renamed utils to modules

modules/filter_modules.py

@@ -0,0 +1,21 @@
+import pandas as pd
+import streamlit as st
+
+def country_option(special_cases, country_names):
+    country_option = st.multiselect(
+                'Country / Countries',
+                special_cases + country_names,
+                placeholder="Select"
+                )
+    
+    return country_option
+
+def orga_option(special_cases, orga_names):
+    orga_list = special_cases + [f"{v[0]} ({k})" for k, v in orga_names.items()]
+    orga_option = st.multiselect(
+                'Development Bank / Organization',
+                orga_list,
+                placeholder="Select"
+                )
+    
+    return orga_option

modules/navbar.py

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+import streamlit as st
+from streamlit_option_menu import option_menu # https://github.com/victoryhb/streamlit-option-menu
+
+# giz-dsc colors
+# orange: #e5b50d
+# green: #48d47b
+# blue: #0da2dc
+# grey: #dadada
+
+# giz colors https://www.giz.de/cdc/en/html/59638.html
+# red: #c80f0f 
+# grey: #6f6f6f
+# light_grey: #b2b2b2
+# light_red: #eba1a3
+
+def show_navbar():
+    st.markdown("<h1 style='color: red;'>THIS APP IS WORK IN PROGRESS ...</h1>", unsafe_allow_html=True)
+
+    st.title("Development Bank Synergy Mapper")

modules/result_table.py

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+import streamlit as st
+
+def show_table(data_df, similarities:list):
+    st.write("------------------")
+    
+    st.dataframe(
+        data_df[["title_main", "orga_abbreviation", "client", "description_main", "country", "sgd_pred_code", "crs_3_code", "crs_5_code", "similarity"]],
+        use_container_width = True,
+        height = 35 + 35 * len(data_df),
+        column_config={
+            "orga_abbreviation": st.column_config.TextColumn(
+                "Organization",
+                help="If description not in English, description in other language provided",
+                disabled=True
+            ),
+            "client": st.column_config.TextColumn(
+                "Client",
+                help="Client organization of customer",
+                disabled=True
+            ),
+            "title_main": st.column_config.TextColumn(
+                "Title",
+                help="If title not in English, title in other language provided",
+                disabled=True
+            ),
+            "description_main": st.column_config.TextColumn(
+                "Description",
+                help="If description not in English, description in other language provided",
+                disabled=True
+            ),
+            "country": st.column_config.TextColumn(
+                "Country",
+                help="Country of project",
+                disabled=True
+            ),
+            "sgd_pred_code": st.column_config.TextColumn(
+                "SDG Prediction",
+                help="Prediction of SDG's",
+                disabled=True
+            ),
+            "crs_3_code": st.column_config.TextColumn(
+                "CRS 3",
+                help="CRS 3 code given by organization",
+                disabled=True
+            ),
+            "crs_5_code": st.column_config.TextColumn(
+                "CRS 5",
+                help="CRS 5 code given by organization",
+                disabled=True
+            ),
+        },
+        hide_index=True,
+    )

modules/semantic_search.py

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+import pickle
+import faiss
+import streamlit as st
+from sentence_transformers import SentenceTransformer
+
+def show_search(model, faiss_index, sentences):
+    query = st.text_input("Enter your search query:")
+
+    if query:
+        # Convert query to embedding
+        query_embedding = model.encode([query])[0].reshape(1, -1)
+        
+        # Perform search
+        D, I = faiss_index.search(query_embedding, k=5)  # Search for top 5 similar items
+        
+        # Extract the sentences corresponding to the top indices
+        top_sentences = [sentences[i] for i in I[0]]
+        
+        # Display results as a selection list
+        selected_sentence = st.selectbox("Top results:", top_sentences)
+        
+        # Optionally, do something with the selected sentence
+        st.write("You selected:", selected_sentence)