Update app.py

app.py

@@ -1,123 +1,153 @@
-from flask import Flask, request, jsonify, Response  # Add Response here
-from faster_whisper import WhisperModel
-import torch
-import io
-import time
-import datetime
-from threading import Semaphore
-import os
-from werkzeug.utils import secure_filename
-import tempfile
-
-app = Flask(__name__)
-
-# Configuration
-MAX_CONCURRENT_REQUESTS = 2  # Adjust based on your server capacity
-MAX_AUDIO_DURATION = 60 * 30  # 30 minutes maximum audio duration (adjust as needed)
-TEMPORARY_FOLDER = tempfile.gettempdir()
-ALLOWED_EXTENSIONS = {'mp3', 'wav', 'ogg', 'm4a', 'flac'}
-
-# Device check for faster-whisper
-device = "cuda" if torch.cuda.is_available() else "cpu"
-compute_type = "float16" if device == "cuda" else "int8"
-print(f"Using device: {device} with compute_type: {compute_type}")
-
-# Faster Whisper setup with optimized parameters for long audio
-beamsize = 2  # Slightly larger beam size can help with long-form accuracy
-wmodel = WhisperModel(
-    "guillaumekln/faster-whisper-small",
-    device=device,
-    compute_type=compute_type,
-    download_root="./model_cache"  # Cache model to avoid re-downloading
-)
-
-# Concurrency control
-request_semaphore = Semaphore(MAX_CONCURRENT_REQUESTS)
-active_requests = 0
-
-def allowed_file(filename):
-    return '.' in filename and \
-           filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
-
-def cleanup_temp_files(file_path):
-    """Ensure temporary files are deleted after processing"""
-    try:
-        if os.path.exists(file_path):
-            os.remove(file_path)
-    except Exception as e:
-        print(f"Error cleaning up temp file {file_path}: {str(e)}")
-
-@app.route("/health", methods=["GET"])
-def health_check():
-    """Endpoint to check if API is running"""
-    return jsonify({
-        'status': 'API is running',
-        'timestamp': datetime.datetime.now().isoformat(),
-        'device': device,
-        'compute_type': compute_type,
-        'active_requests': active_requests,
-        'max_duration_supported': MAX_AUDIO_DURATION
-    })
-
-@app.route("/status/busy", methods=["GET"])
-def server_busy():
-    """Endpoint to check if server is busy"""
-    is_busy = active_requests >= MAX_CONCURRENT_REQUESTS
-    return jsonify({
-        'is_busy': is_busy,
-        'active_requests': active_requests,
-        'max_capacity': MAX_CONCURRENT_REQUESTS
-    })
-
-@app.route("/whisper_transcribe", methods=["POST"])
-def whisper_transcribe():
-    global active_requests
-    
-    if not request_semaphore.acquire(blocking=False):
-        return jsonify({'error': 'Server busy'}), 503
-    
-    active_requests += 1
-    start_time = time.time()
-    temp_file_path = None
-    
-    try:
-        if 'audio' not in request.files:
-            return jsonify({'error': 'No file provided'}), 400
-            
-        audio_file = request.files['audio']
-        if not (audio_file and allowed_file(audio_file.filename)):
-            return jsonify({'error': 'Invalid file format'}), 400
-
-        temp_file_path = os.path.join(TEMPORARY_FOLDER, secure_filename(audio_file.filename))
-        audio_file.save(temp_file_path)
-        
-        segments, _ = wmodel.transcribe(
-            temp_file_path,
-            beam_size=beamsize,
-            vad_filter=True,
-            without_timestamps=True,  # Ensure timestamps are not included
-            compression_ratio_threshold=2.4,
-            word_timestamps=False
-        )
-        
-        full_text = " ".join(segment.text for segment in segments)
-        return jsonify({'transcription': full_text}), 200
-
-        
-        
-    except Exception as e:
-        return jsonify({'error': str(e)}), 500
-        
-    finally:
-        if temp_file_path:
-            cleanup_temp_files(temp_file_path)
-        active_requests -= 1
-        request_semaphore.release()
-        print(f"Processed in {time.time()-start_time:.2f}s (Active: {active_requests})")
-
-if __name__ == "__main__":
-    # Create temporary folder if it doesn't exist
-    if not os.path.exists(TEMPORARY_FOLDER):
-        os.makedirs(TEMPORARY_FOLDER)
-    
+from flask import Flask, request, jsonify, Response
+from faster_whisper import WhisperModel
+import torch
+import io
+import time
+import datetime
+from threading import Semaphore
+import os
+from werkzeug.utils import secure_filename
+import tempfile
+from moviepy.editor import VideoFileClip  # Added for video processing
+
+app = Flask(__name__)
+
+# Configuration
+MAX_CONCURRENT_REQUESTS = 2  # Adjust based on server capacity
+MAX_FILE_DURATION = 60 * 30  # 30 minutes maximum duration (adjust as needed)
+TEMPORARY_FOLDER = tempfile.gettempdir()
+ALLOWED_AUDIO_EXTENSIONS = {'mp3', 'wav', 'ogg', 'm4a', 'flac', 'aac', 'wma', 'opus', 'aiff'}
+ALLOWED_VIDEO_EXTENSIONS = {'mp4', 'avi', 'mov', 'mkv', 'webm', 'flv', 'wmv', 'mpeg', 'mpg', '3gp'}
