TrailBuddy: less scrolling, more fresh air

Описание и применение

TrailBuddy упрощает выбор активностей на свежем воздухе, предлагая три идеи, ориентированные на доступное время и предпочтения пользователя, используя локальную модель Qwen 2.5 3B через Ollama.

Задача

Deciding what to do when you have a free hour and want to get outside can take longer than the walk itself.

Результат

TrailBuddy streamlines the decision process for quick outdoor outings by providing concise, AI-generated activity suggestions without requiring internet connectivity after initial setup.

Рабочий процесс

• 1. User opens TrailBuddy web app.
• 2. User enters starting area, available time, and activity preference.
• 3. App sends request to local Ollama instance running Qwen 2.5 3B.
• 4. Ollama generates three activity ideas, rough duration, and one item to bring.
• 5. App displays the suggestions to the user.
• 6. User selects an idea and closes the tab, ready to go out.

Доказательства

I made TrailBuddy. You put in a starting area, how much time you have, and what you feel like doing. It gives you three ideas, a rough duration, and one thing to bring.

Источник

TrailBuddy is set up to use Qwen 2.5 3B through Ollama on your own machine. With the model downloaded and Ollama running, your request goes to the local Ollama endpoint rather than a hosted AI API.

Источник

If Ollama isn't running, TrailBuddy falls back to a few built-in ideas and labels them as offline — those aren't AI-generated.

Источник

I built the app with FastAPI and plain HTML, CSS, and JavaScript. It doesn't fetch maps, weather, or trail conditions, so the suggestions are ideas, not verified local recommendations.

Источник