introduce Ruff formatting

This commit is contained in:
Aleix Conchillo Flaqué
2024-09-23 09:11:37 -07:00
parent dfa4ac81fd
commit eeb8338dce
149 changed files with 2653 additions and 2461 deletions

View File

@@ -43,6 +43,7 @@ from runner import configure
from loguru import logger
from dotenv import load_dotenv
load_dotenv(override=True)
logger.remove(0)
@@ -60,11 +61,7 @@ for i in range(1, 26):
# Get the filename without the extension to use as the dictionary key
# Open the image and convert it to bytes
with Image.open(full_path) as img:
sprites.append(OutputImageRawFrame(
image=img.tobytes(),
size=img.size,
format=img.format)
)
sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
flipped = sprites[::-1]
sprites.extend(flipped)
@@ -110,7 +107,9 @@ class UserImageRequester(FrameProcessor):
if self.participant_id and isinstance(frame, TextFrame):
if frame.text == user_request_answer:
await self.push_frame(UserImageRequestFrame(self.participant_id), FrameDirection.UPSTREAM)
await self.push_frame(
UserImageRequestFrame(self.participant_id), FrameDirection.UPSTREAM
)
await self.push_frame(TextFrame("Describe the image in a short sentence."))
elif isinstance(frame, UserImageRawFrame):
await self.push_frame(frame)
@@ -154,8 +153,8 @@ async def main():
camera_out_height=576,
transcription_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer()
)
vad_analyzer=SileroVADAnalyzer(),
),
)
tts = CartesiaTTSService(
@@ -163,9 +162,7 @@ async def main():
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)
llm = OpenAILLMService(
api_key=os.getenv("OPENAI_API_KEY"),
model="gpt-4o")
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
ta = TalkingAnimation()
@@ -188,17 +185,17 @@ async def main():
ura = LLMUserResponseAggregator(messages)
pipeline = Pipeline([
transport.input(),
ura,
llm,
ParallelPipeline(
[sa, ir, va, moondream],
[tf, imgf]),
tts,
ta,
transport.output()
])
pipeline = Pipeline(
[
transport.input(),
ura,
llm,
ParallelPipeline([sa, ir, va, moondream], [tf, imgf]),
tts,
ta,
transport.output(),
]
)
task = PipelineTask(pipeline)
await task.queue_frame(quiet_frame)