Use an app factory pattern to enable app testing

.github/workflows/python-test.yaml

@@ -14,14 +14,23 @@ jobs:
  fail-fast: false
  matrix:
  os: ["ubuntu-20.04"]
- python_version: ["3.8", "3.9", "3.10", "3.11"]
+ python_version: ["3.9", "3.10", "3.11"]
  steps:
  - uses: actions/checkout@v3
  - name: Setup python
  uses: actions/setup-python@v2
  with:
  python-version: ${{ matrix.python_version }}
  architecture: x64
+ - name: Setup node
+ uses: actions/setup-node@v2
+ with:
+ node-version: 18
+ - name: Build frontend
+ run: |
+ cd ./app/frontend
+ npm install
+ npm run build
  - name: Install dependencies
  run: |
  python -m pip install --upgrade pip

README.md

@@ -29,7 +29,7 @@ The repo includes sample data so it's ready to try end to end. In this sample ap
 #### To Run Locally
 
 * [Azure Developer CLI](https://aka.ms/azure-dev/install)
-* [Python 3.8+](https://www.python.org/downloads/)
+* [Python 3.9+](https://www.python.org/downloads/)
  * **Important**: Python and the pip package manager must be in the path in Windows for the setup scripts to work.
  * **Important**: Ensure you can run `python --version` from console. On Ubuntu, you might need to run `sudo apt install python-is-python3` to link `python` to `python3`.
 * [Node.js 14+](https://nodejs.org/en/download/)

app/backend/app.py

@@ -5,85 +5,67 @@
 import time
 
 import openai
+from azure.identity import DefaultAzureCredential
+from azure.search.documents import SearchClient
+from azure.storage.blob import BlobServiceClient
+from flask import (
+ Blueprint,
+ Flask,
+ abort,
+ current_app,
+ jsonify,
+ request,
+ send_file,
+ send_from_directory,
+)
+
 from approaches.chatreadretrieveread import ChatReadRetrieveReadApproach
 from approaches.readdecomposeask import ReadDecomposeAsk
 from approaches.readretrieveread import ReadRetrieveReadApproach
 from approaches.retrievethenread import RetrieveThenReadApproach
-from azure.identity import DefaultAzureCredential
-from azure.search.documents import SearchClient
-from azure.storage.blob import BlobServiceClient
-from flask import Flask, abort, jsonify, request, send_file
 
