🌍 Autogen Travel Concierge

A sophisticated AI travel planning assistant showcasing AutoGen's advanced memory capabilities with dual-layer memory architecture: Redis-backed chat history and Mem0 based long term memory that remembers user preferences.

🧠 What's included?

🎯 Dual-Layer Memory: Short-term chat history (Redis) + Long-term learning (Mem0+Redis)
👥 User Isolation: Pre-seeded users get completely separate memory contexts
🔄 Session Persistence: Your conversations and preferences survive app restarts
📚 Intelligent Learning: The agent learns your travel preferences automatically
🌐 Real-time Search: Live travel information via Tavily search API
💬 Clean Chat UI: Gradio interface with user management
📅 Calendar Export (ICS): Generate a calendar file for your itinerary and open it directly in your default calendar app

🚀 Quick Setup (<5 minutes)

Step 1: Get Your API Keys

You'll need three API keys:

OpenAI API Key: Get from platform.openai.com
Tavily API Key: Get from tavily.com (free tier available)
Redis URL: See step two

Step 2: Set Up Redis

You have 3 options for Redis:

Option A: Local Redis with Docker**

docker run --name redis -p 6379:6379 -d redis:8.0.3

Option B: Redis Cloud

Get a free db here.

Option C: Azure Managed Redis

Here's a quickstart guide to create Azure Managed Redis for as low as $12 monthly: https://learn.microsoft.com/en-us/azure/redis/quickstart-create-managed-redis

Step 3: Setup the Project

# Install uv (Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone and install
git clone <repository-url>
cd amr-autogen-travel-agent

# Get uv env setup
uv sync

Step 4: Configure Your Environment

Create a .env file with your API keys:

cp env.example .env

Edit the .env file as needed.

Step 5: Launch the Application

uv run python gradio_app.py

🎉 Open http://localhost:7860 to start chatting!

The application will:

✅ Validate your configuration and API connections
✅ Initialize the dual-layer memory system
✅ Load the user management interface
✅ Enable calendar export/open from finalized itineraries

👤 User Profile Configuration

The demo comes with pre-configured user profiles (Tyler, Purna, and Jan) that have distinct travel preferences. You can easily customize these or add new profiles by editing context/seed.json.

🚀 Ready to see AI memory in action? Start chatting and watch your travel preferences get smarter!

redis-developer/amr-autogen-travel-agent