new version
Browse files
app.py
CHANGED
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import os
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import gradio as gr
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import requests
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import json
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from moviepy import VideoFileClip
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import uuid
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import time
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import soundfile as sf
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ELEVENLABS_API_KEY = os.environ.get(
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def extract_audio(video_path, output_format="mp3"):
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if not video_path:
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return None, "No video provided"
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@@ -23,55 +24,7 @@ def extract_audio(video_path, output_format="mp3"):
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except Exception as e:
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return None, f"Error extracting audio: {str(e)}"
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def
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if "error" in transcription:
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return None, transcription["error"]
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transcript_filename = f"transcription_{uuid.uuid4().hex[:8]}.txt"
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try:
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with open(transcript_filename, "w", encoding="utf-8") as f:
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f.write(transcription.get('text', 'No text found'))
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return transcript_filename, "Transcription saved as text file"
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except Exception as e:
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return None, f"Error saving transcription: {str(e)}"
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def process_video_file(video_file, output_format, api_key, model_id):
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if video_file is None:
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return None, "Please upload a video file", None, "No video provided"
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audio_path, message = extract_audio(video_file, output_format)
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if audio_path and os.path.exists(audio_path):
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transcription = transcribe_audio(audio_path, api_key, model_id)
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transcript_file, transcript_message = save_transcription(transcription)
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return audio_path, message, transcript_file, transcript_message
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else:
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return None, message, None, "Audio extraction failed, cannot transcribe"
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def process_video_url(video_url, output_format, api_key, model_id):
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if not video_url.strip():
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return None, "Please enter a video URL", None, "No URL provided"
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video_path, error = download_video_from_url(video_url)
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if error:
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return None, error, None, "Video download failed, cannot transcribe"
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audio_path, message = extract_audio(video_path, output_format)
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if video_path and os.path.exists(video_path):
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try:
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os.remove(video_path)
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except:
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pass
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if audio_path and os.path.exists(audio_path):
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transcription = transcribe_audio(audio_path, api_key, model_id)
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transcript_file, transcript_message = save_transcription(transcription)
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return audio_path, message, transcript_file, transcript_message
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else:
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return None, message, None, "Audio extraction failed, cannot transcribe"
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def transcribe_audio(audio_path, api_key, model_id="scribe_v1"):
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start_time = time.time()
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if not api_key:
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@@ -79,101 +32,133 @@ def transcribe_audio(audio_path, api_key, model_id="scribe_v1"):
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url = "https://api.elevenlabs.io/v1/speech-to-text"
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headers = {
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"xi-api-key": api_key
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"Content-Type": "multipart/form-data" # Explicitly set content type
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}
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try:
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with open(audio_path, "rb") as f:
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files = {
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"file":
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"model_id": (None, model_id)
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}
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response = requests.post(
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headers=headers,
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files=files
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)
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# More detailed error handling
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if response.status_code != 200:
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return {
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"error": f"API request failed with status {response.status_code}",
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"response_text": response.text
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}
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result = response.json()
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except requests.exceptions.RequestException as e:
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return {"error": f"API request failed: {str(e)}"}
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except json.JSONDecodeError:
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return {"error": "Failed to parse API response"}
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except Exception as e:
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return {"error": f"Unexpected error: {str(e)}"}
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end_time = time.time()
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processing_time = end_time - start_time
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# File size calculation
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file_size = os.path.getsize(audio_path) / (1024 * 1024)
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# Audio duration calculation with fallback
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try:
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# Attempt to get audio duration using soundfile
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audio_data, sample_rate = sf.read(audio_path)
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audio_duration = len(audio_data) / sample_rate
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except
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try:
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import librosa
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audio_duration = librosa.get_duration(filename=audio_path)
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except:
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audio_duration = 0
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return {
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"service": "
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"text":
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"processing_time": processing_time,
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"file_size_mb":
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"audio_duration":
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"real_time_factor":
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"processing_speed":
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"raw_response": result
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}
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if __name__ == "__main__":
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import os
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import uuid
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import time
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import json
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import requests
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import soundfile as sf
