chaging keyword radio to checkbox

appStore/info.py

@@ -7,7 +7,7 @@ def app():
         st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
     
     st.markdown("<h2 style='text-align: center;  \
-                      color: black;'> Policy Action Tracker Manual</h2>", 
+                      color: black;'> Climate Policy Action Tracker Manual</h2>", 
                       unsafe_allow_html=True)
 
     
@@ -79,12 +79,6 @@ def app():
         consequence, the open-source web application aims to support the process\
          through suitable AI-powered and NLP methods. In the following, the \
         application’s functionalities are explained in more detail.
-        <ul>
-        <li>Analizing the policy document</li>
-        <li>finding SDG related content</li> 
-        <li>Make it searchable</li>
-        <li>compare it to the national NDC</li>
-        </ul> 
     </div>
     <br>
     """

appStore/keyword_search.py

@@ -8,6 +8,7 @@ import logging
 from utils.lexical_search import runLexicalPreprocessingPipeline, lexical_search
 from utils.semantic_search import runSemanticPreprocessingPipeline, semantic_keywordsearch
 from utils.checkconfig import getconfig
+from utils.streamlitcheck import checkbox_without_preselect
 
 # Declare all the necessary variables
 config = getconfig('paramconfig.cfg')
@@ -44,7 +45,7 @@ def app():
 
         st.write(
             """     
-            The *Keyword Search* app is an easy-to-use interface \ 
+            The *Keyword Search* app is an easy-to-use interface \
             built in Streamlit for doing keyword search in \
             policy document - developed by GIZ Data and the \
             Sustainable Development Solution Network.
@@ -60,8 +61,8 @@ def app():
             allows for a personalized experience in using the application. Both \
             methods employ a probabilistic retrieval framework in its identification\
             of relevant paragraphs. By defualt the search is performed using \
-            'Semantic Search' to find 'Exact/Lexical Matches' please tick the \
-            checkbox provided, which will by pass semantic search.. Furthermore,\
+            'Semantic Search', and to find 'Exact/Lexical Matches' please tick the \
+            checkbox provided, which will by-pass semantic search. Furthermore,\
             the application allows the user to search for pre-defined keywords \
             from different thematic buckets present in sidebar.""")
 
@@ -70,7 +71,8 @@ def app():
         with open('docStore/sample/keywordexample.json','r') as json_file:
             keywordexample = json.load(json_file)
         
-        genre = st.radio("Select Keyword Category", list(keywordexample.keys()))
+        # genre = st.radio("Select Keyword Category", list(keywordexample.keys()))
+        genre = checkbox_without_preselect(list(keywordexample.keys()))
         if genre:
             keywordList = keywordexample[genre]
         else:
@@ -87,8 +89,8 @@ def app():
                                     will look for an answer in the document\
                                     OR enter the keyword you are looking \
                                     for and we will we will look for similar\
-                                    context in the document. You can select the \
-                                    presets of keywords from sidebar.",
+                                    context in the document. If dont have anything\
+                                    try the presets of keywords from sidebar. ",
                                     value = "{}".format(keywordList))
         searchtype = st.checkbox("Show only Exact Matches")
         if st.button("Find them"):

appStore/sdg_analysis.py

@@ -75,9 +75,9 @@ def app():
             paragraphs with a calculated relevancy score above 85%.  \n""")
 
         st.write("""**Keyphrase Extraction:** The application extracts 15 \
-            keyphrases from the document, calculates a respective relevancy \
-            score, and displays the results in a summary table. The keyphrases \
-            are extracted using using [Textrank](https://github.com/summanlp/textrank)\
+            keyphrases from the document, for each SDG label and displays the \
+            results in a summary table. The keyphrases are extracted using \
+            using [Textrank](https://github.com/summanlp/textrank)\
             which is an easy-to-use computational less expensive \
             model leveraging combination of TFIDF and Graph networks.
             """)

utils/streamlitcheck.py

@@ -1,3 +1,10 @@
+import logging
+try:
+    import streamlit as st
+except ImportError:
+    logging.info("Streamlit not installed")
+
+
 def check_streamlit():
     """
     Function to check whether python code is run within streamlit
@@ -17,3 +24,19 @@ def check_streamlit():
         use_streamlit = False
     return use_streamlit
 
+def disable_other_checkboxes(*other_checkboxes_keys):
+    for checkbox_key in other_checkboxes_keys:
+        st.session_state[checkbox_key] = False
+
+def checkbox_without_preselect(keylist):
+    dict_ = {}
+    for i,key_val in enumerate(keylist):
+        dict_[i] = st.checkbox(key_val,key = key_val,
+        on_change = disable_other_checkboxes,
+        args=tuple(list(filter(lambda x: x!= key_val, keylist))),)
+    
+    for key,val in dict_:
+        if val == True:
+            return keylist[int(key)]
+    
+    return None