add security promps into Generative AI

app/components/app_terminator.py

@@ -1,5 +1,6 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
 import streamlit as st
+from util.enums import Mode
 from util.session_variables import SessionVariables
 import psutil
 import keyboard
@@ -24,7 +25,7 @@ def click():
         return click
 
     def terminate_app_btn(self):
-        if self.sv.mode.value == 'exe':
+        if self.sv.mode.value == Mode.EXE.value:
             exit_app = st.sidebar.button("🔴 Terminate application", disabled=st.session_state.off_btn_disabled, on_click=self._on_click)
             if exit_app:
                 st.text("Shutting down application...")

app/components/app_user.py

@@ -2,6 +2,7 @@
 import streamlit as st
 from javascript.scripts import get_auth_user
 from util.session_variables import SessionVariables
+from util.enums import Mode
 
 class app_user:
 
@@ -29,7 +30,7 @@ def _view_error_info(self, return_value):
 
     def login(self):
         return
-        if self.sv.mode.value != 'cloud':
+        if self.sv.mode.value != Mode.CLOUD.value:
             return
         return_value = get_auth_user()
         username = None

app/pages/Attribute_Patterns.py

@@ -1,12 +1,22 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+from util.session_variables import SessionVariables
 import workflows.attribute_patterns.workflow
 from components.app_loader import load_multipage_app
 import streamlit as st
+from util.enums import Mode
 
 def main():
     st.set_page_config(layout="wide", initial_sidebar_state="collapsed", page_icon="app/myapp.ico", page_title='Intelligence Toolkit | Attribute Patterns')
     load_multipage_app()
-    workflows.attribute_patterns.workflow.create()
+    sv_home = SessionVariables('home')
+
+    try:
+        workflows.attribute_patterns.workflow.create()
+    except Exception as e:
+        if sv_home.mode.value == Mode.DEV.value:
+            st.exception(e)
+        else:
+            st.error(f"An error occurred: {e}")
 
 if __name__ == '__main__':
     main()

app/pages/Data_Synthesis.py

@@ -1,12 +1,22 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+from util.session_variables import SessionVariables
 import workflows.data_synthesis.workflow
 from components.app_loader import load_multipage_app
 import streamlit as st
+from util.enums import Mode
+
 
 def main():
     st.set_page_config(layout="wide", initial_sidebar_state="collapsed", page_icon="app/myapp.ico", page_title='Intelligence Toolkit | Data Synthesis')
     load_multipage_app()
-    workflows.data_synthesis.workflow.create()
+    sv_home = SessionVariables('home')
+    try:
+        workflows.data_synthesis.workflow.create()
+    except Exception as e:
+        if sv_home.mode.value == Mode.DEV.value:
+            st.exception(e)
+        else:
+            st.error(f"An error occurred: {e}")
 
 if __name__ == '__main__':
     main()

app/pages/Group_Narratives.py

@@ -1,12 +1,21 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+from util.session_variables import SessionVariables
 import workflows.group_narratives.workflow
 import streamlit as st
 from components.app_loader import load_multipage_app
+from util.enums import Mode
 
 def main():
     st.set_page_config(layout="wide", initial_sidebar_state="collapsed", page_icon="app/myapp.ico", page_title='Intelligence Toolkit | Group Narratives')
+    sv_home = SessionVariables('home')
     load_multipage_app()
-    workflows.group_narratives.workflow.create()
+    try:
+        workflows.group_narratives.workflow.create()
+    except Exception as e:
+        if sv_home.mode.value == Mode.DEV.value:
+            st.exception(e)
+        else:
+            st.error(f"An error occurred: {e}")
 
 if __name__ == '__main__':
     main()

app/pages/Question_Answering.py

@@ -1,13 +1,21 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+from util.session_variables import SessionVariables
 import workflows.question_answering.workflow
 from components.app_loader import load_multipage_app
 import streamlit as st
-
+from util.enums import Mode
 
 def main():
     st.set_page_config(layout="wide", initial_sidebar_state="collapsed", page_icon="app/myapp.ico", page_title='Intelligence Toolkit | Question Answering')
     load_multipage_app()
-    workflows.question_answering.workflow.create()
-
+    sv_home = SessionVariables('home')
+    try:
+        workflows.question_answering.workflow.create()
+    except Exception as e:
+        if sv_home.mode.value == Mode.DEV.value:
+            st.exception(e)
+        else:
+            st.error(f"An error occurred: {e}")
+
 if __name__ == '__main__':
     main()

