enable upload and model selection in dropdown

Dockerfile

@@ -15,8 +15,7 @@ COPY --chown=user ./requirements.txt requirements.txt
 RUN pip3 install --no-cache-dir -r requirements.txt
 
 # Copy the current directory contents into the container at /app setting the owner to the user
-#COPY --chown=user . /app
-
+# also set the user as owner for root directory to enable update permissions
 COPY --link --chown=1000 ./ /app
 
 # app will need to expose the port for taking browser inputs

app.py

@@ -1,5 +1,8 @@
 import streamlit as st
-import os
+from utils.uploadAndExample import add_upload
+from utils.config import model_dict
+from utils.vulnerability_classifier import label_dict
+
 with st.sidebar:
     # upload and example doc
     choice = st.sidebar.radio(label = 'Select the Document',
@@ -7,16 +10,16 @@ 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','Zephyr 7B β','Mistral-7B','Mixtral-8x7B']
 
     # Dropdown selectbox: model
     model_sel = st.selectbox('Select a model:', model_options)
-    #model_sel_name = model_dict[model_sel]
+    model_sel_name = model_dict[model_sel]
 
-    #st.session_state['model_sel_name'] = model_sel_name
+    st.session_state['model_sel_name'] = model_sel_name
 
 with st.container():
     st.markdown("<h2 style='text-align: center;'> Vulnerability Analysis 3.1 </h2>", unsafe_allow_html=True)

utils/config.py

@@ -0,0 +1,41 @@
+import configparser
+import logging
+
+def getconfig(configfile_path:str):
+    """
+    configfile_path: file path of .cfg file
+    """
+
+    config = configparser.ConfigParser()
+
+    try:
+        config.read_file(open(configfile_path))
+        return config
+    except:
+        logging.warning("config file not found")
+
+
+# Declare all the necessary variables
+def get_classifier_params(model_name):
+    config = getconfig('paramconfig.cfg')
+    params = {}
+    params['model_name'] = config.get(model_name,'MODEL')
+    params['split_by'] = config.get(model_name,'SPLIT_BY')
+    params['split_length'] = int(config.get(model_name,'SPLIT_LENGTH'))
+    params['split_overlap'] = int(config.get(model_name,'SPLIT_OVERLAP'))
+    params['remove_punc'] = bool(int(config.get(model_name,'REMOVE_PUNC')))
+    params['split_respect_sentence_boundary'] = bool(int(config.get(model_name,'RESPECT_SENTENCE_BOUNDARY')))
+    params['threshold'] = float(config.get(model_name,'THRESHOLD'))
+    params['top_n'] = int(config.get(model_name,'TOP_KEY'))
+
+    return params
+
+# Model select
+model_dict = {
+'Llama3.1-8B': 'meta-llama/Meta-Llama-3.1-8B-Instruct',
+'Llama3.1-70B': 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+'Llama3.1-405B': 'meta-llama/Meta-Llama-3.1-405B-Instruct',
+'Zephyr 7B β': 'HuggingFaceH4/zephyr-7b-beta',
+'Mistral-7B': 'mistralai/Mistral-7B-Instruct-v0.2',
+'Mixtral-8x7B': 'mistralai/Mixtral-8x7B-Instruct-v0.1',
+}

utils/uploadAndExample.py

@@ -0,0 +1,39 @@
+import streamlit as st
+import tempfile
+import json
+
+def add_upload(choice):
+    """
+    Provdies the user with choice to either 'Upload Document' or 'Try Example'.
+    Based on user choice runs streamlit processes and save the path and name of
+    the 'file' to streamlit session_state which then can be fetched later.
+
+    """
+    
+    if choice == 'Upload Document':
+        
+       # if 'filename' in st.session_state:
+          # Delete all the items in Session state
+        #    for key in st.session_state.keys():
+         #       del st.session_state[key]
+
+        uploaded_file = st.sidebar.file_uploader('Upload the File',
+                            type=['pdf', 'docx', 'txt'])
+        if uploaded_file is not None:
+            with tempfile.NamedTemporaryFile(mode="wb", delete = False) as temp:
+                bytes_data = uploaded_file.getvalue()
+                temp.write(bytes_data)
+                st.session_state['filename'] = uploaded_file.name
+                st.session_state['filepath'] = temp.name
+
+                
+    else:
+        # listing the options
+        with open('docStore/sample/files.json','r') as json_file:
+            files = json.load(json_file)
+
+        option = st.sidebar.selectbox('Select the example document',
+                              list(files.keys()))
+        file_name = file_path  = files[option]
+        st.session_state['filename'] = file_name
+        st.session_state['filepath'] = file_path

utils/vulnerability_classifier.py

@@ -0,0 +1,19 @@
+# labels dictionary
+label_dict= {0: 'Agricultural communities',
+ 1: 'Children',
+ 2: 'Coastal communities',
+ 3: 'Ethnic, racial or other minorities',
+ 4: 'Fishery communities',
+ 5: 'Informal sector workers',
+ 6: 'Members of indigenous and local communities',
+ 7: 'Migrants and displaced persons',
+ 8: 'Older persons',
+ 9: 'Other',
+ 10: 'Persons living in poverty',
+ 11: 'Persons with disabilities',
+ 12: 'Persons with pre-existing health conditions',
+ 13: 'Residents of drought-prone regions',
+ 14: 'Rural populations',
+ 15: 'Sexual minorities (LGBTQI+)',
+ 16: 'Urban populations',
+ 17: 'Women and other genders'}