chnaging logo file

appStore/multiapp.py

@@ -45,7 +45,7 @@ class MultiApp:
     def run(self):
         
         st.sidebar.write(format_func=lambda app: app['title'])
-        image = Image.open('docStore/img/giz_sdsn_small.jpg')
+        image = Image.open('docStore/img/sdsn.jpg')
         st.sidebar.image(image, width =200)
        
         with st.sidebar:

utils/keyword_extraction.py

@@ -49,8 +49,7 @@ def extract_topn_from_vector(feature_names, sorted_items, top_n=10):
         #keep track of feature name and its corresponding score
         score_vals.append(round(score, 3))
         feature_vals.append(feature_names[idx])
-    #create a tuples of feature,score
-    #results = zip(feature_vals,score_vals)
+
     results= {}
     for idx in range(len(feature_vals)):
         results[feature_vals[idx]]=score_vals[idx]
@@ -128,11 +127,6 @@ def textrank(textdata:Text, ratio:float = 0.1, words:int = 0)->List[str]:
     results: extracted keywords
     """
     if words == 0:
-        # try:
-        #     words = int(config.get('sdg','TOP_KEY'))
-        #     results = keywords.keywords(textdata, words = words).split("\n")    
-        # except Exception as e:
-        #     logging.warning(e)
         logging.info("Textrank using defulat ratio value = 0.1, as no words limit given")
         results = keywords.keywords(textdata, ratio= ratio).split("\n")
     else:

utils/lexical_search.py

@@ -3,7 +3,6 @@ from haystack.document_stores import InMemoryDocumentStore
 import spacy
 import re
 from spacy.matcher import Matcher
-import streamlit as st
 from markdown import markdown
 from annotated_text import annotation
 from haystack.schema import Document