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add convert to audio
Browse files- Dockerfile +4 -0
- libs/convert_to_audio.py +18 -0
- routers/get_transcript.py +19 -3
Dockerfile
CHANGED
@@ -1,6 +1,10 @@
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# Use the official Python 3.10.9 image
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FROM python:3.12.1
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WORKDIR /app
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# Copy the current directory contents into the container at .
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# Use the official Python 3.10.9 image
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FROM python:3.12.1
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RUN apt-get update -qq && apt-get install ffmpeg -y
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WORKDIR /app
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# Copy the current directory contents into the container at .
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libs/convert_to_audio.py
ADDED
@@ -0,0 +1,18 @@
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import os
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import subprocess
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def convert_to_audio(input_file, output_file):
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ffmpeg_command = [
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"ffmpeg",
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"-i", input_file,
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"-vn",
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"-acodec", "libmp3lame",
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"-ab", "96k",
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"-ar", "44100",
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"-y",
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output_file
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]
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try:
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subprocess.run(ffmpeg_command, check=True)
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except subprocess.CalledProcessError as e:
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print("Error: failed to convert audio")
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routers/get_transcript.py
CHANGED
@@ -2,6 +2,9 @@ import time
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from fastapi import APIRouter, Depends, HTTPException, status
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from faster_whisper import WhisperModel
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from libs.header_api_auth import get_api_key
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router = APIRouter(prefix="/get-transcript", tags=["transcript"])
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@@ -23,18 +26,29 @@ def get_transcript(audio_path: str, model_size: str = "distil-large-v3", api_key
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print(f"model>>>: {model_size}")
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st = time.time()
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try:
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model_run = WhisperModel(model_size, device="cpu", compute_type="int8")
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segments, info = model_run.transcribe(
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beam_size=16,
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language="en",
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condition_on_previous_text=False,
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)
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except Exception as error:
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raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail=f"error>>>: {error}")
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text = ""
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@@ -49,11 +63,13 @@ def get_transcript(audio_path: str, model_size: str = "distil-large-v3", api_key
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"text": segment.text
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})
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et = time.time()
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elapsed_time = et - st
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return {"text": text,
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'list_sentence': listSentences
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}
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# time.sleep(5)
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from fastapi import APIRouter, Depends, HTTPException, status
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from faster_whisper import WhisperModel
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import os
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from libs.convert_to_audio import convert_to_audio
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from libs.header_api_auth import get_api_key
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router = APIRouter(prefix="/get-transcript", tags=["transcript"])
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print(f"model>>>: {model_size}")
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output_audio_folder = f"./cached/audio"
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if not os.path.exists(output_audio_folder):
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os.makedirs(output_audio_folder)
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output_file = f"{output_audio_folder}/{audio_path.split('/')[-1].split(".")[0]}.mp3"
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st = time.time()
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convert_to_audio(audio_path.strip(), output_file)
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try:
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model_run = WhisperModel(model_size, device="cpu", compute_type="int8")
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segments, info = model_run.transcribe(
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output_file,
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beam_size=16,
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language="en",
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condition_on_previous_text=False,
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)
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os.remove(output_file)
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except Exception as error:
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if os.path.exists(output_file):
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os.remove(output_file)
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raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail=f"error>>>: {error}")
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text = ""
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"text": segment.text
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})
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et = time.time()
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elapsed_time = et - st
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return {"text": text,
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'list_sentence': listSentences,
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'elapsed_time': round(elapsed_time, 2)
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}
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# time.sleep(5)
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