Update app.py

app.py

@@ -4,8 +4,10 @@ import json
 import uuid
 from pathlib import Path
 
-# Azure AI Agents SDK (API key auth)
-from azure.core.credentials import AzureKeyCredential
+# Azure SDK auth (Entra ID)
+from azure.identity import DefaultAzureCredential
+
+# Azure AI Agents SDK
 from azure.ai.agents import AgentsClient
 from azure.ai.agents.models import (
     FunctionTool,
@@ -14,7 +16,7 @@ from azure.ai.agents.models import (
     MessageRole,
 )
 
-# ---------- Inline custom function(s) so no separate user_functions.py is needed ----------
+# ---------- Inline custom function(s) ----------
 
 def submit_support_ticket(email_address: str, description: str) -> str:
     """
@@ -33,30 +35,40 @@ def submit_support_ticket(email_address: str, description: str) -> str:
     )
     file_path.write_text(text, encoding="utf-8")
 
-    message_json = json.dumps({
+    return json.dumps({
         "message": f"Support ticket {ticket_number} submitted. The ticket file is saved as {file_name}"
     })
-    return message_json
 
-# Define the callable tool set
+# Register callable tools
 user_functions: Set[Callable[..., Any]] = { submit_support_ticket }
 
 # ---------- Core Agent Helpers ----------
 
-def init_agent(endpoint: str, api_key: str, model_deployment: str) -> dict:
+def init_agent(project_endpoint: str, model_deployment: str) -> dict:
     """
-    Initialize an Azure AI Agent with a custom FunctionTool.
+    Initialize an Azure AI Agent (Entra ID auth via DefaultAzureCredential).
     Returns a session dict containing client, agent_id, thread_id, etc.
     """
-    if not endpoint or not api_key or not model_deployment:
-        raise ValueError("Please provide endpoint, key, and model deployment name.")
+    if not project_endpoint or not model_deployment:
+        raise ValueError("Please provide a Project Endpoint and Model Deployment name (e.g., gpt-4o).")
+
+    # Entra ID token credential (requires `az login` or other supported auth in your environment)
+    credential = DefaultAzureCredential(
+        exclude_environment_credential=False,
+        exclude_managed_identity_credential=False,
+        exclude_shared_token_cache_credential=False,
+        exclude_visual_studio_code_credential=False,
+        exclude_powershell_credential=False,
+        exclude_cli_credential=False,  # allows Azure CLI token if you've run `az login`
+        exclude_interactive_browser_credential=True,  # set True for server environments
+    )
 
     client = AgentsClient(
-        endpoint=endpoint.strip(),
-        credential=AzureKeyCredential(api_key.strip()),
+        endpoint=project_endpoint.strip(),
+        credential=credential,
     )
 
-    # Build toolset with your functions and enable auto function calls
+    # Build toolset and enable auto function calls
     functions_tool = FunctionTool(user_functions)
     toolset = ToolSet()
     toolset.add(functions_tool)
@@ -68,8 +80,8 @@ def init_agent(endpoint: str, api_key: str, model_deployment: str) -> dict:
         name="support-agent",
         instructions=(
             "You are a technical support agent. "
-            "When a user has a technical issue, ask for their email address and a description "
-            "of the issue. Then submit a support ticket using the available function. "
+            "Ask for the user's email address and a description of the issue. "
+            "Then submit a support ticket using the provided function. "
             "If a file is saved, tell the user the file name."
         ),
         toolset=toolset,
@@ -80,8 +92,7 @@ def init_agent(endpoint: str, api_key: str, model_deployment: str) -> dict:
 
     # Session we keep in Gradio state
     return {
-        "endpoint": endpoint.strip(),
-        "api_key": api_key.strip(),
+        "endpoint": project_endpoint.strip(),
         "model": model_deployment.strip(),
         "client": client,
         "agent_id": agent.id,
@@ -159,15 +170,13 @@ def teardown(session: dict) -> str:
 with gr.Blocks(title="Azure AI Support Agent (Functions) — Gradio") as demo:
     gr.Markdown(
         "## Azure AI Support Agent (Custom Function Tool)\n"
-        "Enter your **Project Endpoint** and **Key**, set your **Model Deployment** (e.g., `gpt-4o`), then chat.\n"
-        "The agent can call a custom function to **submit a support ticket** and save it as a file."
+        "1) **Run `az login`** in the same environment.  \n"
+        "2) Paste your **Project Endpoint** and **Model Deployment** (e.g., `gpt-4o`).  \n"
+        "Then chat — the agent can auto-call a function to submit a support ticket."
     )
 
     with gr.Row():
         endpoint = gr.Textbox(label="Project Endpoint", placeholder="https://<your-project-endpoint>")
-        api_key = gr.Textbox(label="Project Key", placeholder="paste your key", type="password")
-
-    with gr.Row():
         model = gr.Textbox(label="Model Deployment Name", value="gpt-4o")
 
     session_state = gr.State(value=None)
@@ -191,16 +200,16 @@ with gr.Blocks(title="Azure AI Support Agent (Functions) — Gradio") as demo:
 
     # ----- Callbacks -----
 
-    def on_connect(ep, key, mdl):
+    def on_connect(ep, mdl):
         try:
-            sess = init_agent(ep, key, mdl)
-            return sess, "✅ Connected. Support agent and thread are ready."
+            sess = init_agent(ep, mdl)
+            return sess, "✅ Connected. Support agent and thread are ready. (Auth via DefaultAzureCredential)"
         except Exception as e:
             return None, f"❌ Connection error: {e}"
 
     connect_btn.click(
         fn=on_connect,
-        inputs=[endpoint, api_key, model],
+        inputs=[endpoint, model],
         outputs=[session_state, connect_status],
     )