Add pro-dev quick start example, switch LLM to azure-ai-inference

Author: Saurabh Badenkal

examples/advanced/datascience_risk_assessment.py

@@ -26,8 +26,8 @@
 
 Additional libraries (optional -- used for visualization and LLM; not part
 of the SDK and must be installed separately):
-    pip install matplotlib    # for charts / visualization
-    pip install openai        # for LLM summarization (Azure OpenAI or OpenAI)
+    pip install matplotlib         # for charts / visualization
+    pip install azure-ai-inference  # for LLM summarization (Azure AI Foundry / Azure OpenAI)
 """
 
 import sys
@@ -50,11 +50,12 @@
     HAS_MATPLOTLIB = False
 
 try:
-    from openai import AzureOpenAI
+    from azure.ai.inference import ChatCompletionsClient
+    from azure.core.credentials import AzureKeyCredential
 
-    HAS_OPENAI = True
+    HAS_AZURE_AI = True
 except ImportError:
-    HAS_OPENAI = False
+    HAS_AZURE_AI = False
 
 
 # ================================================================
@@ -282,7 +283,7 @@ def classify_risk(score):
 # ================================================================
 
 
-def step3_summarize(risk_df, azure_openai_endpoint=None, azure_openai_key=None):
+def step3_summarize(risk_df, azure_ai_endpoint=None, azure_ai_key=None):
     """Generate per-account risk summaries using LLM or template fallback."""
     print("\n" + "=" * 60)
     print("STEP 3: Generate risk summaries")
@@ -292,11 +293,11 @@ def step3_summarize(risk_df, azure_openai_endpoint=None, azure_openai_key=None):
     flagged = risk_df[risk_df["risk_tier"].isin(["High", "Medium"])].copy()
     print(f"[INFO] Generating summaries for {len(flagged)} flagged accounts")
 
-    if HAS_OPENAI and azure_openai_endpoint:
-        print("[INFO] Using Azure OpenAI for LLM summarization")
-        summaries = _summarize_with_llm(flagged, azure_openai_endpoint, azure_openai_key)
+    if HAS_AZURE_AI and azure_ai_endpoint:
+        print("[INFO] Using Azure AI Inference for LLM summarization")
+        summaries = _summarize_with_llm(flagged, azure_ai_endpoint, azure_ai_key)
     else:
-        print("[INFO] Using template-based summarization (install openai for LLM)")
+        print("[INFO] Using template-based summarization (install azure-ai-inference for LLM)")
         summaries = _summarize_with_template(flagged)
 
     flagged["risk_summary"] = summaries
@@ -316,11 +317,10 @@ def step3_summarize(risk_df, azure_openai_endpoint=None, azure_openai_key=None):
 
 
 def _summarize_with_llm(flagged_df, endpoint, api_key):
-    """Use Azure OpenAI to generate risk narratives."""
-    client = AzureOpenAI(
-        azure_endpoint=endpoint,
-        api_key=api_key,
-        api_version="2024-02-01",
+    """Use Azure AI Inference (Azure OpenAI / Azure AI Foundry) for risk narratives."""
+    client = ChatCompletionsClient(
+        endpoint=endpoint,
+        credential=AzureKeyCredential(api_key),
     )
 
     summaries = []
@@ -337,11 +337,12 @@ def _summarize_with_llm(flagged_df, endpoint, api_key):
             Avg Close Probability: {row["avg_close_probability"]:.0f}%
         """)
 
-        response = client.chat.completions.create(
-            model="gpt-4o",
+        from azure.ai.inference.models import SystemMessage, UserMessage
+
+        response = client.complete(
             messages=[
-                {"role": "system", "content": "You are a risk analyst. Be concise and actionable."},
-                {"role": "user", "content": prompt},
+                SystemMessage(content="You are a risk analyst. Be concise and actionable."),
+                UserMessage(content=prompt),
             ],
             max_tokens=150,
             temperature=0.3,
@@ -517,7 +518,7 @@ def run_risk_pipeline(client):
     risk_df = step2_analyze(accounts, cases, opportunities)
 
     # Step 3: LLM-powered risk summarization
-    # To use Azure OpenAI, set these values:
+    # To use Azure AI Inference (Azure OpenAI / AI Foundry), set these values:
     azure_endpoint = None  # e.g. "https://your-resource.openai.azure.com/"
     azure_key = None  # Your API key
     risk_df = step3_summarize(risk_df, azure_endpoint, azure_key)