added web server
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@@ -20,6 +20,10 @@ class ImageQueueFrame(QueueFrame):
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url: str | None
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image: bytes
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@dataclass()
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class ImageListQueueFrame(QueueFrame):
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images: list[bytes] | None
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@dataclass()
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class TextQueueFrame(QueueFrame):
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text: str
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@@ -12,6 +12,7 @@ from dailyai.queue_frame import (
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AudioQueueFrame,
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EndStreamQueueFrame,
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ImageQueueFrame,
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ImageListQueueFrame,
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QueueFrame,
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StartStreamQueueFrame,
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TranscriptionQueueFrame,
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@@ -149,6 +150,7 @@ class DailyTransportService(EventHandler):
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)
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self.image: bytes | None = None
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self.images: list[bytes] | None = None
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self.camera_thread = Thread(target=self.run_camera, daemon=True)
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self.camera_thread.start()
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@@ -307,12 +309,22 @@ class DailyTransportService(EventHandler):
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def set_image(self, image: bytes):
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self.image: bytes | None = image
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self.images: list[bytes] | None = None
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def set_images(self, images: list[bytes], start_frame=0):
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self.images: list[bytes] | None = images
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self.image = None
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self.current_frame = start_frame
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def run_camera(self):
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try:
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while not self.stop_threads.is_set():
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if self.image:
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self.camera.write_frame(self.image)
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if self.images:
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this_frame = self.current_frame % len(self.images)
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self.camera.write_frame(self.sprites[self.images[this_frame]])
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self.current_frame = this_frame + 1
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time.sleep(1.0 / 8) # 8 fps
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except Exception as e:
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@@ -354,6 +366,8 @@ class DailyTransportService(EventHandler):
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b = b[l:]
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elif isinstance(frame, ImageQueueFrame):
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self.set_image(frame.image)
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elif isinstance(frame, ImageListQueueFrame):
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self.set_images(frame.images)
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elif len(b):
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self.mic.write_frames(bytes(b))
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b = bytearray()
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@@ -8,6 +8,7 @@ from dailyai.services.daily_transport_service import DailyTransportService
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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.fal_ai_services import FalImageGenService
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from dailyai.services.open_ai_services import OpenAIImageGenService
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from dailyai.queue_aggregators import LLMContextAggregator
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from dailyai.queue_frame import LLMMessagesQueueFrame, QueueFrame, TextQueueFrame
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from dailyai.services.ai_services import AIService
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@@ -73,11 +74,12 @@ async def main(room_url:str, token):
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)
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async def make_cats():
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imagegen = FalImageGenService(image_size="1024x1024")
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imagegen = OpenAIImageGenService(image_size="1024x1024")
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while True:
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imagegen.run_to_queue(transport.send_queue, [TextQueueFrame("a golden kitty trophy, cartoon, colorful, detailed, 4k")])
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await asyncio.sleep(60)
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print("generating new image")
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await imagegen.run_to_queue(transport.send_queue, [TextQueueFrame("a golden kitty trophy, cartoon, colorful, detailed, 4k")])
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await asyncio.sleep(10)
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transport.transcription_settings["extra"]["punctuate"] = True
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await asyncio.gather(transport.run(), handle_transcriptions(), make_cats())
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@@ -101,9 +103,9 @@ if __name__ == "__main__":
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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 5 hours in the future.
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# Create a meeting token for the given room with an expiration 24 hours in the future.
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room_name: str = urllib.parse.urlparse(args.url).path[1:]
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expiration: float = time.time() + 60 * 60 * 5
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expiration: float = time.time() + 60 * 60 * 24
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res: requests.Response = requests.post(
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f"https://api.daily.co/v1/meeting-tokens",
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BIN
src/samples/foundational/images/cat1.png
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src/samples/foundational/images/cat1.png
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src/samples/foundational/images/cat2.png
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src/samples/foundational/images/cat2.png
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src/samples/foundational/images/cat3.png
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src/samples/foundational/images/cat3.png
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After Width: | Height: | Size: 1.7 MiB |
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