
-    st.stop()
-        
-
-st.markdown(f"""**Results:**\n""")
-# print('dic...........:',biotag_dic.keys())
-print('........:',test_tag)
-print('........!!!!!!:',input_text)
-print('...input:',input_text)
-tag_result=bioTag(session,input_text,biotag_dic,nn_model,onlyLongest=para_set['onlyLongest'], abbrRecog=para_set['abbrRecog'],Threshold=para_set['ML_Threshold'])
-for ele in tag_result:
-    start = ele[0]
-    last = ele[1]
-    mention = input_text[int(ele[0]):int(ele[1])]
-    type='Phenotype'
-    id=ele[2]
-    score=ele[3]
-    output=start+"\t"+last+"\t"+mention+"\t"+id+"\n"
-    st.info(output)
-