Transcriptify.py

import os
import time
import openai
from tqdm import tqdm
import subprocess

# Define API key file path
API_KEY_PATH = os.path.expanduser("~/.openai")

# Load API key from file if it exists
if os.path.isfile(API_KEY_PATH):
 with open(API_KEY_PATH, "r") as f:
 api_key = f.read().strip()
 openai.api_key = api_key

# Ask for API key if it's not loaded
while not openai.api_key:
 api_key = input("Please enter your OpenAI API key: ").strip()
 openai.api_key = api_key
 # Save API key to file
 with open(API_KEY_PATH, "w") as f:
 f.write(api_key)

# Get ffmpeg path
if os.name == 'nt': # Windows system
 try:
 ffmpeg_path = subprocess.check_output(['where', 'ffmpeg']).decode().strip()
 except:
 print('Please make sure ffmpeg is installed and added to the PATH environment variable')
 exit()
else: # Linux and Mac systems
 try:
 ffmpeg_path = subprocess.check_output(['which', 'ffmpeg']).decode().strip()
 except:
 print('Please make sure ffmpeg is installed and added to the PATH environment variable')
 exit()

def compress_audio(input_file):
 # Get input file size
 file_size = os.path.getsize(input_file)
 if file_size <= 25000000:
 return input_file

 # Compress audio file using ffmpeg
 output_file = f"{os.path.splitext(input_file)[0]}_compressed.mp3"
 command = f"{ffmpeg_path} -i {input_file} -ac 1 -ar 16000 -ab 32k {output_file}"
 os.system(command)

 return output_file

def transcribe_audio(input_file, output_file, response_format, progress_bar):
 with open(input_file, "rb") as f:
 transcript = openai.Audio.transcribe("whisper-1", f, response_format=response_format)

 progress_bar.update(100)

 with open(output_file, "w", encoding="utf-8") as f:
 f.write(transcript)

 # Remove compressed file
 compressed_file = f"{os.path.splitext(input_file)[0]}_compressed.mp3"
 if os.path.exists(compressed_file):
 os.remove(compressed_file)

input_file = input("Please enter the audio file name (including extension): ").strip("'\"")
output_format = input("Please enter the output format (txt, vtt, srt, tsv, json, all): ").strip("'\"")

if output_format not in ["txt", "vtt", "srt", "tsv", "json", "all"]:
 print("Invalid output format.")
 exit()

file_name, _ = os.path.splitext(input_file)
output_file = f"{file_name}_transcript.{output_format}"

# Compress audio file if larger than 25MB
input_file = compress_audio(input_file)

progress_bar = tqdm(total=100, desc="Transcribing audio", ncols=80)

start_time = time.time()

transcribe_audio(input_file, output_file, output_format, progress_bar)

progress_bar.close()

elapsed_time = time.time() - start_time
print(f"Audio transcription completed in {elapsed_time:.2f} seconds")

print(f"Transcript saved to {output_file}")