 # Replace these with your own values, either in environment variables or directly here
-AZURE_STORAGE_ACCOUNT = os.environ.get("AZURE_STORAGE_ACCOUNT") or "mystorageaccount"
-AZURE_STORAGE_CONTAINER = os.environ.get("AZURE_STORAGE_CONTAINER") or "content"
-AZURE_SEARCH_SERVICE = os.environ.get("AZURE_SEARCH_SERVICE") or "gptkb"
-AZURE_SEARCH_INDEX = os.environ.get("AZURE_SEARCH_INDEX") or "gptkbindex"
-AZURE_OPENAI_SERVICE = os.environ.get("AZURE_OPENAI_SERVICE") or "myopenai"
-AZURE_OPENAI_GPT_DEPLOYMENT = os.environ.get("AZURE_OPENAI_GPT_DEPLOYMENT") or "davinci"
-AZURE_OPENAI_CHATGPT_DEPLOYMENT = os.environ.get("AZURE_OPENAI_CHATGPT_DEPLOYMENT") or "chat"
-AZURE_OPENAI_CHATGPT_MODEL = os.environ.get("AZURE_OPENAI_CHATGPT_MODEL") or "gpt-35-turbo"
-AZURE_OPENAI_EMB_DEPLOYMENT = os.environ.get("AZURE_OPENAI_EMB_DEPLOYMENT") or "embedding"
-
-KB_FIELDS_CONTENT = os.environ.get("KB_FIELDS_CONTENT") or "content"
-KB_FIELDS_CATEGORY = os.environ.get("KB_FIELDS_CATEGORY") or "category"
-KB_FIELDS_SOURCEPAGE = os.environ.get("KB_FIELDS_SOURCEPAGE") or "sourcepage"
-
-# Use the current user identity to authenticate with Azure OpenAI, Cognitive Search and Blob Storage (no secrets needed,
-# just use 'az login' locally, and managed identity when deployed on Azure). If you need to use keys, use separate AzureKeyCredential instances with the
-# keys for each service
-# If you encounter a blocking error during a DefaultAzureCredntial resolution, you can exclude the problematic credential by using a parameter (ex. exclude_shared_token_cache_credential=True)
-azure_credential = DefaultAzureCredential(exclude_shared_token_cache_credential = True)
-
-# Used by the OpenAI SDK
-openai.api_type = "azure"
-openai.api_base = f"https://{AZURE_OPENAI_SERVICE}.openai.azure.com"
-openai.api_version = "2023-05-15"
-
-# Comment these two lines out if using keys, set your API key in the OPENAI_API_KEY environment variable instead
-openai.api_type = "azure_ad"
-openai_token = azure_credential.get_token("https://cognitiveservices.azure.com/.default")
-openai.api_key = openai_token.token
-
-# Set up clients for Cognitive Search and Storage
-search_client = SearchClient(
- endpoint=f"https://{AZURE_SEARCH_SERVICE}.search.windows.net",
- index_name=AZURE_SEARCH_INDEX,
- credential=azure_credential)
-blob_client = BlobServiceClient(
- account_url=f"https://{AZURE_STORAGE_ACCOUNT}.blob.core.windows.net",
- credential=azure_credential)
-blob_container = blob_client.get_container_client(AZURE_STORAGE_CONTAINER)
-
-# Various approaches to integrate GPT and external knowledge, most applications will use a single one of these patterns
-# or some derivative, here we include several for exploration purposes
-ask_approaches = {
- "rtr": RetrieveThenReadApproach(search_client, AZURE_OPENAI_CHATGPT_DEPLOYMENT, AZURE_OPENAI_CHATGPT_MODEL, AZURE_OPENAI_EMB_DEPLOYMENT, KB_FIELDS_SOURCEPAGE, KB_FIELDS_CONTENT),
- "rrr": ReadRetrieveReadApproach(search_client, AZURE_OPENAI_GPT_DEPLOYMENT, AZURE_OPENAI_EMB_DEPLOYMENT, KB_FIELDS_SOURCEPAGE, KB_FIELDS_CONTENT),
- "rda": ReadDecomposeAsk(search_client, AZURE_OPENAI_GPT_DEPLOYMENT, AZURE_OPENAI_EMB_DEPLOYMENT, KB_FIELDS_SOURCEPAGE, KB_FIELDS_CONTENT)
-}
-
-chat_approaches = {
- "rrr": ChatReadRetrieveReadApproach(search_client,
- AZURE_OPENAI_CHATGPT_DEPLOYMENT,
- AZURE_OPENAI_CHATGPT_MODEL,
- AZURE_OPENAI_EMB_DEPLOYMENT,
- KB_FIELDS_SOURCEPAGE,
- KB_FIELDS_CONTENT)
-}
-
-app = Flask(__name__)
-
-@app.route("/", defaults={"path": "index.html"})
-@app.route("/<path:path>")
-def static_file(path):
- return app.send_static_file(path)
+AZURE_STORAGE_ACCOUNT = os.getenv("AZURE_STORAGE_ACCOUNT", "mystorageaccount")
+AZURE_STORAGE_CONTAINER = os.getenv("AZURE_STORAGE_CONTAINER", "content")
+AZURE_SEARCH_SERVICE = os.getenv("AZURE_SEARCH_SERVICE", "gptkb")
+AZURE_SEARCH_INDEX = os.getenv("AZURE_SEARCH_INDEX", "gptkbindex")
+AZURE_OPENAI_SERVICE = os.getenv("AZURE_OPENAI_SERVICE", "myopenai")
+AZURE_OPENAI_GPT_DEPLOYMENT = os.getenv("AZURE_OPENAI_GPT_DEPLOYMENT", "davinci")
+AZURE_OPENAI_CHATGPT_DEPLOYMENT = os.getenv("AZURE_OPENAI_CHATGPT_DEPLOYMENT", "chat")
+AZURE_OPENAI_CHATGPT_MODEL = os.getenv("AZURE_OPENAI_CHATGPT_MODEL", "gpt-35-turbo")
+AZURE_OPENAI_EMB_DEPLOYMENT = os.getenv("AZURE_OPENAI_EMB_DEPLOYMENT", "embedding")
+
+KB_FIELDS_CONTENT = os.getenv("KB_FIELDS_CONTENT", "content")
+KB_FIELDS_CATEGORY = os.getenv("KB_FIELDS_CATEGORY", "category")
+KB_FIELDS_SOURCEPAGE = os.getenv("KB_FIELDS_SOURCEPAGE", "sourcepage")
+
+CONFIG_OPENAI_TOKEN = "openai_token"
+CONFIG_CREDENTIAL = "azure_credential"
+CONFIG_ASK_APPROACHES = "ask_approaches"
+CONFIG_CHAT_APPROACHES = "chat_approaches"
+CONFIG_BLOB_CLIENT = "blob_client"
+
+
+bp = Blueprint("routes", __name__, static_folder='static')
+
+@bp.route("/")
+def index():
+ return bp.send_static_file("index.html")
+
+@bp.route("/favicon.ico")
+def favicon():
+ return bp.send_static_file("favicon.ico")
+
+@bp.route("/assets/<path:path>")
+def assets(path):
+ return send_from_directory("static/assets", path)
 
