Update app.py

app.py

@@ -38,6 +38,7 @@ import appStore.target as target_analysis
 import appStore.doc_processing as processing
 from utils.uploadAndExample import add_upload
 from utils.vulnerability_classifier import label_dict
+from utils.config import model_dict
 import pandas as pd
 import plotly.express as px
 
@@ -51,7 +52,16 @@ with st.sidebar:
                             or else you can try a example document', 
                             options = ('Upload Document', 'Try Example'), 
                             horizontal = True)
-    add_upload(choice) 
+    add_upload(choice)
+
+    # Create a list of options for the dropdown
+    model_options = ['Llama3.1-8B','Llama3.1-70B','Llama3.1-405B',]
+
+    # Dropdown selectbox: model
+    model_sel = st.selectbox('Select a model:', model_options)
+    model_sel_name = model_dict[model_sel]
+
+    st.session_state['model_sel_name'] = model_sel_name
 
 with st.container():
     st.markdown("<h2 style='text-align: center;'> Vulnerability Analysis 3.0 </h2>", unsafe_allow_html=True)
@@ -97,85 +107,6 @@ if st.button("Analyze Document"):
 if 'key0' in st.session_state:
 
     vulnerability_analysis.vulnerability_display()
-    target_analysis.target_display()
-
-    # ###################################################################
-       
-    # #with st.sidebar:
-    #  #  topic = st.radio(
-    #   #                 "Which category you want to explore?",
-    #    #                (['Vulnerability', 'Concrete targets/actions/measures']))
-    
-    # #if topic == 'Vulnerability':
+    target_analysis.target_display(model_sel_name=model_sel_name)
 
-    # # Assign dataframe a name
-    # df_vul = st.session_state['key0']
-    # st.write(df_vul)
-    
-    # col1, col2 = st.columns([1,1])
-    
-    # with col1:
-        
-    #     # Header
-    #     st.subheader("Explore references to vulnerable groups:")
-
-    #     # Text 
-    #     num_paragraphs = len(df_vul['Vulnerability Label'])
-    #     num_references = df_vul['Vulnerability Label'].apply(lambda x: 'Other' not in x).sum()
-       
-    #     st.markdown(f"""<div style="text-align: justify;"> The document contains a
-    #             total of <span style="color: red;">{num_paragraphs}</span> paragraphs.
-    #             We identified <span style="color: red;">{num_references}</span>
-    #             references to vulnerable groups.</div>
-    #             <br>
-    #             In the pie chart on the right you can see the distribution of the different 
-    #             groups defined. For a more detailed view in the text, see the paragraphs and 
-    #             their respective labels in the table below.</div>""", unsafe_allow_html=True)
-
-    # with col2:
-        
-    #     ### Bar chart
-                    
-    #     # # Create a df that stores all the labels
-    #     df_labels = pd.DataFrame(list(label_dict.items()), columns=['Label ID', 'Label'])
-
-    #     # Count how often each label appears in the "Vulnerability Labels" column
-    #     group_counts = {}
-
-    #     # Iterate through each sublist
-    #     for index, row in df_vul.iterrows():
-            
-    #         # Iterate through each group in the sublist
-    #         for sublist in row['Vulnerability Label']:
-                
-    #             # Update the count in the dictionary
-    #             group_counts[sublist] = group_counts.get(sublist, 0) + 1
-
-    #     # Create a new dataframe from group_counts
-    #     df_label_count = pd.DataFrame(list(group_counts.items()), columns=['Label', 'Count'])
-
-    #     # Merge the label counts with the df_label DataFrame
-    #     df_label_count = df_labels.merge(df_label_count, on='Label', how='left')
-    #     st.write("df_label_count")
-        
-    # #     # Configure graph
-    # #     fig = px.pie(df_labels,
-    # #             names="Label", 
-    # #             values="Count",
-    # #             title='Label Counts',
-    # #             hover_name="Count",
-    # #             color_discrete_sequence=px.colors.qualitative.Plotly
-    # #     )
-        
-    # #     #Show plot
-    # #     st.plotly_chart(fig, use_container_width=True)
-
-    # # ### Table 
-    # st.table(df_vul[df_vul['Vulnerability Label'] != 'Other'])
-
-   # vulnerability_analysis.vulnerability_display()
-# elif topic == 'Action':
-#     policyaction.action_display()
-# else: 
-#     policyaction.policy_display()
-#st.write(st.session_state.key0)
+