Merge pull request #7 from robertmcleod2/add-auth

Add auth

.env_template

@@ -0,0 +1,2 @@
+OPENAI_API_KEY=<OPENAI_API_KEY>
+STREAMLIT_PASSWORD=1234

.github/workflows/deploy.yml

@@ -30,11 +30,12 @@ jobs:
       # App env variables
       OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
       LANGCHAIN_API_KEY: ${{ secrets.LANGCHAIN_API_KEY }}
+      STREAMLIT_PASSWORD: ${{ secrets.STREAMLIT_PASSWORD }}
 
     steps:
       - name: Checkout
         uses: actions/checkout@v3
-      - name: Login to Azure and run deploy.sh
+      - name: run deploy.sh
         shell: bash
         run: |
           echo "$AZURE_CLIENT_CERT" > ${{ vars.AZURE_CLIENT_CERT_NAME }}

README.md

@@ -1,7 +1,11 @@
 # energy-usage-anomaly-detection-assistant
-The energy usage anomaly detection assistant is an LLM based agentic assistant that uses tools to detect anomalies in smart meter data and provide human readable alerts to the customer.
+The energy usage anomaly detection assistant is an LLM based agentic assistant that uses tools to detect anomalies in smart meter data and provide human readable alerts to the customer. 
 
-## Setup
+The customer interacts with the assistant through a streamlit application. The application is deployed to Azure, and can be accessed [here](https://anomalydetectionprodapp.azurewebsites.net/). Please reach out to Robert Mcleod for the password to access the application.
+
+## Local Setup
+
+To run the application locally, follow the steps below:
 
 1. Clone the repository
 
@@ -23,7 +27,10 @@ conda activate energy-usage-anomaly-detection-assistant
 pip install -r requirements_dev.txt
 ```
 
-4. Run the streamlit application
+4. Set up your local environment variables. Create a `.env` file in the root directory of the project, following the template in the .env_template file. The streamlit password can be set to any value. The `OPENAI_API_KEY` can be obtained from [OpenAI](https://platform.openai.com/api-keys), or reach out to Robert Mcleod for the key.
+
+
+5. Run the streamlit application
 
 ```bash
 streamlit run src/app.py

deployment/deploy.sh

@@ -17,17 +17,18 @@ password=$(az acr credential show -n ${AZURE_RESOURCE_GROUP} --query passwords[0
 
 # build and push docker image
 docker build -t streamlit .
-docker image tag streamlit ${AZURE_RESOURCE_GROUP}.azurecr.io/dashboard
-docker push ${AZURE_RESOURCE_GROUP}.azurecr.io/dashboard
+docker image tag streamlit ${AZURE_RESOURCE_GROUP}.azurecr.io/dashboard:latest
+docker push ${AZURE_RESOURCE_GROUP}.azurecr.io/dashboard:latest
 
 # create web app
 az webapp create --name ${AZURE_RESOURCE_GROUP}app --plan ${AZURE_RESOURCE_GROUP} --resource-group  ${AZURE_RESOURCE_GROUP} \
- --container-image-name ${AZURE_RESOURCE_GROUP}.azurecr.io/dashboard \
+ --container-image-name ${AZURE_RESOURCE_GROUP}.azurecr.io/dashboard:latest \
  --container-registry-user ${username} --container-registry-password ${password} --https-only true
 
 # set env variables
 az webapp config appsettings set --resource-group  ${AZURE_RESOURCE_GROUP} --name ${AZURE_RESOURCE_GROUP}app \
- --settings OPENAI_API_KEY=${OPENAI_API_KEY} LANGCHAIN_TRACING_V2="true" LANGCHAIN_API_KEY=${LANGCHAIN_API_KEY} 
+ --settings OPENAI_API_KEY=${OPENAI_API_KEY} LANGCHAIN_TRACING_V2="true" LANGCHAIN_API_KEY=${LANGCHAIN_API_KEY}  \
+ STREAMLIT_PASSWORD=${STREAMLIT_PASSWORD}
 
 az webapp restart --resource-group  ${AZURE_RESOURCE_GROUP} --name ${AZURE_RESOURCE_GROUP}app
 

src/app.py

@@ -1,9 +1,13 @@
 import streamlit as st
 from basic_chatbot import setup_chain
 from dotenv import load_dotenv
+from utils import check_password
 
 load_dotenv()
 
+if not check_password():
+    st.stop()  # Do not continue if check_password is not True.
+
 st.title("Energy Usage Anomaly Detection Assistant")
 
 if "chain" not in st.session_state:
@@ -16,7 +20,7 @@
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
-if prompt := st.chat_input("What is up?"):
+if prompt := st.chat_input("Please describe your energy usage anomaly."):
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)

src/utils.py

@@ -0,0 +1,38 @@
+import os
+import time
+
+import streamlit as st
+import logging
+
+
+def check_password():
+    """Returns `True` if the user had the correct password."""
+
+    def password_entered():
+        """Checks whether a password entered by the user is correct."""
+        password = os.getenv("STREAMLIT_PASSWORD")
+        if not password:
+            st.error("😕 Password not set")
+            return False
+        if st.session_state["password"] == password:
+            st.session_state["password_correct"] = True
+            st.session_state["show_success"] = True
+            del st.session_state["password"]  # Don't store the password.
+        else:
+            st.session_state["password_correct"] = False
+
+    # Return True if the password is validated.
+    if st.session_state.get("password_correct", False):
+        if st.session_state.get("show_success", False):
+            placeholder = st.empty()
+            placeholder.success("🎉 Password correct")
+            time.sleep(1.5)
+            placeholder.empty()
+            st.session_state["show_success"] = False
+        return True
+
+    # Show input for password.
+    st.text_input("Password", type="password", on_change=password_entered, key="password")
+    if "password_correct" in st.session_state:
+        st.error("😕 Password incorrect")
+    return False