app/pages/Record_Matching.py

@@ -1,12 +1,22 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+from util.session_variables import SessionVariables
 import workflows.record_matching.workflow
 from components.app_loader import load_multipage_app
 import streamlit as st
+from util.enums import Mode
 
 def main():
     st.set_page_config(layout="wide", initial_sidebar_state="collapsed", page_icon="app/myapp.ico", page_title='Intelligence Toolkit | Record Matching')
     load_multipage_app()
-    workflows.record_matching.workflow.create()
+    sv_home = SessionVariables('home')
+
+    try:
+        workflows.record_matching.workflow.create()
+    except Exception as e:
+        if sv_home.mode.value == Mode.DEV.value:
+            st.exception(e)
+        else:
+            st.error(f"An error occurred: {e}")
 
 if __name__ == '__main__':
     main()

app/pages/Risk_Networks.py

@@ -1,12 +1,22 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+from util.session_variables import SessionVariables
 import workflows.risk_networks.workflow
 from components.app_loader import load_multipage_app
 import streamlit as st
+from util.enums import Mode
 
 def main():
     st.set_page_config(layout="wide", initial_sidebar_state="collapsed", page_icon="app/myapp.ico", page_title='Intelligence Toolkit | Risk Networks')
     load_multipage_app()
-    workflows.risk_networks.workflow.create()
+    sv_home = SessionVariables('home')
+
+    try:
+        workflows.risk_networks.workflow.create()
+    except Exception as e:
+        if sv_home.mode.value == Mode.DEV.value:
+            st.exception(e)
+        else:
+            st.error(f"An error occurred: {e}")
 
 if __name__ == '__main__':
     main()

app/pages/Settings.py

@@ -5,6 +5,7 @@
 import streamlit as st
 import time
 from util.session_variables import SessionVariables
+from util.enums import Mode
 
 def on_change(handler, key = None, value = None):
     def change():
@@ -20,7 +21,7 @@ def main():
     secrets_handler = SecretsHandler()
     placeholder = "Enter key here..."
     secret = secrets_handler.get_secret(key)
-    is_mode_cloud = sv.mode.value == 'cloud'
+    is_mode_cloud = sv.mode.value == Mode.CLOUD.value
 
     secret_input = st.text_input('Enter your OpenAI key', type="password", disabled=is_mode_cloud, placeholder=placeholder, value=secret)
 

app/util/AI_API.py

@@ -1,3 +1,4 @@
+# Copyright (c) 2024 Microsoft Corporation. All rights reserved.
 import tiktoken
 import json
 from util.openai_instance import _OpenAI
@@ -64,9 +65,9 @@ def generate_text_from_message_list(messages, placeholder=None, prefix='', model
     except Exception as e:
         print(f'Error generating from message list: {e}')
         if '401' and 'invalid_api_key' in str(e):
-            if placeholder is not None:
-                placeholder.error(f'Error generating OpenAI response. Your key is invalid.')
+            raise Exception('Your OpenAI key is invalid.')
+        elif 'rate_limit_exceeded' in str(e):
+            raise Exception('Rate limit exceeded when generating OpenAI response. Try again in a few seconds.')
         else:
-            if placeholder is not None:
-                placeholder.error(f'Error generating OpenAI response.')
+            raise Exception('Problem in OpenAI response.')
     return response

