S1056 - Doodstream <Top 20 Popular>

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

@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) S1056 - DoodStream

app = Flask(__name__)

# Example in-memory video features video_features = np.array([ [1, 2, 3], [4, 5, 6], [7, 8, 9] ]) nbrs = NearestNeighbors(n_neighbors=3

# Return recommended video IDs return jsonify(indices[0].tolist()) S1056 - DoodStream