PackPal - Local AI Travel Companion

Ansh Meshram — Mon, 05 Oct 2026 07:02:17 +0000

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

PackPal is a local-AI travel companion built for a friend who wanted a simpler way to organize trips with friends. It combines personalized packing lists, weather/activity-aware recommendations, smart luggage optimization, itineraries, travelers, and group expense splitting in one place.

PackPal uses Gemma 2 through Ollama for local AI reasoning, while deterministic TypeScript handles calculations such as luggage weights and expense settlements.

Demo

🚀 Live Demo: https://pack-pal-tau.vercel.app/

Code

💻 GitHub: https://github.com/AnshMeshram/PackPal

How I Built It

PackPal is built with Next.js, React, TypeScript, Tailwind CSS, MongoDB Atlas, SerpApi, Ollama, and Gemma 2.

Gemma 2 is at the core of the application and handles:

🎒 Personalized packing recommendations
🧳 Luggage optimization
🏃 Activity-to-packing reasoning
🔄 Natural-language trip changes
💸 Natural-language expense extraction
🗺️ Destination interpretation

The architecture separates AI reasoning from deterministic application logic:

Gemma understands and recommends → TypeScript validates and calculates.

For example, Gemma extracts information from:

"Rahul paid ₹1,800 for dinner for everyone."

Then PackPal's deterministic expense engine calculates the actual balances and settlements.

SerpApi provides live travel/search context, MongoDB Atlas provides persistence, ElevenLabs enables optional voice output, and Sentry provides monitoring.

Why Does Open Innovation Matter?

PackPal was intentionally built around open-weight AI and local inference.

Running Gemma 2 through Ollama means the core AI can run locally instead of requiring every request to be sent to a closed AI API.

This provides:

🔐 Greater privacy for personal trip information
💰 Lower recurring AI inference costs
📴 Potential for offline/local usage
🔄 Freedom to swap or upgrade models
🛠️ More control over how the AI behaves

For a personal travel assistant, keeping sensitive trip and group information under the user's control is especially valuable.

My Agent Session

DevRelay agent session: https://dev.to/agent_sessions/packpal-privacy-first-ai-travel-journal-packing-companion-430lto

Prize Categories

🏆 Best Use of Gemma — Gemma 2 is the core AI model powering PackPal.
🔎 Best Use of SerpApi — Provides live search and destination context.
🗄️ Best Use of MongoDB Atlas — Persistent application data layer.
🎙️ Best Use of ElevenLabs — Optional voice generation.
🛡️ Best Use of Sentry Agent Tracing — Monitoring and debugging.

devchallenge #weekendchallenge #hf26challenge

DEV Community: Ansh Meshram