cleaned up example logging (#46)

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

@@ -1,23 +1,29 @@
 import argparse
 import asyncio
 import os
+import logging
 from typing import AsyncGenerator
 import aiohttp
 import requests
 import time
 import urllib.parse
-
 from PIL import Image
-from dailyai.pipeline.frames import ImageFrame, Frame
 
+from dailyai.pipeline.frames import ImageFrame, Frame
 from dailyai.services.daily_transport_service import DailyTransportService
 from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
 from dailyai.services.ai_services import AIService
-from dailyai.pipeline.aggregators import LLMAssistantContextAggregator, LLMUserContextAggregator
+from dailyai.pipeline.aggregators import (
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+)
 from dailyai.services.fal_ai_services import FalImageGenService
-
 from examples.support.runner import configure
 
+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):
@@ -50,15 +56,18 @@ async def main(room_url: str, token):
         llm = AzureLLMService(
             api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
             endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"),
-            model=os.getenv("AZURE_CHATGPT_MODEL"))
+            model=os.getenv("AZURE_CHATGPT_MODEL"),
+        )
         tts = AzureTTSService(
             api_key=os.getenv("AZURE_SPEECH_API_KEY"),
-            region=os.getenv("AZURE_SPEECH_REGION"))
+            region=os.getenv("AZURE_SPEECH_REGION"),
+        )
         img = FalImageGenService(
             image_size="1024x1024",
             aiohttp_session=session,
             key_id=os.getenv("FAL_KEY_ID"),
-            key_secret=os.getenv("FAL_KEY_SECRET"))
+            key_secret=os.getenv("FAL_KEY_SECRET"),
+        )
 
         async def get_images():
             get_speaking_task = asyncio.create_task(
@@ -80,12 +89,13 @@ async def main(room_url: str, token):
 
         async def handle_transcriptions():
             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."},
+                {
+                    "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.",
+                },
             ]
 
-            tma_in = LLMUserContextAggregator(
-                messages, transport._my_participant_id
-            )
+            tma_in = LLMUserContextAggregator(messages, transport._my_participant_id)
             tma_out = LLMAssistantContextAggregator(
                 messages, transport._my_participant_id
             )
@@ -96,14 +106,8 @@ async def main(room_url: str, token):
             await tts.run_to_queue(
                 transport.send_queue,
                 image_sync_aggregator.run(
-                    tma_out.run(
-                        llm.run(
-                            tma_in.run(
-                                transport.get_receive_frames()
-                            )
-                        )
-                    )
-                )
+                    tma_out.run(llm.run(tma_in.run(transport.get_receive_frames())))
+                ),
             )
 
         transport.transcription_settings["extra"]["punctuate"] = True