updated ImageFrame and added URLImageFrame and UserImageFrame
This commit is contained in:
@@ -5,7 +5,7 @@ import tkinter as tk
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import os
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from dailyai.pipeline.aggregators import LLMFullResponseAggregator
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from dailyai.pipeline.frames import AudioFrame, ImageFrame, LLMMessagesFrame, TextFrame
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from dailyai.pipeline.frames import AudioFrame, URLImageFrame, LLMMessagesFrame, TextFrame
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from dailyai.services.open_ai_services import OpenAILLMService
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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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@@ -94,6 +94,7 @@ async def main():
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"text": image_description,
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"image_url": image_data[0],
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"image": image_data[1],
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"image_size": image_data[2],
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"audio": audio,
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}
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@@ -117,7 +118,7 @@ async def main():
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if data:
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await transport.send_queue.put(
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[
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ImageFrame(data["image_url"], data["image"]),
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URLImageFrame(data["image_url"], data["image"], data["image_size"]),
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AudioFrame(data["audio"]),
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]
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)
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@@ -35,9 +35,9 @@ class ImageSyncAggregator(AIService):
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self._waiting_image_bytes = self._waiting_image.tobytes()
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async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
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yield ImageFrame(None, self._speaking_image_bytes)
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yield ImageFrame(self._speaking_image_bytes, (1024, 1024))
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yield frame
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yield ImageFrame(None, self._waiting_image_bytes)
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yield ImageFrame(self._waiting_image_bytes, (1024, 1024))
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async def main(room_url: str, token):
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@@ -122,7 +122,7 @@ async def main(room_url: str):
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)
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await transport.send_queue.put(
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[
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ImageFrame(None, image_data1[1]),
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ImageFrame(image_data1[1], image_data1[2]),
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AudioFrame(audio1),
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]
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)
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@@ -134,7 +134,7 @@ async def main(room_url: str):
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)
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await transport.send_queue.put(
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[
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ImageFrame(None, image_data2[1]),
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ImageFrame(image_data2[1], image_data2[2]),
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AudioFrame(audio2),
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]
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)
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@@ -55,7 +55,7 @@ for file in image_files:
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sprites[file] = img.tobytes()
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# When the bot isn't talking, show a static image of the cat listening
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quiet_frame = ImageFrame("", sprites["sc-listen-1.png"])
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quiet_frame = ImageFrame(sprites["sc-listen-1.png"], (720, 1280))
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# When the bot is talking, build an animation from two sprites
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talking_list = [sprites["sc-default.png"], sprites["sc-talk.png"]]
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talking = [random.choice(talking_list) for x in range(30)]
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@@ -48,7 +48,7 @@ for i in range(1, 26):
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flipped = sprites[::-1]
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sprites.extend(flipped)
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# When the bot isn't talking, show a static image of the cat listening
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quiet_frame = ImageFrame("", sprites[0])
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quiet_frame = ImageFrame(sprites[0], (1024, 576))
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talking_frame = SpriteFrame(images=sprites)
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@@ -99,7 +99,7 @@ class StoryProcessor(FrameProcessor):
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1. Catch the frames that are generated by the LLM service
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"""
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if isinstance(frame, UserStoppedSpeakingFrame):
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yield ImageFrame(None, images["grandma-writing.png"])
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yield ImageFrame(images["grandma-writing.png"], (1024, 1024))
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yield AudioFrame(sounds["talking.wav"])
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elif isinstance(frame, TextFrame):
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@@ -112,7 +112,7 @@ class StoryProcessor(FrameProcessor):
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self._text = self._text.replace("\n", " ")
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if len(self._text) > 2:
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yield ImageFrame(None, images["grandma-writing.png"])
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yield ImageFrame(images["grandma-writing.png"], (1024, 1024))
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yield StoryStartFrame(self._text)
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yield AudioFrame(sounds["ding3.wav"])
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self._text = ""
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@@ -146,11 +146,11 @@ class StoryProcessor(FrameProcessor):
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# last bit
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pass
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elif isinstance(frame, LLMResponseEndFrame):
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yield ImageFrame(None, images["grandma-writing.png"])
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yield ImageFrame(images["grandma-writing.png"], (1024, 1024))
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yield StoryPromptFrame(self._text)
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self._text = ""
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yield frame
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yield ImageFrame(None, images["grandma-listening.png"])
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yield ImageFrame(images["grandma-listening.png"], (1024, 1024))
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yield AudioFrame(sounds["listening.wav"])
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else:
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@@ -252,7 +252,7 @@ async def main(room_url: str, token):
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[llm, lca, tts], sink=transport.send_queue)
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await local_pipeline.queue_frames(
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[
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ImageFrame(None, images["grandma-listening.png"]),
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ImageFrame(images["grandma-listening.png"], (1024, 1024)),
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LLMMessagesFrame(intro_messages),
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AudioFrame(sounds["listening.wav"]),
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EndPipeFrame(),
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@@ -360,7 +360,7 @@ class GatedAggregator(FrameProcessor):
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... start_open=False)
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>>> asyncio.run(print_frames(aggregator, TextFrame("Hello")))
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>>> asyncio.run(print_frames(aggregator, TextFrame("Hello again.")))
