Add actions file and Readme

.github/workflows/deploy.yml

@@ -0,0 +1,41 @@
+name: Python application deploy to Azure Functions
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build-and-deploy:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: 'Checkout GitHub Action'
+      uses: actions/checkout@v2
+
+    - name: 'Set up Python 3.11'
+      uses: actions/setup-python@v3
+      with:
+        python-version: 3.11
+
+    - name: 'Install dependencies'
+      run: |
+        python3 -m pip install --upgrade pip
+        pip install -r requirements.txt
+
+    - name: 'Login via Azure CLI'
+      uses: azure/login@v1
+      with:
+        creds: ${{ secrets.AZURE_CREDENTIALS }}
+
+    - name: 'Run Azure Functions Action'
+      uses: Azure/functions-action@v1
+      id: fa
+      with:
+        app-name: <Your-Function-App-Name>
+        package: .
+        publish-profile: ${{ secrets.AZURE_PUBLISH_PROFILE }}
+
+    - name: 'Logout of Azure CLI'
+      run: |
+        az logout

.gitignore

@@ -1,2 +1,3 @@
 .DS_Store
-US_Accidents_March23.csv
+US_Accidents_March23.csv
+/.venv/

Readme.md

@@ -3,31 +3,4 @@ This demo is based on Kagglle data set of [US Accidents](https://www.kaggle.com/
 
 ### RAG
 
-![alt text](image.png)
-
-#### Multiple data source
-
-```
-from langchain.prompts import ChatPromptTemplate
-
-system_message = """Use the information from the below two sources to answer any questions.
-
-Source 1: a SQL database about employee data
-<source1>
-{source1}
-</source1>
-
-Source 2: a text database of random information
-<source2>
-{source2}
-</source2>
-"""
-
-prompt = ChatPromptTemplate.from_messages([("system", system_message), ("human", "{question}")])
-
-full_chain = {
-    "source1": {"question": lambda x: x["question"]} | db_chain.run,
-    "source2": (lambda x: x['question']) | retriever,
-    "question": lambda x: x['question'],
-} | prompt | OpenAI()
-```
+![alt text](image.png)