Update app.py

app.py

@@ -20,6 +20,7 @@ from wordcloud import WordCloud
 from heapq import nlargest
 from werkzeug.utils import secure_filename
 from spacy.lang.en.stop_words import STOP_WORDS
+import huggingface_hub as hf_hub
 
 # Change the directory to the backend folder
 # os.chdir("E:/Centennial/SEMESTER 6/Software Development Project/backend/")
@@ -58,34 +59,89 @@ def upload_video():
     start_time = time.time()
     if 'video' not in request.files:
         return jsonify({'error': 'No video file found in the request'})
+
     video = request.files['video']
+    if video.filename == '':
+        return jsonify({'error': 'No selected video file'})
+
     if video.mimetype.split('/')[0] != 'video':
         return jsonify({'error': 'The file uploaded is not a video'})
 
     model_name = request.form.get('modelName')
     print("MODEL:", model_name)
 
-    # backend_folder = 'backend_videos'
-    # if not os.path.exists(backend_folder):
-    #     os.makedirs(backend_folder)
-    video_path = os.path.join(os.getcwd(), secure_filename(video.filename))
-    video.save(video_path)
-
-    transcript = transcribe_audio(video_path)
-
-    summary = ""
-    if model_name == 'T5':
-        summary = summarize_text_t5(transcript)
-    elif model_name == 'BART':
-        summary = summarize_text_bart(transcript)
-    else:
-        summary = summarizer(transcript)
-
-    end_time = time.time()
-    elapsed_time = end_time - start_time
-    print(f"Video saved successfully. Time taken: {elapsed_time} seconds")
-
-    return jsonify({'message': 'successful', 'transcript': transcript, 'summary': summary, 'modelName': model_name})
+    try:
+        # Save the uploaded video to a temporary directory
+        video_path = os.path.join(os.getcwd(), 'temp', secure_filename(video.filename))
+        video.save(video_path)
+
+        # Save the video file to Hugging Face Spaces
+        video_file_id = hf_hub.upload(video_path, name=video.filename)
+
+        # Transcribe audio from the uploaded video
+        transcript = transcribe_audio(video_path)
+
+        # Save the transcribed audio to a temporary WAV file
+        audio_path = os.path.join(os.getcwd(), 'temp', 'transcribed_audio.wav')
+        with open(audio_path, 'w') as audio_file:
+            audio_file.write(transcript)
+
+        # Save the audio file to Hugging Face Spaces
+        audio_file_id = hf_hub.upload(audio_path, name='transcribed_audio.wav')
+
+        # Summarize the transcribed text using the selected model
+        summary = ""
+        if model_name == 'T5':
+            summary = summarize_text_t5(transcript)
+        elif model_name == 'BART':
+            summary = summarize_text_bart(transcript)
+        else:
+            summary = summarizer(transcript)
+
+        # Calculate the elapsed time and print a success message
+        end_time = time.time()
+        elapsed_time = end_time - start_time
+        print(f"Video saved successfully. Time taken: {elapsed_time} seconds")
+
+        # Return the transcript, summary, model name, video file ID, and audio file ID in the response
+        return jsonify({'message': 'successful', 'transcript': transcript, 'summary': summary, 'modelName': model_name,
+                        'videoFileId': video_file_id, 'audioFileId': audio_file_id})
+    except Exception as e:
+        # If an error occurs during processing, return an error message
+        return jsonify({'error': str(e)})
+        
+# def upload_video():
+#     start_time = time.time()
+#     if 'video' not in request.files:
+#         return jsonify({'error': 'No video file found in the request'})
+#     video = request.files['video']
+#     if video.mimetype.split('/')[0] != 'video':
+#         return jsonify({'error': 'The file uploaded is not a video'})
+
+#     model_name = request.form.get('modelName')
+#     print("MODEL:", model_name)
+
+#     # backend_folder = 'backend_videos'
+#     # if not os.path.exists(backend_folder):
+#     #     os.makedirs(backend_folder)
+#     video_path = os.path.join(os.getcwd(), secure_filename(video.filename))
+#     video.save(video_path)
+
+#     transcript = transcribe_audio(video_path)
+
+#     summary = ""
+#     if model_name == 'T5':
+#         summary = summarize_text_t5(transcript)
+#     elif model_name == 'BART':
+#         summary = summarize_text_bart(transcript)
+#     else:
+#         summary = summarizer(transcript)
+
+#     end_time = time.time()
+#     elapsed_time = end_time - start_time
+#     print(f"Video saved successfully. Time taken: {elapsed_time} seconds")
+
+#     return jsonify({'message': 'successful', 'transcript': transcript, 'summary': summary, 'modelName': model_name})
 
 # Route for uploading YouTube video links
 @app.route('/youtube_upload_video', methods=['POST'])