5 AI Projects a Cloud Engineer Can Ship in a Weekend

azd init -t azure-search-openai-demo
azd auth login
azd up

Answer the question based on the context below. Be specific and cite the source file name in brackets for each fact.

az functionapp identity assign -g rg-support-bot -n func-support-bot
az role assignment create \
  --assignee <principalId-from-previous-command> \
  --role "Cognitive Services OpenAI User" \
  --scope <openai-resource-id>

import json, os
import azure.functions as func
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from openai import AzureOpenAI
 
app = func.FunctionApp()
 
client = AzureOpenAI(
    azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
    azure_ad_token_provider=get_bearer_token_provider(
        DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
    ),
    api_version="2024-10-21",
)
 
FAQ = open("faq.md").read()
SYSTEM = (
    "You are a support assistant. Answer only from the FAQ below. "
    'Reply as JSON: {"answer": string, "confident": boolean}. '
    "Set confident to false if the FAQ does not clearly answer the question.\n\n"
    + FAQ
)
 
@app.route(route="ask", methods=["POST"], auth_level=func.AuthLevel.FUNCTION)
@app.queue_output(arg_name="handoff", queue_name="handoff", connection="AzureWebJobsStorage")
def ask(req: func.HttpRequest, handoff: func.Out[str]) -> func.HttpResponse:
    question = req.get_json()["question"]
    r = client.chat.completions.create(
        model=os.environ["CHAT_DEPLOYMENT"],  # the deployment name, not the model name
        messages=[
            {"role": "system", "content": SYSTEM},
            {"role": "user", "content": question},
        ],
        response_format={"type": "json_object"},
        temperature=0,
    )
    out = json.loads(r.choices[0].message.content)
    if not out.get("confident"):
        handoff.set(question)  # a person picks it up from the queue
        return func.HttpResponse(json.dumps({"handoff": True}), mimetype="application/json")
    return func.HttpResponse(
        json.dumps({"handoff": False, "answer": out["answer"]}), mimetype="application/json"
    )

SUB=$(az account show --query id -o tsv)
 
az rest --method post \
  --url "https://management.azure.com/subscriptions/$SUB/providers/Microsoft.CostManagement/query?api-version=2023-11-01" \
  --body '{
    "type": "ActualCost",
    "timeframe": "TheLastMonth",
    "dataset": {
      "granularity": "None",
      "aggregation": { "totalCost": { "name": "Cost", "function": "Sum" } },
      "grouping": [ { "type": "Dimension", "name": "ServiceName" } ]
    }
  }' > last-month.json

import json
 
data = json.load(open("last-month.json"))["properties"]
cols = [c["name"] for c in data["columns"]]
rows = [dict(zip(cols, r)) for r in data["rows"]]
top3 = sorted(rows, key=lambda r: r["Cost"], reverse=True)[:3]
 
prompt = (
    "Explain each of these three Azure charges to a non-technical manager. "
    "For each one say what the service does, why the cost could be this size, "
    "and one thing to check. Do not invent numbers.\n\n" + json.dumps(top3)
)
# send `prompt` with the same client setup as Project 2

azd init --template remote-mcp-functions-python -e mcpserver-python
azd up
azd env get-value AZURE_FUNCTION_NAME

https://<FUNCTION_APP_NAME>.azurewebsites.net/runtime/webhooks/blobs?functionName=Host.Functions.read_invoice&code=<BLOB_EXTENSION_KEY>

import json, os
import azure.functions as func
from azure.identity import DefaultAzureCredential
from azure.ai.documentintelligence import DocumentIntelligenceClient
from azure.ai.documentintelligence.models import AnalyzeDocumentRequest
 
app = func.FunctionApp()
di = DocumentIntelligenceClient(os.environ["DI_ENDPOINT"], DefaultAzureCredential())
 
FIELDS = ("VendorName", "InvoiceId", "InvoiceDate", "InvoiceTotal")
 
@app.blob_trigger(arg_name="blob", path="invoices/{name}",
                  connection="AzureWebJobsStorage", source="EventGrid")
@app.blob_output(arg_name="out", path="results/{name}.json",
                 connection="AzureWebJobsStorage")
def read_invoice(blob: func.InputStream, out: func.Out[str]):
    poller = di.begin_analyze_document(
        "prebuilt-invoice", AnalyzeDocumentRequest(bytes_source=blob.read())
    )
    result = poller.result()
    if not result.documents:
        out.set(json.dumps({"error": "no invoice found"}))
        return
    fields = result.documents[0].fields
    out.set(json.dumps({
        k: {
            "value": fields[k].get("content") if k in fields else None,
            "confidence": fields[k].get("confidence") if k in fields else None,
        }
        for k in FIELDS
    }))

az group delete --name rg-docs-chat --yes --no-wait
az group delete --name rg-support-bot --yes --no-wait
az group delete --name rg-bill-explainer --yes --no-wait
az group delete --name rg-invoice-reader --yes --no-wait
azd down   # in the MCP project folder