Update app.py

app.py

@@ -1,77 +1,58 @@
-from flask import Flask, request, render_template, redirect, url_for
-import os
-from moviepy.editor import VideoFileClip
-import whisper
-
-app = Flask(__name__)
-
-# Add ffmpeg to the PATH
-ffmpeg_path = r'C:\Users\M&G\Downloads\ffmpeg-7.0.1-essentials_build\bin'  # Replace with your actual path
-
-if not os.path.isdir(ffmpeg_path):
-    raise FileNotFoundError(f"FFmpeg directory not found: {ffmpeg_path}")
-os.environ['PATH'] += os.pathsep + ffmpeg_path
-
-# Verify that ffmpeg is available
-try:
-    from subprocess import check_output
-    ffmpeg_version = check_output(['ffmpeg', '-version'], text=True)
-    print("FFmpeg is available. Version details:\n", ffmpeg_version)
-except FileNotFoundError:
-    raise RuntimeError("FFmpeg executable not found in the specified PATH.")
-except Exception as e:
-    raise RuntimeError(f"Error checking FFmpeg version: {e}")
-
-# Load the Whisper model
-model = whisper.load_model("medium")
-
-@app.route('/')
-def index():
-    return render_template('index.html')
-
-@app.route('/upload', methods=['POST'])
-def upload_video():
-    if 'video' not in request.files:
-        return redirect(url_for('index'))
-
-    video_file = request.files['video']
-    if video_file.filename == '':
-        return redirect(url_for('index'))
-
-    # Save the video file
-    video_path = os.path.join('uploads', video_file.filename)
-    video_file.save(video_path)
-
-    try:
-        # Extract audio from the video
-        audio_path = extract_audio(video_path)
-        # Transcribe the audio
-        transcript = transcribe_audio(audio_path)
-    except Exception as e:
-        return f"Error: {e}"
-
-    return render_template('result.html', transcript=transcript)
-
-def extract_audio(video_path):
-    audio_path = os.path.splitext(video_path)[0] + ".wav"
-    try:
-        video = VideoFileClip(video_path)
-        video.audio.write_audiofile(audio_path)
-    except Exception as e:
-        raise RuntimeError(f"Error extracting audio: {e}")
-    return audio_path
-
-def transcribe_audio(audio_path):
-    if not os.path.exists(audio_path):
-        raise FileNotFoundError(f"Audio file not found at {audio_path}")
-
-    try:
-        result = model.transcribe(audio_path)
-        return result["text"]
-    except Exception as e:
-        raise RuntimeError(f"Error during transcription: {e}")
-
-if __name__ == '__main__':
-    if not os.path.exists('uploads'):
-        os.makedirs('uploads')
-    app.run(debug=True)
+from flask import Flask, request, render_template, redirect, url_for
+import os
+from moviepy.editor import VideoFileClip
+import whisper
+
+app = Flask(__name__)
+
+# Add ffmpeg to the PATH
+ffmpeg_path = r'/usr/bin/ffmpeg'  # Path for ffmpeg in the Docker container
+
+# Load the Whisper model
+model = whisper.load_model("medium")  # Change to "large" for the most accurate model
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/upload', methods=['POST'])
+def upload_video():
+    if 'video' not in request.files:
+        return redirect(url_for('index'))
+
+    video_file = request.files['video']
+    if video_file.filename == '':
+        return redirect(url_for('index'))
+
+    # Save the video file
+    video_path = os.path.join('uploads', video_file.filename)
+    video_file.save(video_path)
+
+    try:
+        # Extract audio from the video
+        audio_path = extract_audio(video_path)
+        # Transcribe the audio
+        transcript = transcribe_audio(audio_path)
+    except Exception as e:
+        return f"Error: {e}"
+
+    return render_template('result.html', transcript=transcript, model_name="medium")  # Adjust model name accordingly
+
+def extract_audio(video_path):
+    audio_path = os.path.splitext(video_path)[0] + ".wav"
+    try:
+        video = VideoFileClip(video_path)
+        video.audio.write_audiofile(audio_path)
+    except Exception as e:
+        raise RuntimeError(f"Error extracting audio: {e}")
+    return audio_path
+
+def transcribe_audio(audio_path):
+    if not os.path.exists(audio_path):
+        raise FileNotFoundError(f"Audio file not found at {audio_path}")
+
+    try:
+        result = model.transcribe(audio_path)
+        return result["text"]
+    except Exception as e:
+        raise RuntimeError(f"Error during transcription: {e}")