Using Language Specific SDKs

# app.py
from flask import Flask, request, render_template, jsonify
import os

from azure.ai.openai import OpenAIClient
from azure.core.credentials import AzureKeyCredential

app = Flask(__name__)

# Read credentials from environment variables for safety
AZURE_OPENAI_KEY = os.environ.get("AZURE_OPENAI_KEY")
AZURE_OPENAI_ENDPOINT = os.environ.get("AZURE_OPENAI_ENDPOINT")
DEPLOYMENT_NAME = os.environ.get("AZURE_OPENAI_DEPLOYMENT", "gpt-4o")

if not (AZURE_OPENAI_KEY and AZURE_OPENAI_ENDPOINT):
    raise ValueError("Set AZURE_OPENAI_KEY and AZURE_OPENAI_ENDPOINT environment variables.")

# Initialize the Azure OpenAI client
credential = AzureKeyCredential(AZURE_OPENAI_KEY)
client = OpenAIClient(endpoint=AZURE_OPENAI_ENDPOINT, credential=credential)

@app.route('/')
def index():
    # Serve a simple UI (index.html) that posts JSON to /chat
    return render_template('index.html')

@app.route('/chat', methods=['POST'])
def chat():
    user_input = request.json.get("message", "").strip()
    if not user_input:
        return jsonify({"reply": "Please send a non-empty message."}), 400

    # Prepare messages and parameters for the chat completion
    messages = [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": user_input}
    ]

    # Call the Azure OpenAI chat completions API (synchronous)
    response = client.get_chat_completions(
        deployment_id=DEPLOYMENT_NAME,
        messages=messages,
        temperature=0.7,
        max_tokens=150
    )

    # Extract the assistant reply
    reply = response.choices[0].message.content.strip()
    return jsonify({"reply": reply})

if __name__ == '__main__':
    # For local development only. In production use a WSGI server like Gunicorn or uWSGI.
    app.run(host='0.0.0.0', port=5000, debug=True)

{
  "reply": "Hello! I'm a virtual assistant ready to help. What would you like to do today?"
}