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appStore/info.py

@@ -29,6 +29,21 @@ def app():
        """
     st.markdown(footer, unsafe_allow_html=True)
     # <div class="text">
+    c1, c2, c3 =  st.columns([6,1,10])
+    with c1:
+        st.image("docStore/img/ndc.png")
+    with c3:
+        st.markdown('<div style="text-align: justify;">The manual extraction \
+        of relevant information from text documents is a \
+    time-consuming task for any policy analysts. As the amount and length of \
+    public policy documents in relation to sustainable development (such as \
+    National Development Plans and Nationally Determined Contributions) \
+    continuously increases, a major challenge for policy action tracking – the \
+    evaluation of stated goals and targets and their actual implementation on \
+    the ground – arises. Luckily, Artificial Intelligence (AI) and Natural \
+    Language Processing (NLP) methods can help in shortening and easing this \
+    task for policy analysts.</div>')
+
     intro = """
     <div style="text-align: justify;">
     The manual extraction of relevant information from text documents is a \