some sample and readme updates
@@ -35,7 +35,7 @@ pip install path_to_this_repo
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Tou can run the simple sample like so:
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```
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python src/samples/simple-sample/simple-sample.py -u your_room_url -k your_daily_api_key
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python src/samples/theoretical-to-real/01-say-one-thing.py -u <url of your Daily meeting> -k <your Daily API Key>
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```
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Note that the sample uses Azure's TTS and LLM services. You'll need to set the following environment variables for the sample to work:
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1
src/samples/deprecated/README.md
Normal file
@@ -0,0 +1 @@
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These samples need to be updated! Don't rely on them.
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Before Width: | Height: | Size: 871 KiB After Width: | Height: | Size: 871 KiB |
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Before Width: | Height: | Size: 870 KiB After Width: | Height: | Size: 870 KiB |
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Before Width: | Height: | Size: 871 KiB After Width: | Height: | Size: 871 KiB |
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Before Width: | Height: | Size: 868 KiB After Width: | Height: | Size: 868 KiB |
@@ -36,6 +36,7 @@ async def main(room_url):
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async def on_participant_joined(transport, participant):
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if participant["info"]["isLocal"]:
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return
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async for audio in audio_generator:
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transport.output_queue.put(QueueFrame(FrameType.AUDIO_FRAME, audio))
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@@ -52,6 +53,6 @@ if __name__ == "__main__":
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"-u", "--url", type=str, required=True, help="URL of the Daily room to join"
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)
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args: argparse.Namespace = parser.parse_args()
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args, unknown = parser.parse_known_args()
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asyncio.run(main(args.url))
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@@ -1,124 +0,0 @@
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import argparse
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import asyncio
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from asyncio.queues import Queue
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import re
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from dailyai.queue_frame import QueueFrame, FrameType
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from dailyai.services.azure_ai_services import AzureLLMService
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from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
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from dailyai.services.open_ai_services import OpenAIImageGenService
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from dailyai.services.daily_transport_service import DailyTransportService
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async def main(room_url):
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meeting_duration_minutes = 5
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transport = DailyTransportService(
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room_url,
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None,
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"Month Narration Bot",
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meeting_duration_minutes,
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)
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transport.mic_enabled = True
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transport.camera_enabled = True
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transport.mic_sample_rate = 16000
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transport.camera_width = 1024
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transport.camera_height = 1024
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llm = AzureLLMService()
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tts = ElevenLabsTTSService(voice_id="ErXwobaYiN019PkySvjV")
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dalle = OpenAIImageGenService()
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# Get a complete audio chunk from the given text. Splitting this into its own
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# coroutine lets us ensure proper ordering of the audio chunks on the output queue.
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async def get_all_audio(text):
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all_audio = bytearray()
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async for audio in tts.run_tts(text):
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all_audio.extend(audio)
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return all_audio
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async def get_month_data(month):
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image_text = ""
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tts_tasks = []
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first_sentence = True
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async for sentence in llm.run_llm_async_sentences(
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[
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{
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"role": "system",
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"content": f"Describe a nature photograph suitable for use in a calendar, for the month of {month}. Include only the image description with no preamble. Limit the description to one sentence, please."
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}
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]
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):
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image_text += sentence
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if first_sentence:
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sentence = f"{month}: {sentence}"
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else:
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first_sentence = False
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tts_tasks.append(get_all_audio(sentence))
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tts_tasks.insert(0, dalle.run_image_gen(image_text, "1024x1024"))
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print(f"waiting for tasks to finish for {month}")
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data = await asyncio.gather(
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*tts_tasks
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)
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print(f"done gathering tts tasks for {month}")
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return {
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"month": month,
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"text": image_text,
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"image": data[0][1],
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"audio": data[1:],
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}
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months: list[str] = [
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"January",
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"February",
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"March",
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"April",
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"May",
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"June",
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"July",
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"August",
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"September",
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"October",
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"November",
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"December",
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]
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@transport.event_handler("on_first_other_participant_joined")
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async def on_first_other_participant_joined(transport):
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# This will play the months in the order they're completed. The benefit
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# is we'll have as little delay as possible before the first month, and
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# likely no delay between months, but the months won't display in order.
