mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
Mathieu Virbel
d94e2911c3
* serverless: implement banana backend for both audio and LLM Related to monadical-sas/reflector-gpu-banana project * serverless: got llm working on banana ! * tests: fixes * serverless: fix dockerfile to use fastapi server + httpx
86 lines
2.7 KiB
Python
86 lines
2.7 KiB
Python
"""
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Implementation using the GPU service from banana.
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API will be a POST request to TRANSCRIPT_URL:
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```json
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{
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"audio_url": "https://...",
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"audio_ext": "wav",
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"timestamp": 123.456
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"language": "en"
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}
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```
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"""
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from reflector.processors.audio_transcript import AudioTranscriptProcessor
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from reflector.processors.audio_transcript_auto import AudioTranscriptAutoProcessor
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from reflector.processors.types import AudioFile, Transcript, Word
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from reflector.settings import settings
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from reflector.storage import Storage
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from reflector.utils.retry import retry
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from pathlib import Path
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import httpx
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class AudioTranscriptBananaProcessor(AudioTranscriptProcessor):
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def __init__(self, banana_api_key: str, banana_model_key: str):
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super().__init__()
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self.transcript_url = settings.TRANSCRIPT_URL
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self.timeout = settings.TRANSCRIPT_TIMEOUT
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self.storage = Storage.get_instance(
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settings.TRANSCRIPT_STORAGE_BACKEND, "TRANSCRIPT_STORAGE_"
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)
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self.headers = {
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"X-Banana-API-Key": banana_api_key,
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"X-Banana-Model-Key": banana_model_key,
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}
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async def _transcript(self, data: AudioFile):
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async with httpx.AsyncClient() as client:
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print(f"Uploading audio {data.path.name} to S3")
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url = await self._upload_file(data.path)
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print(f"Try to transcribe audio {data.path.name}")
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request_data = {
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"audio_url": url,
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"audio_ext": data.path.suffix[1:],
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"timestamp": float(round(data.timestamp, 2)),
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}
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response = await retry(client.post)(
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self.transcript_url,
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json=request_data,
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headers=self.headers,
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timeout=self.timeout,
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)
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print(f"Transcript response: {response.status_code} {response.content}")
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response.raise_for_status()
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result = response.json()
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transcript = Transcript(
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text=result["text"],
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words=[
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Word(text=word["text"], start=word["start"], end=word["end"])
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for word in result["words"]
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],
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)
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# remove audio file from S3
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await self._delete_file(data.path)
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return transcript
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@retry
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async def _upload_file(self, path: Path) -> str:
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upload_result = await self.storage.put_file(path.name, open(path, "rb"))
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return upload_result.url
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@retry
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async def _delete_file(self, path: Path):
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await self.storage.delete_file(path.name)
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return True
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AudioTranscriptAutoProcessor.register("banana", AudioTranscriptBananaProcessor)
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