app/util/Embedder.py

@@ -51,17 +51,19 @@ def encode_all(self, texts):
             list_all_embeddings = []
             try:
                 embeddings = [x.embedding for x in openai.client().embeddings.create(input = batch_texts, model=self.model).data]
-                for j, (ix, text) in enumerate(batch):
-                    hsh = hash(text)
-                    list_all_embeddings.append((hsh, embeddings[j]))
-                    final_embeddings[ix] = np.array(embeddings[j])
-                self.connection.insert_multiple_into_embeddings(list_all_embeddings) 
             except Exception as e:
                 if '401' and 'invalid_api_key' in str(e):
-                    raise Exception('Error generating OpenAI response. Your key is invalid.')
+                    raise Exception('Your OpenAI key is invalid.')
+                elif 'rate_limit_exceeded' in str(e):
+                    raise Exception('Rate limit exceeded when generating OpenAI response. Try again in a few seconds.')
                 else:
-                    raise Exception('Error generating OpenAI response.')
-
+                    raise Exception('Problem in OpenAI response.')
+
+            for j, (ix, text) in enumerate(batch):
+                hsh = hash(text)
+                list_all_embeddings.append((hsh, embeddings[j]))
+                final_embeddings[ix] = np.array(embeddings[j])
+            self.connection.insert_multiple_into_embeddings(list_all_embeddings) 
         pb.empty()
         return np.array(final_embeddings)
 
@@ -79,14 +81,17 @@ def encode(self, text, auto_save = True):
                 print('Truncated text to max tokens')
             try:
                 embedding = openai.client().embeddings.create(input = [text], model=self.model).data[0].embedding
-                if auto_save:
-                    self.connection.insert_into_embeddings(hsh, embedding, self.username)
-                return embedding
             except Exception as e:
                 if '401' and 'invalid_api_key' in str(e):
-                    raise Exception('Error generating OpenAI response. Your key is invalid.')
+                    raise Exception('Your OpenAI key is invalid.')
+                elif 'rate_limit_exceeded' in str(e):
+                    raise Exception('Rate limit exceeded when generating OpenAI response. Try again in a few seconds.')
                 else:
-                    raise Exception('Error generating OpenAI response.')
+                    raise Exception('Problem in OpenAI response.')
+
+            if auto_save:
+                self.connection.insert_into_embeddings(hsh, embedding, self.username)
+            return embedding
 
 def create_embedder(cache, model=embed_model, encoder=text_encoder, max_tokens=max_embed_tokens):
     return Embedder(cache, model, encoder, max_tokens)

app/util/download_pdf.py

@@ -17,9 +17,11 @@ def add_download_pdf(name, text, button_text='Download PDF', is_markdown=True, d
 
     # Generate PDF from HTML string
     config_pdf = config_pdfkit()
-    with tempfile.NamedTemporaryFile(suffix='.pdf', delete=False) as temp_file:
-        pdfkit.from_string(text, temp_file.name, options=pdfkit_options, configuration=config_pdf)
-
-        # Provide download button for the generated PDF
-        with open(temp_file.name, 'rb') as f:
-            st.download_button(button_text, f, file_name=name, mime='application/pdf', disabled=disabled)
+
+    with st.spinner('Preparing PDF download...'):
+        with tempfile.NamedTemporaryFile(suffix='.pdf', delete=False) as temp_file:
+            pdfkit.from_string(text, temp_file.name, options=pdfkit_options, configuration=config_pdf)
+
+            # Provide download button for the generated PDF
+            with open(temp_file.name, 'rb') as f:
+                st.download_button(button_text, f, file_name=name, mime='application/pdf', disabled=disabled)

app/util/enums.py

@@ -0,0 +1,8 @@
+# Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+
+from enum import Enum
+
+class Mode(Enum):
+    DEV = 'dev'
+    CLOUD = 'cloud'
+    EXE = 'exe'

app/util/openai_instance.py

@@ -23,7 +23,8 @@ def client(self):
             try:
                 self._instance = OpenAI(api_key=self._key)
             except Exception as e:
-                print(f'Error creating OpenAI client: {e}')
+                raise Exception(f'OpenAI client not created: {e}')
+
 
         return self._instance
 

app/util/session_variables.py

@@ -1,3 +1,4 @@
+from util.enums import Mode
 from util.session_variable import SessionVariable
 import pandas as pd
 import util.session_variable as sv
@@ -7,9 +8,5 @@ class SessionVariables:
 
     def __init__(self, prefix = ''):
         self.narrative_input_df = SessionVariable(pd.DataFrame(), prefix)
-        self.mode = sv.SessionVariable(os.environ.get("MODE", "dev"))
+        self.mode = sv.SessionVariable(os.environ.get("MODE", Mode.DEV.value))
         self.username = sv.SessionVariable('')
-
-
-
-