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>>> asyncio.run(print_frames(aggregator, ImageFrame(url='', image=bytes([]))))
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>>> asyncio.run(print_frames(aggregator, ImageFrame(image=bytes([]), size=(0, 0))))
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ImageFrame
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Hello
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Hello again.
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@@ -70,11 +70,39 @@ class AudioFrame(Frame):
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class ImageFrame(Frame):
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"""An image. Will be shown by the transport if the transport's camera is
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enabled."""
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url: str | None
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image: bytes
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size: tuple[int, int]
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def __str__(self):
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return f"{self.__class__.__name__}, url: {self.url}, image size: {len(self.image)} B"
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return f"{self.__class__.__name__}, image size: {self.size[0]}x{self.size[1]} buffer size: {len(self.image)} B"
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@dataclass()
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class URLImageFrame(ImageFrame):
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"""An image. Will be shown by the transport if the transport's camera is
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enabled."""
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url: str | None
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def __init__(self, url, image, size):
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super().__init__(image, size)
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self.url = url
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def __str__(self):
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return f"{self.__class__.__name__}, url: {self.url}, image size: {self.size[0]}x{self.size[1]}, buffer size: {len(self.image)} B"
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@dataclass()
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class UserImageFrame(ImageFrame):
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"""An image associated to a user. Will be shown by the transport if the transport's camera is
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enabled."""
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user_id: str
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def __init__(self, user_id, image, size):
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super().__init__(image, size)
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self.user_id = user_id
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def __str__(self):
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return f"{self.__class__.__name__}, user: {self.user_id}, image size: {self.size[0]}x{self.size[1]}, buffer size: {len(self.image)} B"
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@dataclass()
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@@ -14,6 +14,7 @@ from dailyai.pipeline.frames import (
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TTSStartFrame,
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TextFrame,
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TranscriptionFrame,
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URLImageFrame,
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)
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from abc import abstractmethod
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@@ -87,7 +88,7 @@ class ImageGenService(AIService):
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# Renders the image. Returns an Image object.
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@abstractmethod
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async def run_image_gen(self, sentence: str) -> tuple[str, bytes]:
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async def run_image_gen(self, sentence: str) -> tuple[str, bytes, tuple[int, int]]:
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pass
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async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
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@@ -95,8 +96,8 @@ class ImageGenService(AIService):
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yield frame
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return
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(url, image_data) = await self.run_image_gen(frame.text)
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yield ImageFrame(url, image_data)
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(url, image_data, image_size) = await self.run_image_gen(frame.text)
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yield URLImageFrame(url, image_data, image_size)
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class STTService(AIService):
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@@ -105,7 +105,7 @@ class AzureImageGenServiceREST(ImageGenService):
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self._model = model
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self._aiohttp_session = aiohttp_session
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async def run_image_gen(self, sentence) -> tuple[str, bytes]:
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async def run_image_gen(self, sentence) -> tuple[str, bytes, tuple[int, int]]:
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url = f"{self._azure_endpoint}openai/images/generations:submit?api-version={self._api_version}"
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headers = {
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"api-key": self._api_key,
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@@ -146,4 +146,4 @@ class AzureImageGenServiceREST(ImageGenService):
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async with self._aiohttp_session.get(image_url) as response:
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image_stream = io.BytesIO(await response.content.read())
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image = Image.open(image_stream)
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return (image_url, image.tobytes())
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return (image_url, image.tobytes(), image.size)
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@@ -31,7 +31,7 @@ class FalImageGenService(ImageGenService):
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if key_secret:
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os.environ["FAL_KEY_SECRET"] = key_secret
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async def run_image_gen(self, sentence) -> tuple[str, bytes]:
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async def run_image_gen(self, sentence) -> tuple[str, bytes, tuple[int, int]]:
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def get_image_url(sentence, size):
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handler = fal.apps.submit(
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"110602490-fast-sdxl",
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@@ -55,4 +55,4 @@ class FalImageGenService(ImageGenService):
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async with self._aiohttp_session.get(image_url) as response:
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image_stream = io.BytesIO(await response.content.read())
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image = Image.open(image_stream)
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return (image_url, image.tobytes())
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return (image_url, image.tobytes(), image.size)
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@@ -36,7 +36,7 @@ class OpenAIImageGenService(ImageGenService):
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self._client = AsyncOpenAI(api_key=api_key)
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self._aiohttp_session = aiohttp_session
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async def run_image_gen(self, sentence) -> tuple[str, bytes]:
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async def run_image_gen(self, sentence) -> tuple[str, bytes, tuple[int, int]]:
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self.logger.info("Generating OpenAI image", sentence)
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image = await self._client.images.generate(
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@@ -53,4 +53,4 @@ class OpenAIImageGenService(ImageGenService):
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async with self._aiohttp_session.get(image_url) as response:
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image_stream = io.BytesIO(await response.content.read())
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image = Image.open(image_stream)
