renamed samples to examples

src/examples/foundational/04-utterance-and-speech.py

@@ -0,0 +1,64 @@
+import asyncio
+import os
+
+import aiohttp
+
+from dailyai.services.daily_transport_service import DailyTransportService
+from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
+from dailyai.queue_frame import EndStreamQueueFrame, LLMMessagesQueueFrame
+from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
+
+from examples.foundational.support.runner import configure
+
+async def main(room_url: str):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransportService(
+            room_url,
+            None,
+            "Static And Dynamic Speech",
+            duration_minutes=1,
+            mic_enabled=True,
+            mic_sample_rate=16000,
+            camera_enabled=False
+        )
+
+        llm = AzureLLMService(api_key=os.getenv("AZURE_CHATGPT_API_KEY"), endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"), model=os.getenv("AZURE_CHATGPT_MODEL"))
+        azure_tts = AzureTTSService(api_key=os.getenv("AZURE_SPEECH_API_KEY"), region=os.getenv("AZURE_SPEECH_REGION"))
+        elevenlabs_tts = ElevenLabsTTSService(aiohttp_session=session, api_key=os.getenv("ELEVENLABS_API_KEY"), voice_id=os.getenv("ELEVENLABS_VOICE_ID"))
+
+        messages = [{"role": "system", "content": "tell the user a joke about llamas"}]
+
+        # Start a task to run the LLM to create a joke, and convert the LLM output to audio frames. This task
+        # will run in parallel with generating and speaking the audio for static text, so there's no delay to
+        # speak the LLM response.
+        buffer_queue = asyncio.Queue()
+        llm_response_task = asyncio.create_task(
+            elevenlabs_tts.run_to_queue(
+                buffer_queue,
+                llm.run([LLMMessagesQueueFrame(messages)]),
+                True,
+            )
+        )
+
+        @transport.event_handler("on_first_other_participant_joined")
+        async def on_first_other_participant_joined(transport):
+            await azure_tts.say("My friend the LLM is now going to tell a joke about llamas.", transport.send_queue)
+
+            async def buffer_to_send_queue():
+                while True:
+                    frame = await buffer_queue.get()
+                    await transport.send_queue.put(frame)
+                    buffer_queue.task_done()
+                    if isinstance(frame, EndStreamQueueFrame):
+                        break
+
+            await asyncio.gather(llm_response_task, buffer_to_send_queue())
+
+            await transport.stop_when_done()
+
+        await transport.run()
+
+
+if __name__ == "__main__":
+    (url, token) = configure()
+    asyncio.run(main(url))