TrailBuddy: less scrolling, more fresh air

说明与用途

TrailBuddy 通过使用本地 Qwen 2.5 3B 模型，提供三条基于用户输入的户外活动建议，简化了选择过程。

问题

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

结果

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

工作流

• 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.

证据

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.

来源

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.

来源

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

来源

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.

来源