 # Serve content files from blob storage from within the app to keep the example self-contained.
 # *** NOTE *** this assumes that the content files are public, or at least that all users of the app
 # can access all the files. This is also slow and memory hungry.
-@app.route("/content/<path>")
+@bp.route("/content/<path>")
 def content_file(path):
+ blob_container = current_app.config[CONFIG_BLOB_CLIENT].get_container_client(AZURE_STORAGE_CONTAINER)
  blob = blob_container.get_blob_client(path).download_blob()
  if not blob.properties or not blob.properties.has_key("content_settings"):
  abort(404)
@@ -95,13 +77,13 @@ def content_file(path):
  blob_file.seek(0)
  return send_file(blob_file, mimetype=mime_type, as_attachment=False, download_name=path)
 
-@app.route("/ask", methods=["POST"])
+@bp.route("/ask", methods=["POST"])
 def ask():
- if not request.json:
- return jsonify({"error": "request must be json"}), 400
+ if not request.is_json:
+ return jsonify({"error": "request must be json"}), 415
  approach = request.json["approach"]
  try:
- impl = ask_approaches.get(approach)
+ impl = current_app.config[CONFIG_ASK_APPROACHES].get(approach)
  if not impl:
  return jsonify({"error": "unknown approach"}), 400
  r = impl.run(request.json["question"], request.json.get("overrides") or {})
@@ -110,13 +92,13 @@ def ask():
  logging.exception("Exception in /ask")
  return jsonify({"error": str(e)}), 500
 
-@app.route("/chat", methods=["POST"])
+@bp.route("/chat", methods=["POST"])
 def chat():
- if not request.json:
- return jsonify({"error": "request must be json"}), 400
+ if not request.is_json:
+ return jsonify({"error": "request must be json"}), 415
  approach = request.json["approach"]
  try:
- impl = chat_approaches.get(approach)
+ impl = current_app.config[CONFIG_CHAT_APPROACHES].get(approach)
  if not impl:
  return jsonify({"error": "unknown approach"}), 400
  r = impl.run(request.json["history"], request.json.get("overrides") or {})
@@ -125,12 +107,89 @@ def chat():
  logging.exception("Exception in /chat")
  return jsonify({"error": str(e)}), 500
 