+ALLOWED_EXTENSIONS = ALLOWED_AUDIO_EXTENSIONS.union(ALLOWED_VIDEO_EXTENSIONS)
+
+# Device check for faster-whisper
+device = "cuda" if torch.cuda.is_available() else "cpu"
+compute_type = "float16" if device == "cuda" else "int8"
+print(f"Using device: {device} with compute_type: {compute_type}")
+
+# Faster Whisper setup with optimized parameters for long audio
+beamsize = 2
+wmodel = WhisperModel(
+    "guillaumekln/faster-whisper-small",
+    device=device,
+    compute_type=compute_type,
+    download_root="./model_cache"
+)
+
+# Concurrency control
+request_semaphore = Semaphore(MAX_CONCURRENT_REQUESTS)
+active_requests = 0
+
+def allowed_file(filename):
+    return '.' in filename and \
+           filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
+
+def cleanup_temp_files(*file_paths):
+    """Ensure temporary files are deleted after processing"""
+    for file_path in file_paths:
+        try:
+            if file_path and os.path.exists(file_path):
+                os.remove(file_path)
+        except Exception as e:
+            print(f"Error cleaning up temp file {file_path}: {str(e)}")
+
+def extract_audio_from_video(video_path, output_audio_path):
+    """Extract audio from a video file and save it as a temporary audio file"""
+    try:
+        video = VideoFileClip(video_path)
+        if video.duration > MAX_FILE_DURATION:
+            video.close()
+            raise ValueError(f"Video duration exceeds {MAX_FILE_DURATION} seconds")
+        video.audio.write_audiofile(output_audio_path)
+        video.close()
+        return output_audio_path
+    except Exception as e:
+        raise Exception(f"Failed to extract audio from video: {str(e)}")
+
+@app.route("/health", methods=["GET"])
+def health_check():
+    """Endpoint to check if API is running"""
+    return jsonify({
+        'status': 'API is running',
+        'timestamp': datetime.datetime.now().isoformat(),
+        'device': device,
+        'compute_type': compute_type,
+        'active_requests': active_requests,
+        'max_duration_supported': MAX_FILE_DURATION,
+        'supported_formats': list(ALLOWED_EXTENSIONS)
+    })
+
+@app.route("/status/busy", methods=["GET"])
+def server_busy():
+    """Endpoint to check if server is busy"""
+    is_busy = active_requests >= MAX_CONCURRENT_REQUESTS
+    return jsonify({
+        'is_busy': is_busy,
+        'active_requests': active_requests,
+        'max_capacity': MAX_CONCURRENT_REQUESTS
+    })
+
+@app.route("/whisper_transcribe", methods=["POST"])
+def transcribe():
+    global active_requests
+    
+    if not request_semaphore.acquire(blocking=False):
+        return jsonify({'error': 'Server busy'}), 503
+    
+    active_requests += 1
+    start_time = time.time()
+    temp_file_path = None
+    temp_audio_path = None
+    
+    try:
+        if 'file' not in request.files:
+            return jsonify({'error': 'No file provided'}), 400
+            
+        file = request.files['file']
+        if not (file and allowed_file(file.filename)):
+            return jsonify({'error': f'Invalid file format. Supported: {", ".join(ALLOWED_EXTENSIONS)}'}), 400
+
+        # Save uploaded file to temporary location
+        temp_file_path = os.path.join(TEMPORARY_FOLDER, secure_filename(file.filename))
+        file.save(temp_file_path)
+        
+        # Check if file is a video and extract audio if necessary
+        file_extension = file.filename.rsplit('.', 1)[1].lower()
+        if file_extension in ALLOWED_VIDEO_EXTENSIONS:
+            temp_audio_path = os.path.join(TEMPORARY_FOLDER, f"temp_audio_{int(time.time())}.wav")
+            extract_audio_from_video(temp_file_path, temp_audio_path)
+            transcription_file = temp_audio_path
+        else:
+            transcription_file = temp_file_path
+        
+        # Transcribe the audio file
+        segments, _ = wmodel.transcribe(
+            transcription_file,
+            beam_size=beamsize,
+            vad_filter=True,
+            without_timestamps=True,
+            compression_ratio_threshold=2.4,
+            word_timestamps=False
+        )
+        
+        full_text = " ".join(segment.text for segment in segments)
+        return jsonify({
+            'transcription': full_text,
+            'file_type': 'video' if file_extension in ALLOWED_VIDEO_EXTENSIONS else 'audio'
+        }), 200
+        
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+        
+    finally:
+        cleanup_temp_files(temp_file_path, temp_audio_path)
+        active_requests -= 1
+        request_semaphore.release()
+        print(f"Processed in {time.time()-start_time:.2f}s (Active: {active_requests})")
+
+if __name__ == "__main__":
+    # Create temporary folder if it doesn't exist
+    if not os.path.exists(TEMPORARY_FOLDER):
+        os.makedirs(TEMPORARY_FOLDER)
+    
     app.run(host="0.0.0.0", port=7860, threaded=True)