# Sample video data videos = [ {"id": 1, "title": "Video 1", "resolution": "720p"}, {"id": 2, "title": "Video 2", "resolution": "1080p"}, {"id": 3, "title": "Video 3", "resolution": "720p"} ]
This feature aims to improve the user experience by providing a more efficient and personalized way to discover videos. BigTitsRoundAsses 25 01 18 Red Eviee XXX 720p M...
"Enhanced Video Discovery"
@app.route("/recommend", methods=["GET"]) def recommend(): user_id = request.args.get("user_id") user = next((u for u in users if u["id"] == user_id), None) if user: viewing_history = user["viewing_history"] # Use the recommendation system to suggest videos distances, indices = nn.fit_transform(viewing_history) recommended_videos = [videos[i] for i in indices[0]] return jsonify(recommended_videos) return jsonify([]) # Sample video data videos = [ {"id":
# AI-powered recommendation system nn = NearestNeighbors(n_neighbors=3) "title": "Video 1"
app = Flask(__name__)