-@app.before_request
+@bp.before_request
 def ensure_openai_token():
- global openai_token
+ openai_token = current_app.config[CONFIG_OPENAI_TOKEN]
  if openai_token.expires_on < time.time() + 60:
- openai_token = azure_credential.get_token("https://cognitiveservices.azure.com/.default")
+ openai_token = current_app.config[CONFIG_CREDENTIAL].get_token("https://cognitiveservices.azure.com/.default")
+ current_app.config[CONFIG_OPENAI_TOKEN] = openai_token
  openai.api_key = openai_token.token
 
+
+def create_app():
+ app = Flask(__name__)
+
+ # Use the current user identity to authenticate with Azure OpenAI, Cognitive Search and Blob Storage (no secrets needed,
+ # just use 'az login' locally, and managed identity when deployed on Azure). If you need to use keys, use separate AzureKeyCredential instances with the
+ # keys for each service
+ # If you encounter a blocking error during a DefaultAzureCredntial resolution, you can exclude the problematic credential by using a parameter (ex. exclude_shared_token_cache_credential=True)
+ azure_credential = DefaultAzureCredential(exclude_shared_token_cache_credential = True)
+
+ # Set up clients for Cognitive Search and Storage
+ search_client = SearchClient(
+ endpoint=f"https://{AZURE_SEARCH_SERVICE}.search.windows.net",
+ index_name=AZURE_SEARCH_INDEX,
+ credential=azure_credential)
+ blob_client = BlobServiceClient(
+ account_url=f"https://{AZURE_STORAGE_ACCOUNT}.blob.core.windows.net",
+ credential=azure_credential)
+
+ # Used by the OpenAI SDK
+ openai.api_type = "azure"
+ openai.api_base = f"https://{AZURE_OPENAI_SERVICE}.openai.azure.com"
+ openai.api_version = "2023-05-15"
+
+ # Comment these two lines out if using keys, set your API key in the OPENAI_API_KEY environment variable instead
+ openai.api_type = "azure_ad"
+ openai_token = azure_credential.get_token(
+ "https://cognitiveservices.azure.com/.default"
+ )
+ openai.api_key = openai_token.token
+
+ # Store on app.config for later use inside requests
+ app.config[CONFIG_OPENAI_TOKEN] = openai_token
+ app.config[CONFIG_CREDENTIAL] = azure_credential
+ app.config[CONFIG_BLOB_CLIENT] = blob_client
+ # Various approaches to integrate GPT and external knowledge, most applications will use a single one of these patterns
+ # or some derivative, here we include several for exploration purposes
+ app.config[CONFIG_ASK_APPROACHES] = {
+ "rtr": RetrieveThenReadApproach(
+ search_client,
+ AZURE_OPENAI_CHATGPT_DEPLOYMENT,
+ AZURE_OPENAI_CHATGPT_MODEL,
+ AZURE_OPENAI_EMB_DEPLOYMENT,
+ KB_FIELDS_SOURCEPAGE,
+ KB_FIELDS_CONTENT
+ ),
+ "rrr": ReadRetrieveReadApproach(
+ search_client,
+ AZURE_OPENAI_GPT_DEPLOYMENT,
+ AZURE_OPENAI_EMB_DEPLOYMENT,
+ KB_FIELDS_SOURCEPAGE,
+ KB_FIELDS_CONTENT
+ ),
+ "rda": ReadDecomposeAsk(search_client,
+ AZURE_OPENAI_GPT_DEPLOYMENT,
+ AZURE_OPENAI_EMB_DEPLOYMENT,
+ KB_FIELDS_SOURCEPAGE,
+ KB_FIELDS_CONTENT
+ )
+ }
+ app.config[CONFIG_CHAT_APPROACHES] = {
+ "rrr": ChatReadRetrieveReadApproach(
+ search_client,
+ AZURE_OPENAI_CHATGPT_DEPLOYMENT,
+ AZURE_OPENAI_CHATGPT_MODEL,
+ AZURE_OPENAI_EMB_DEPLOYMENT,
+ KB_FIELDS_SOURCEPAGE,
+ KB_FIELDS_CONTENT,
+ )
+ }
+
+ app.register_blueprint(bp)
+
+ return app
+
 if __name__ == "__main__":
+ app = create_app()
  app.run()