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import gradio as gr
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from moviepy.editor import VideoFileClip
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ELEVENLABS_API_KEY = os.environ.get('ELEVENLABS_API_KEY', '')
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def extract_audio(video_path, output_format="mp3"):
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if not video_path:
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return None, "No video provided"
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except Exception as e:
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return None, f"Error extracting audio: {str(e)}"
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def transcribe_with_scribe(audio_path, api_key, model_id="scribe_v1"):
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start_time = time.time()
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if not api_key:
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url = "https://api.elevenlabs.io/v1/speech-to-text"
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headers = {
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"xi-api-key": api_key
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}
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try:
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with open(audio_path, "rb") as f:
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files = {
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"file": f,
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"model_id": (None, model_id)
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}
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response = requests.post(url, headers=headers, files=files)
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response.raise_for_status()
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result = response.json()
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except requests.exceptions.RequestException as e:
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return {"error": f"API request failed: {str(e)}"}
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except json.JSONDecodeError:
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return {"error": "Failed to parse API response"}
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end_time = time.time()
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processing_time = end_time - start_time
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file_size = os.path.getsize(audio_path) / (1024 * 1024)
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try:
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audio_data, sample_rate = sf.read(audio_path)
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audio_duration = len(audio_data) / sample_rate
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except:
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try:
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import librosa
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audio_duration = librosa.get_duration(filename=audio_path)
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except:
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audio_duration = 0
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text = result.get('text', '')
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return {
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"service": "Scribe",
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"text": text,
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"processing_time": processing_time,
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"file_size_mb": file_size,
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"audio_duration": audio_duration,
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"real_time_factor": processing_time / audio_duration if audio_duration > 0 else None,
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"processing_speed": audio_duration / processing_time if audio_duration > 0 else None,
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"raw_response": result
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}
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def save_transcription(transcription):
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if "error" in transcription:
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return None, transcription["error"]
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transcript_filename = f"transcription_{uuid.uuid4().hex[:8]}.txt"
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try:
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with open(transcript_filename, "w", encoding="utf-8") as f:
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f.write(transcription.get('text', 'No text found'))
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return transcript_filename, "Transcription saved as text file"
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except Exception as e:
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return None, f"Error saving transcription: {str(e)}"
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def process_video_file(video_input, output_format, api_key, model_id):
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audio_output, audio_status = extract_audio(video_input, output_format)
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if not audio_output:
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return None, audio_status, None, audio_status
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transcription = transcribe_with_scribe(audio_output, api_key, model_id)
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transcript_file, transcript_status = save_transcription(transcription)
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try:
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os.remove(audio_output)
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except Exception:
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pass
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return audio_output, audio_status, transcript_file, transcript_status
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def create_interface():
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with gr.Blocks(title="Video to Audio to Transcription") as app:
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gr.Markdown("# Video => Audio => Transcription")
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with gr.Row():
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api_key = gr.Textbox(
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placeholder="Enter your ElevenLabs API key",
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label="ElevenLabs API Key",
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type="password",
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value=ELEVENLABS_API_KEY
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)
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model_id = gr.Dropdown(
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choices=["scribe_v1"],
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value="scribe_v1",
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label="Transcription Model"
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)
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with gr.Tabs():
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with gr.TabItem("Upload Video"):
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with gr.Row():
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with gr.Column():
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video_input = gr.Video(label="Upload Video")
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format_choice_file = gr.Radio(
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["mp3"],
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value="mp3",
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label="Output Format"
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)
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extract_button_file = gr.Button("Extract Audio & Transcribe")
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with gr.Column():
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audio_output_file = gr.Audio(label="Extracted Audio", type="filepath")
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status_output_file = gr.Textbox(label="Audio Extraction Status")
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transcript_file_output = gr.File(label="Transcription Text File")
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transcript_status_output = gr.Textbox(label="Transcription Status")
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extract_button_file.click(
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fn=process_video_file,
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inputs=[video_input, format_choice_file, api_key, model_id],
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outputs=[
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audio_output_file,
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status_output_file,
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transcript_file_output,
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transcript_status_output
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]
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)
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return app
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def main():
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app = create_interface()
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app.launch()
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if __name__ == "__main__":
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main()
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