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return (image_url, image.tobytes())
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return (image_url, image.tobytes(), image.size)
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@@ -19,7 +19,7 @@ class MockAIService(AIService):
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image_stream = io.BytesIO(response.content)
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image = Image.open(image_stream)
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time.sleep(1)
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return (image_url, image)
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return (image_url, image.tobytes(), image.size)
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def run_llm(self, messages, latest_user_message=None, stream=True):
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for i in range(5):
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@@ -2,6 +2,7 @@ import asyncio
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import inspect
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import logging
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import signal
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import time
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import threading
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import types
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@@ -11,6 +12,7 @@ from typing import Any
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from dailyai.pipeline.frames import (
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ReceivedAppMessageFrame,
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TranscriptionFrame,
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UserImageFrame,
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)
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from threading import Event
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@@ -58,6 +60,7 @@ class DailyTransport(ThreadedTransport, EventHandler):
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bot_name: str,
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min_others_count: int = 1,
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start_transcription: bool = False,
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video_rendering_enabled: bool = False,
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**kwargs,
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):
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kwargs['has_webrtc_vad'] = True
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@@ -69,6 +72,7 @@ class DailyTransport(ThreadedTransport, EventHandler):
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self._token: str | None = token
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self._min_others_count = min_others_count
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self._start_transcription = start_transcription
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self._video_rendering_enabled = video_rendering_enabled
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self._is_interrupted = Event()
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self._stop_threads = Event()
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@@ -76,6 +80,8 @@ class DailyTransport(ThreadedTransport, EventHandler):
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self._other_participant_has_joined = False
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self._my_participant_id = None
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self._video_renderers = {}
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self.transcription_settings = {
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"language": "en",
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"tier": "nova",
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@@ -236,7 +242,7 @@ class DailyTransport(ThreadedTransport, EventHandler):
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self.client.update_subscription_profiles({
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"base": {
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"camera": "unsubscribed",
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"camera": "subscribed" if self._video_rendering_enabled else "unsubscribed",
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}
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})
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@@ -268,6 +274,37 @@ class DailyTransport(ThreadedTransport, EventHandler):
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def start_recording(self):
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self.client.start_recording()
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def render_participant_video(self,
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participant_id,
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framerate=10,
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video_source="camera",
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color_format="RGB") -> None:
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if not self._video_rendering_enabled:
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self._logger.warn("Video rendering is not enabled")
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self._video_renderers[participant_id] = {
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"framerate": framerate,
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"timestamp": 0,
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}
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self.client.set_video_renderer(
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participant_id,
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self.on_participant_video_frame,
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video_source=video_source,
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color_format=color_format)
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def on_participant_video_frame(self, participant_id, video_frame):
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curr_time = time.time()
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prev_time = self._video_renderers[participant_id]["timestamp"]
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diff_time = curr_time - prev_time
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period = 1 / self._video_renderers[participant_id]["framerate"]
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if diff_time > period and self._loop:
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self._video_renderers[participant_id]["timestamp"] = curr_time
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frame = UserImageFrame(participant_id, video_frame.buffer,
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(video_frame.width, video_frame.height))
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asyncio.run_coroutine_threadsafe(
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self.receive_queue.put(frame), self._loop
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)
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def on_error(self, error):
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self._logger.error(f"on_error: {error}")
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@@ -54,13 +54,13 @@ class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
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TextFrame("Hello, "),
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TextFrame("world."),
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AudioFrame(b"hello"),
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ImageFrame("image", b"image"),
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ImageFrame(b"image", (0, 0)),
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AudioFrame(b"world"),
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LLMResponseEndFrame(),
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]
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expected_output_frames = [
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ImageFrame("image", b"image"),
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ImageFrame(b"image", (0, 0)),
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LLMResponseStartFrame(),
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TextFrame("Hello, "),
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TextFrame("world."),
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@@ -68,7 +68,7 @@ class TestDailyTransport(unittest.IsolatedAsyncioTestCase):
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await transport.send_queue.put(AudioFrame(bytes([0] * 3300)))
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async def send_video_frame():
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await transport.send_queue.put(ImageFrame(None, b"test"))
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await transport.send_queue.put(ImageFrame(b"test", (0, 0)))
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await asyncio.gather(transport.run(), send_audio_frame(), send_video_frame())
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