app/backend/approaches/chatreadretrieveread.py

@@ -1,9 +1,10 @@
 from typing import Any, Sequence
 
 import openai
-from approaches.approach import Approach
 from azure.search.documents import SearchClient
 from azure.search.documents.models import QueryType
+
+from approaches.approach import Approach
 from core.messagebuilder import MessageBuilder
 from core.modelhelper import get_token_limit
 from text import nonewlines

app/backend/approaches/readdecomposeask.py

@@ -2,14 +2,15 @@
 from typing import Any, List, Optional
 
 import openai
-from approaches.approach import Approach
 from azure.search.documents import SearchClient
 from azure.search.documents.models import QueryType
 from langchain.agents import AgentExecutor, Tool
 from langchain.agents.react.base import ReActDocstoreAgent
 from langchain.callbacks.manager import CallbackManager
 from langchain.llms.openai import AzureOpenAI
 from langchain.prompts import BasePromptTemplate, PromptTemplate
+
+from approaches.approach import Approach
 from langchainadapters import HtmlCallbackHandler
 from text import nonewlines
 

app/backend/approaches/readretrieveread.py

@@ -1,13 +1,14 @@
 from typing import Any
 
 import openai
-from approaches.approach import Approach
 from azure.search.documents import SearchClient
 from azure.search.documents.models import QueryType
 from langchain.agents import AgentExecutor, Tool, ZeroShotAgent
 from langchain.callbacks.manager import CallbackManager, Callbacks
 from langchain.chains import LLMChain
 from langchain.llms.openai import AzureOpenAI
+
+from approaches.approach import Approach
 from langchainadapters import HtmlCallbackHandler
 from lookuptool import CsvLookupTool
 from text import nonewlines

app/backend/approaches/retrievethenread.py

@@ -1,9 +1,10 @@
 from typing import Any
 
 import openai
-from approaches.approach import Approach
 from azure.search.documents import SearchClient
 from azure.search.documents.models import QueryType
+
+from approaches.approach import Approach
 from core.messagebuilder import MessageBuilder
 from text import nonewlines
 

app/backend/gunicorn.conf.py

@@ -9,3 +9,4 @@
 workers = (num_cpus * 2) + 1
 threads = 1 if num_cpus == 1 else 2
 timeout = 600
+worker_class = "gthread"

infra/main.bicep

@@ -111,7 +111,7 @@ module backend 'core/host/appservice.bicep' = {
  appServicePlanId: appServicePlan.outputs.id
  runtimeName: 'python'
  runtimeVersion: '3.10'
- appCommandLine: 'start_appservice.sh'
+ appCommandLine: 'python3 -m gunicorn "app:create_app()"'
  scmDoBuildDuringDeployment: true
  managedIdentity: true
  appSettings: {

pyproject.toml

@@ -2,12 +2,14 @@
 target-version = "py38"
 select = ["E", "F", "I", "UP"]
 ignore = ["E501", "E701"] # line too long, multiple statements on one line
+src = ["app/backend"]
 
 [tool.black]
 line-length = 300
 
 [tool.pytest.ini_options]
 addopts = "-ra --cov"
+pythonpath = ["app/backend"]
 
 [tool.coverage.paths]
 source = ["scripts", "app"]