app = Flask(__name__)

@app.route('/recommend', methods=['GET']) def recommend(): # Assume user provides a video ID and we fetch its features video_id = 0 # Example video ID query_features = video_features[video_id].reshape(1, -1)

# Return recommended video IDs return jsonify(indices[0].tolist())

nbrs = NearestNeighbors(n_neighbors=3, algorithm='brute', metric='euclidean').fit(video_features) distances, indices = nbrs.kneighbors(query_features)