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for month_data_task in asyncio.as_completed(month_tasks):
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data = await month_data_task
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transport.output_queue.put(
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[
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QueueFrame(FrameType.IMAGE_FRAME, data["image"]),
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QueueFrame(FrameType.AUDIO_FRAME, data["audio"][0]),
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]
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)
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for audio in data["audio"][1:]:
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transport.output_queue.put(QueueFrame(FrameType.AUDIO_FRAME, audio))
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# wait for the output queue to be empty, then leave the meeting
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transport.output_queue.join()
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transport.stop()
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month_tasks = [asyncio.create_task(get_month_data(month)) for month in months]
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await transport.run()
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if __name__=="__main__":
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parser = argparse.ArgumentParser(description="Simple Daily Bot Sample")
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parser.add_argument(
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"-u", "--url", type=str, required=True, help="URL of the Daily room to join"
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)
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args, unknown = parser.parse_known_args()
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asyncio.run(main(args.url))
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@@ -1,15 +1,13 @@
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import argparse
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import asyncio
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from asyncio.queues import Queue
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import re
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from dailyai.queue_frame import QueueFrame, FrameType
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from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
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from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
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from dailyai.services.open_ai_services import OpenAILLMService, OpenAIImageGenService
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from dailyai.services.azure_ai_services import AzureLLMService
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from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
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from dailyai.services.open_ai_services import OpenAIImageGenService
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from dailyai.services.daily_transport_service import DailyTransportService
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async def main(room_url):
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@@ -27,7 +25,7 @@ async def main(room_url):
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transport.camera_height = 1024
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llm = AzureLLMService()
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tts = ElevenLabsTTSService()
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tts = ElevenLabsTTSService(voice_id="ErXwobaYiN019PkySvjV")
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dalle = OpenAIImageGenService()
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# Get a complete audio chunk from the given text. Splitting this into its own
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@@ -41,9 +39,9 @@ async def main(room_url):
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async def get_month_data(month):
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image_text = ""
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current_clause = ""
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tts_tasks = []
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async for text in llm.run_llm_async(
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first_sentence = True
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async for sentence in llm.run_llm_async_sentences(
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[
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{
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"role": "system",
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@@ -51,18 +49,24 @@ async def main(room_url):
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}
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]
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):
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image_text += text
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current_clause += text
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if re.match(r"^.*[.!?]$", text):
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tts_tasks.append(get_all_audio(current_clause))
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current_clause = ""
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image_text += sentence
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if first_sentence:
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sentence = f"{month}: {sentence}"
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else:
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first_sentence = False
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tts_tasks.append(get_all_audio(sentence))
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tts_tasks.insert(0, dalle.run_image_gen(image_text, "1024x1024"))
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print(f"waiting for tasks to finish for {month}")
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data = await asyncio.gather(
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*tts_tasks
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)
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print(f"done gathering tts tasks for {month}")
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return {
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"month": month,
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"text": image_text,
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@@ -75,9 +79,6 @@ async def main(room_url):
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"February",
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"March",
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"April",
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]
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unused_months = [
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"May",
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"June",
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"July",
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@@ -88,11 +89,11 @@ async def main(room_url):
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"December",
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]
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@transport.event_handler("on_participant_joined")
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async def on_participant_joined(transport, participant):
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if participant["id"] == transport.my_participant_id:
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return
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@transport.event_handler("on_first_other_participant_joined")
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async def on_first_other_participant_joined(transport):
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# This will play the months in the order they're completed. The benefit
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# is we'll have as little delay as possible before the first month, and
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# likely no delay between months, but the months won't display in order.
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for month_data_task in asyncio.as_completed(month_tasks):
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data = await month_data_task
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transport.output_queue.put(
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@@ -118,6 +119,6 @@ if __name__=="__main__":
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"-u", "--url", type=str, required=True, help="URL of the Daily room to join"
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)
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args: argparse.Namespace = parser.parse_args()
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args, unknown = parser.parse_known_args()
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asyncio.run(main(args.url))
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@@ -67,7 +67,7 @@ if __name__ == "__main__":
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help="Daily API Key (needed to create token)",
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)
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args: argparse.Namespace = parser.parse_args()
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args, unknown = parser.parse_known_args()
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# Create a meeting token for the given room with an expiration 1 hour in the future.
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room_name: str = urllib.parse.urlparse(args.url).path[1:]
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