use inference text in demo, clean up image generation

src/samples/05-sync-speech-and-text.py

@@ -0,0 +1,60 @@
+import asyncio
+
+from dailyai.output_queue import OutputQueueFrame, FrameType
+from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService, AzureImageGenServiceREST
+from dailyai.services.daily_transport_service import DailyTransportService
+
+async def main(room_url, token):
+    class Sample05Transport(DailyTransportService):
+        def on_participant_joined(self, participant):
+            super().on_participant_joined(participant)
+
+    meeting_duration_minutes = 4
+    transport = Sample05Transport(
+        room_url,
+        token,
+        "Simple Bot",
+        meeting_duration_minutes,
+    )
+    transport.mic_enabled = True
+    transport.camera_enabled = True
+    transport.mic_sample_rate = 16000
+    transport.camera_width = 1024
+    transport.camera_height = 1024
+
+    llm = AzureLLMService()
+    tts = AzureTTSService()
+    dalle = AzureImageGenServiceREST()
+
+    inference_text_process = llm.run_llm(
+        [
+            {
+                "role": "system",
+                "content": f"Describe a nature photograph suitable for use in a calendar, for the month of January. Include only the image description with no preamble."
+            }
+        ]
+    )
+
+    try:
+        transport.run()
+
+        inference_text = await inference_text_process
+
+        tts_iterator = tts.run_tts(inference_text)
+        (image, audio) = await asyncio.gather(
+            *[dalle.run_image_gen(inference_text, "1024x1024"), anext(tts_iterator)]
+        )
+        transport.output_queue.put(OutputQueueFrame(FrameType.IMAGE_FRAME, image[1]))
+        transport.output_queue.put(OutputQueueFrame(FrameType.AUDIO_FRAME, audio))
+        async for audio in tts_iterator:
+            transport.output_queue.put(
+                OutputQueueFrame(FrameType.AUDIO_FRAME, audio)
+            )
+
+        await asyncio.sleep(meeting_duration_minutes * 60)
+    finally:
+        transport.stop()
+    print("Done")
+
+if __name__=="__main__":
+    asyncio.run(main("https://moishe.daily.co/Lettvins", None))