Cleanup the last few badly-named Frame types
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@@ -14,7 +14,7 @@ from dailyai.pipeline.frames import (
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SpriteFrame,
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Frame,
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LLMResponseEndFrame,
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LLMMessagesQueueFrame,
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LLMMessagesFrame,
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AudioFrame,
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PipelineStartedFrame,
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)
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@@ -129,7 +129,7 @@ async def main(room_url: str, token):
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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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print(f"!!! in here, pipeline.source is {pipeline.source}")
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await pipeline.queue_frames([LLMMessagesQueueFrame(messages)])
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await pipeline.queue_frames([LLMMessagesFrame(messages)])
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async def run_conversation():
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@@ -24,7 +24,7 @@ from dailyai.pipeline.aggregators import (
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)
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from dailyai.pipeline.frames import (
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EndPipeFrame,
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LLMMessagesQueueFrame,
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LLMMessagesFrame,
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Frame,
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TextFrame,
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LLMResponseEndFrame,
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@@ -172,7 +172,7 @@ class StoryImageGenerator(FrameProcessor):
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prompt = f"You are an illustrator for a children's story book. Here is the story so far:\n\n\"{' '.join(self._story[:-1])}\"\n\nGenerate a prompt for DALL-E to create an illustration for the next page. Here's the sentence for the next page:\n\n\"{self._story[-1:][0]}\"\n\n Your response should start with the phrase \"Children's book illustration of\"."
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msgs = [{"role": "system", "content": prompt}]
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image_prompt = ""
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async for f in self._llm.process_frame(LLMMessagesQueueFrame(msgs)):
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async for f in self._llm.process_frame(LLMMessagesFrame(msgs)):
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if isinstance(f, TextFrame):
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image_prompt += f.text
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async for f in self._img.process_frame(TextFrame(image_prompt)):
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@@ -253,7 +253,7 @@ async def main(room_url: str, token):
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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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LLMMessagesQueueFrame(intro_messages),
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LLMMessagesFrame(intro_messages),
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AudioFrame(sounds["listening.wav"]),
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EndPipeFrame(),
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]
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@@ -7,7 +7,7 @@ from typing import AsyncGenerator
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from dailyai.pipeline.aggregators import (
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SentenceAggregator,
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)
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from dailyai.pipeline.frames import Frame, LLMMessagesQueueFrame, TextFrame
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from dailyai.pipeline.frames import Frame, LLMMessagesFrame, TextFrame
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from dailyai.pipeline.frame_processor import FrameProcessor
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from dailyai.pipeline.pipeline import Pipeline
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from dailyai.transports.daily_transport import DailyTransport
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@@ -44,7 +44,7 @@ class TranslationProcessor(FrameProcessor):
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},
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{"role": "user", "content": frame.text},
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]
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yield LLMMessagesQueueFrame(context)
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yield LLMMessagesFrame(context)
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else:
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yield frame
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