feat(agents): add agent naming functionality

Allow users to name an agent and use the name in telemetry instead of
relying on randomly generated agent_ids. This improves the developer
experience by making it easier to find specific agents in telemetry logs.

Closes #1832

tests/integration/telemetry/test_telemetry.py

@@ -41,3 +41,77 @@ def test_agent_query_spans(llama_stack_client, text_model_id):
     assert len(agent_logs) == 1
     assert "Give me a sentence that contains the word: hello" in agent_logs[0]["input"]
     assert "hello" in agent_logs[0]["output"].lower()
+
+
+def test_agent_name_filtering(llama_stack_client, text_model_id):
+    # Create an agent with a specific name
+    agent_name = f"test-agent-{uuid4()}"
+    print(f"Using agent_name: {agent_name}")
+
+    agent = Agent(
+        llama_stack_client,
+        model=text_model_id,
+        instructions="You are a helpful assistant",
+        name=agent_name,
+    )
+    session_id = agent.create_session(f"test-session-{uuid4()}")
+    print(f"Created session_id: {session_id}")
+
+    agent.create_turn(
+        messages=[
+            {
+                "role": "user",
+                "content": "Give me a sentence that contains the word: hello",
+            }
+        ],
+        session_id=session_id,
+        stream=False,
+    )
+
+    # Wait for the span to be logged - increase the time to ensure it's processed
+    time.sleep(5)
+
+    # Query spans filtered by session_id to see what's available
+    all_spans = []
+    for span in llama_stack_client.telemetry.query_spans(
+        attribute_filters=[
+            {"key": "session_id", "op": "eq", "value": session_id},
+        ],
+        attributes_to_return=["input", "output", "agent_name", "agent_id", "session_id"],
+    ):
+        all_spans.append(span.attributes)
+
+    print(f"All spans for session {session_id}:")
+    for span in all_spans:
+        print(f"Span attributes: {span}")
+
+    # Query all spans to see if any have the agent_name attribute
+    agent_name_spans = []
+    for span in llama_stack_client.telemetry.query_spans(
+        attribute_filters=[],
+        attributes_to_return=["agent_name"],
+    ):
+        if "agent_name" in span.attributes:
+            agent_name_spans.append(span.attributes)
+
+    print("All spans with agent_name attribute:")
+    for span in agent_name_spans:
+        print(f"Span with agent_name: {span}")
+
+    # Query spans filtered by agent name
+    agent_logs = []
+    for span in llama_stack_client.telemetry.query_spans(
+        attribute_filters=[
+            {"key": "agent_name", "op": "eq", "value": agent_name},
+        ],
+        attributes_to_return=["input", "output", "agent_name"],
+    ):
+        if "output" in span.attributes and span.attributes["output"] != "no shields":
+            agent_logs.append(span.attributes)
+
+    print(f"Found {len(agent_logs)} spans filtered by agent_name")
+
+    assert len(agent_logs) == 1
+    assert agent_logs[0]["agent_name"] == agent_name
+    assert "Give me a sentence that contains the word: hello" in agent_logs[0]["input"]
+    assert "hello" in agent_logs[0]["output"].lower()