diff --git a/examples/foundational/new-test.py b/examples/foundational/new-test.py
new file mode 100644
index 000000000..51d402ba0
--- /dev/null
+++ b/examples/foundational/new-test.py
@@ -0,0 +1,64 @@
+import asyncio
+import sys
+
+from dailyai.pipeline.frames import FrameType
+from dailyai.pipeline.pipeline import Pipeline
+from dailyai.processors.passthrough import Passthrough
+from dailyai.services.live_stream import LiveStream
+from dailyai.transports.daily_transport import DailyTransport
+from dailyai.processors.demuxer import Demuxer
+from dailyai.processors.llm_response_aggregator import LLMUserResponseAggregator
+
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main(room_url, token):
+    transport = DailyTransport(
+        room_url, token,
+        camera_enabled=True,
+        camera_width=1280,
+        camera_height=720,
+        mic_enabled=True,
+        speaker_enabled=True,
+        video_capture_enabled=True,
+        transcription_enabled=True,
+    )
+
+    media_passthrough = Passthrough([FrameType.AUDIO_RAW, FrameType.IMAGE_RAW])
+
+    livestream_source = LiveStream(transport, speaker_enabled=True)
+    livestream_sink = LiveStream(transport, camera_enabled=True, mic_enabled=True)
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    llm_user_response = LLMUserResponseAggregator(messages)
+
+    @livestream_source.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(livestream, participant):
+        livestream_source.capture_participant_transcription(participant["id"])
+        livestream_source.capture_participant_video(participant["id"])
+
+    pipeline = Pipeline([livestream_source,
+                         Demuxer([llm_user_response],
+                                 [media_passthrough]),
+                         livestream_sink])
+
+    await pipeline.run()
+
+
+if __name__ == "__main__":
+    (url, token) = configure()
+    asyncio.run(main(url, token))