add OpenAI Agents SDK zero-code example

examples/zero-code-examples/openai-agents/requirements.txt

@@ -0,0 +1,6 @@
+openai-agents>=0.3.3
+opentelemetry-instrumentation-openai-agents-v2>=0.1.0
+
+opentelemetry-sdk>=1.36.0
+opentelemetry-exporter-otlp-proto-http>=1.36.0
+python-dotenv>=1.0.0

examples/zero-code-examples/openai-agents/run.py

@@ -0,0 +1,105 @@
+"""Run a dice-rolling OpenAI Agents SDK agent with OTLP export — no agentevals SDK.
+
+Demonstrates zero-code integration: any OTel-instrumented agent streams
+traces to agentevals by pointing the OTLP exporter at the receiver.
+
+Unlike the LangChain and Strands examples, this one is fully self-contained:
+the agent code lives inline with no cross-folder imports.
+
+Prerequisites:
+    1. pip install -r requirements.txt
+    2. agentevals serve --dev
+    3. export OPENAI_API_KEY="your-key-here"
+
+Usage:
+    python examples/zero-code-examples/openai-agents/run.py
+"""
+
+import os
+import random
+
+from agents import Agent, Runner, function_tool
+from dotenv import load_dotenv
+from opentelemetry import trace
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from opentelemetry.instrumentation.openai_agents import OpenAIAgentsInstrumentor
+from opentelemetry.sdk.resources import Resource
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.sdk.trace.export import BatchSpanProcessor
+
+load_dotenv(override=True)
+
+
+@function_tool
+def roll_die(sides: int) -> int:
+    """Roll a die with the given number of sides and return the result."""
+    return random.randint(1, sides)
+
+
+@function_tool
+def check_prime(number: int) -> bool:
+    """Return True if the number is prime, False otherwise."""
+    if number < 2:
+        return False
+    for i in range(2, int(number**0.5) + 1):
+        if number % i == 0:
+            return False
+    return True
+
+
+def main():
+    if not os.getenv("OPENAI_API_KEY"):
+        print("OPENAI_API_KEY not set.")
+        return
+
+    endpoint = os.environ.get("OTEL_EXPORTER_OTLP_ENDPOINT", "http://localhost:4318")
+    print(f"OTLP endpoint: {endpoint}")
+
+    os.environ.setdefault("OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT", "span_and_event")
+
+    os.environ.setdefault(
+        "OTEL_RESOURCE_ATTRIBUTES",
+        "agentevals.eval_set_id=openai_agents_eval,agentevals.session_name=openai-agents-zero-code",
+    )
+
+    resource = Resource.create()
+
+    tracer_provider = TracerProvider(resource=resource)
+    tracer_provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter(), schedule_delay_millis=1000))
+    trace.set_tracer_provider(tracer_provider)
+
+    OpenAIAgentsInstrumentor().instrument()
+
+    agent = Agent(
+        name="Dice Agent",
+        instructions="You are a helpful assistant. You can roll dice and check if numbers are prime.",
+        tools=[roll_die, check_prime],
+    )
+
+    test_queries = [
+        "Hi! Can you help me?",
+        "Roll a 20-sided die for me",
+        "Is the number you rolled prime?",
+    ]
+
+    conversation_input: list = []
+
+    try:
+        for i, query in enumerate(test_queries, 1):
+            print(f"\n[{i}/{len(test_queries)}] User: {query}")
+
+            conversation_input.append({"role": "user", "content": query})
+            result = Runner.run_sync(agent, conversation_input)
+
+            agent_response = result.final_output or ""
+            print(f"     Agent: {agent_response}")
+
+            conversation_input = result.to_input_list()
+    finally:
+        print()
+        tracer_provider.force_flush()
+        print("All traces flushed to OTLP receiver.")
+
+
+if __name__ == "__main__":
+    main()

tests/integration/test_live_agents.py

@@ -248,6 +248,63 @@ def test_session_visible_via_api(self, live_servers):
         assert session_name in session_ids
 
 
+@_skip_no_openai
+class TestOpenAIAgentsZeroCode:
+    """Run the OpenAI Agents SDK zero-code OTLP example and verify session grouping."""
+
+    def test_session_created_with_spans(self, live_servers):
+        main_port, otlp_port, mgr = live_servers
+        session_name = "e2e-openai-agents"
+
+        result = _run_agent(
+            "examples/zero-code-examples/openai-agents/run.py",
+            otlp_port,
+            session_name,
+        )
+        assert result.returncode == 0, f"Agent failed:\nstdout: {result.stdout}\nstderr: {result.stderr}"
+
+        wait_for_session_complete_sync(mgr, session_name, timeout=30)
+        session = mgr.sessions[session_name]
+
+        assert session.is_complete
+        assert session.source == "otlp"
+        assert len(session.spans) > 0, "Expected spans from LLM calls"
+
+    def test_invocations_extracted(self, live_servers):
+        main_port, otlp_port, mgr = live_servers
+        session_name = "e2e-openai-agents-inv"
+
+        result = _run_agent(
+            "examples/zero-code-examples/openai-agents/run.py",
+            otlp_port,
+            session_name,
+        )
+        assert result.returncode == 0, f"Agent failed:\nstdout: {result.stdout}\nstderr: {result.stderr}"
+
+        wait_for_session_complete_sync(mgr, session_name, timeout=30)
+        session = mgr.sessions[session_name]
+
+        assert len(session.invocations) > 0, "Expected extracted invocations"
+
+    def test_session_visible_via_api(self, live_servers):
+        main_port, otlp_port, mgr = live_servers
+        session_name = "e2e-openai-agents-api"
+
+        result = _run_agent(
+            "examples/zero-code-examples/openai-agents/run.py",
+            otlp_port,
+            session_name,
+        )
+        assert result.returncode == 0
+
+        wait_for_session_complete_sync(mgr, session_name, timeout=30)
+
+        resp = httpx.get(f"http://127.0.0.1:{main_port}/api/streaming/sessions")
+        assert resp.status_code == 200
+        session_ids = [s["sessionId"] for s in resp.json()["data"]]
+        assert session_name in session_ids
+
+
 @_skip_no_openai
 class TestAgentRerun:
     """Verify that re-running an agent with the same session_name creates