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import os
import gradio as gr
import requests
import json
from moviepy import VideoFileClip
import uuid
ELEVENLABS_API_KEY = os.environ.get("ELEVENLABS_API_KEY", None)
def extract_audio(video_path, output_format="mp3"):
if not video_path:
return None, "No video provided"
output_path = f"extracted_audio_{uuid.uuid4().hex[:8]}.{output_format}"
try:
video = VideoFileClip(video_path)
video.audio.write_audiofile(output_path, logger=None)
video.close()
return output_path, f"Audio extracted successfully"
except Exception as e:
return None, f"Error extracting audio: {str(e)}"
def save_transcription(transcription):
if "error" in transcription:
return None, transcription["error"]
transcript_filename = f"transcription_{uuid.uuid4().hex[:8]}.txt"
try:
with open(transcript_filename, "w", encoding="utf-8") as f:
f.write(transcription.get('text', 'No text found'))
return transcript_filename, "Transcription saved as text file"
except Exception as e:
return None, f"Error saving transcription: {str(e)}"
def process_video_file(video_file, output_format, api_key, model_id):
if video_file is None:
return None, "Please upload a video file", None, "No video provided"
audio_path, message = extract_audio(video_file, output_format)
if audio_path and os.path.exists(audio_path):
transcription = transcribe_audio(audio_path, api_key, model_id)
transcript_file, transcript_message = save_transcription(transcription)
return audio_path, message, transcript_file, transcript_message
else:
return None, message, None, "Audio extraction failed, cannot transcribe"
def process_video_url(video_url, output_format, api_key, model_id):
if not video_url.strip():
return None, "Please enter a video URL", None, "No URL provided"
video_path, error = download_video_from_url(video_url)
if error:
return None, error, None, "Video download failed, cannot transcribe"
audio_path, message = extract_audio(video_path, output_format)
if video_path and os.path.exists(video_path):
try:
os.remove(video_path)
except:
pass
if audio_path and os.path.exists(audio_path):
transcription = transcribe_audio(audio_path, api_key, model_id)
transcript_file, transcript_message = save_transcription(transcription)
return audio_path, message, transcript_file, transcript_message
else:
return None, message, None, "Audio extraction failed, cannot transcribe"
def transcribe_audio(audio_file, api_key, model_id="scribe_v1"):
if not api_key:
return {"error": "Please provide an API key"}
url = "https://api.elevenlabs.io/v1/speech-to-text"
headers = {
"xi-api-key": api_key
}
try:
with open(audio_file, "rb") as f:
files = {
"file": f,
"model_id": (None, model_id)
}
response = requests.post(url, headers=headers, files=files)
response.raise_for_status()
result = response.json()
return result
except requests.exceptions.RequestException as e:
return {"error": f"API request failed: {str(e)}"}
except json.JSONDecodeError:
return {"error": "Failed to parse API response"}
with gr.Blocks(title="Video to Audio to Transcription") as app:
gr.Markdown("# Video => Audio => Transcription")
api_key = gr.Textbox(
placeholder="Enter your ElevenLabs API key",
label="ElevenLabs API Key",
type="password",
value=ELEVENLABS_API_KEY
)
model_id = gr.Dropdown(
choices=["scribe_v1"],
value="scribe_v1",
label="Transcription Model"
)
with gr.Tabs():
with gr.TabItem("Upload Video"):
with gr.Row():
with gr.Column():
video_input = gr.Video(label="Upload Video")
format_choice_file = gr.Radio(["mp3", "wav"], value="mp3", label="Output Format")
extract_button_file = gr.Button("Extract Audio & Transcribe")
with gr.Column():
audio_output_file = gr.Audio(label="Extracted Audio", type="filepath")
status_output_file = gr.Textbox(label="Audio Extraction Status")
transcript_file_output = gr.File(label="Transcription Text File")
transcript_status_output = gr.Textbox(label="Transcription Status")
extract_button_file.click(
fn=process_video_file,
inputs=[video_input, format_choice_file, api_key, model_id],
outputs=[audio_output_file, status_output_file, transcript_file_output, transcript_status_output]
)
if __name__ == "__main__":
app.launch() |