Cleanup: no more sentence aggregator, let the TTS service deal with that; also removed the queue typing stuff from ai_services

src/samples/theoretical-to-real/02-llm-say-one-thing.py

@@ -4,7 +4,6 @@ from typing import AsyncGenerator
 
 from dailyai.queue_frame import QueueFrame, FrameType
 from dailyai.services.daily_transport_service import DailyTransportService
-from dailyai.services.ai_services import SentenceAggregator
 from dailyai.services.azure_ai_services import AzureLLMService
 from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
 
@@ -28,9 +27,7 @@ async def main(room_url):
     tts_task = asyncio.create_task(
         tts.run_to_queue(
             transport.send_queue,
-            SentenceAggregator().run(
-                llm.run([QueueFrame(FrameType.LLM_MESSAGE, messages)])
-            )
+            llm.run([QueueFrame(FrameType.LLM_MESSAGE, messages)])
         )
     )
 

src/samples/theoretical-to-real/03-still-frame.py

@@ -23,7 +23,7 @@ async def main(room_url):
 
     imagegen = OpenAIImageGenService(image_size="1024x1024")
     image_task = asyncio.create_task(
-        imagegen.run_to_queue(transport.send_queue, [QueueFrame(FrameType.IMAGE_DESCRIPTION, "a cat in the style of picasso")])
+        imagegen.run_to_queue(transport.send_queue, [QueueFrame(FrameType.TEXT, "a cat in the style of picasso")])
     )
 
     @transport.event_handler("on_participant_joined")

src/samples/theoretical-to-real/04-utterance-and-speech.py

@@ -2,7 +2,6 @@ import argparse
 import asyncio
 import re
 
-from dailyai.services.ai_services import SentenceAggregator
 from dailyai.services.daily_transport_service import DailyTransportService
 from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
 from dailyai.queue_frame import QueueFrame, FrameType
@@ -36,9 +35,7 @@ async def main(room_url:str):
     llm_response_task = asyncio.create_task(
         elevenlabs_tts.run_to_queue(
             buffer_queue,
-            SentenceAggregator().run(
-                llm.run([QueueFrame(FrameType.LLM_MESSAGE, messages)])
-            ),
+            llm.run([QueueFrame(FrameType.LLM_MESSAGE, messages)]),
             True,
         )
     )
@@ -48,10 +45,7 @@ async def main(room_url:str):
         if participant["id"] == transport.my_participant_id:
             return
 
-        await azure_tts.run_to_queue(
-            transport.send_queue,
-            [QueueFrame(FrameType.SENTENCE, "My friend the LLM is now going to tell a joke about llamas.")]
-        )
+        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:

src/samples/theoretical-to-real/05-sync-speech-and-text.py

@@ -5,7 +5,6 @@ from asyncio.queues import Queue
 import re
 
 from dailyai.queue_frame import QueueFrame, FrameType
-from dailyai.services.ai_services import SentenceAggregator
 from dailyai.services.azure_ai_services import AzureLLMService
 from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
 from dailyai.services.open_ai_services import OpenAIImageGenService

src/samples/theoretical-to-real/06-listen-and-respond.py

@@ -33,7 +33,7 @@ async def main(room_url:str, token):
 
         sentence = ""
         async for frame in transport.get_receive_frames():
-            if frame.frame_type != FrameType.TRANSCRIPTION:
+            if frame.frame_type != FrameType.TEXT:
                 continue
 
             message = frame.frame_data