examples: updated to_be_updated examples

examples/foundational/06a-image-sync.py

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+import asyncio
+import os
+import logging
+from typing import AsyncGenerator
+import aiohttp
+from PIL import Image
+
+from dailyai.pipeline.frames import ImageFrame, Frame, TextFrame
+from dailyai.pipeline.pipeline import Pipeline
+from dailyai.transports.daily_transport import DailyTransport
+from dailyai.services.ai_services import AIService
+from dailyai.pipeline.aggregators import (
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+)
+from dailyai.services.open_ai_services import OpenAILLMService
+from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
+
+from runner import configure
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
+logger = logging.getLogger("dailyai")
+logger.setLevel(logging.DEBUG)
+
+
+class ImageSyncAggregator(AIService):
+    def __init__(self, speaking_path: str, waiting_path: str):
+        self._speaking_image = Image.open(speaking_path)
+        self._speaking_image_bytes = self._speaking_image.tobytes()
+
+        self._waiting_image = Image.open(waiting_path)
+        self._waiting_image_bytes = self._waiting_image.tobytes()
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        yield ImageFrame(None, self._speaking_image_bytes)
+        yield frame
+        yield ImageFrame(None, self._waiting_image_bytes)
+
+
+async def main(room_url: str, token):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            5,
+        )
+        transport._camera_enabled = True
+        transport._camera_width = 1024
+        transport._camera_height = 1024
+        transport._mic_enabled = True
+        transport._mic_sample_rate = 16000
+        transport.transcription_settings["extra"]["punctuate"] = True
+
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
+        )
+
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_API_KEY"),
+            model="gpt-4-turbo-preview")
+
+        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 so it should not include any special characters. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        tma_in = LLMUserContextAggregator(
+            messages, transport._my_participant_id)
+        tma_out = LLMAssistantContextAggregator(
+            messages, transport._my_participant_id
+        )
+        image_sync_aggregator = ImageSyncAggregator(
+            os.path.join(os.path.dirname(__file__), "assets", "speaking.png"),
+            os.path.join(os.path.dirname(__file__), "assets", "waiting.png"),
+        )
+
+        pipeline = Pipeline([image_sync_aggregator, tma_in, llm, tma_out, tts])
+
+        @transport.event_handler("on_first_other_participant_joined")
+        async def on_first_other_participant_joined(transport):
+            await pipeline.queue_frames([TextFrame("Hi, I'm listening!")])
+
+        await transport.run(pipeline)
+
+
+if __name__ == "__main__":
+    (url, token) = configure()
+    asyncio.run(main(url, token))