Wanderlust is an AI-powered travel itinerary generator that helps users plan their trips effortlessly by asking a series of questions and generating personalized travel recommendations. It uses LangChain, Groq's Llama3-8B-8192 model, and TavilySearch to create highly customized itineraries based on user preferences.

Check out the live version on Hugging Face Spaces: 👉 Wanderlust - AI-Powered Travel Itinerary Generator

• ✅ Interactive Chat Interface: Guided conversation to gather user preferences.
• 🔍 Smart Search Integration: Fetches top recommendations for destinations using TavilySearch.
• 🤖 AI-Powered Itinerary Generation: Generates a detailed multi-day itinerary based on preferences and search results.
• 🔄 Restart Option: Easily start over and plan a new trip.
• 🛠️ Seamless Gradio Interface: User-friendly chatbot interface built using Gradio.

git clone https://github.com/SHASWATSINGH3101/Wanderlust.git
cd wanderlust

# Create a virtual environment
python -m venv wanderlust-env

# Activate the virtual environment
# For Windows
wanderlust-env\Scripts\activate

# For macOS/Linux
source wanderlust-env/bin/activate

pip install -r requirements.txt

Create a .env file in the root directory and add the following:

TAVILY_API_KEY=your_tavily_api_key
GROQ_API_KEY=your_groq_api_key

👉 API Key Setup:

• Get your Tavily API Key
• Get your Groq API Key

python wanderlust.py

Visit the link provided in your terminal, usually:

http://127.0.0.1:7860

Bot: Hello! Ready to plan your next trip? Type 'START' to begin.
User: START
Bot: Great! Where would you like to go?
User: Paris, France
and so on....
...

• Utilizes llama3-8b-8192 from Groq to generate the final itinerary.
• Processes user preferences and search results to craft detailed recommendations.

• Searches for top-rated activities and recommendations.
• Helps provide relevant suggestions for the itinerary.

• Stores user responses and progress in a Python dictionary.
• Tracks the conversation flow and resets after completion.

📁 wanderlust
├── 📄 wanderlust.py          # Main script with Gradio interface and logic
├── 📄 requirements.txt       # Dependencies
├── 📄 .env                   # API keys for Groq and Tavily (ignored in Git)
└── 📂 asset
    └── 📄 logo.png           # Logo image

• gradio
• langchain_groq
• langchain_tavily
• python-dotenv

Install them using:

pip install gradio langchain_groq langchain_tavily python-dotenv

• LLM: Llama3-8B-8192 (Groq API)
• Search API: Tavily API for fetching relevant travel data

• Make sure to correctly set API keys in the .env file.
• Check the console for any errors while running the application.

• Python 3.8+
• Compatible with Windows, macOS, and Linux

# Deactivate the virtual environment after usage
# For Windows/macOS/Linux
deactivate

This project is licensed under the MIT License - see the LICENSE file for details.

Pull requests are welcome! Please check out the CONTRIBUTING.md before making any changes.

For any inquiries, reach out to:

• GitHub: SHASWATSINGH3101

Happy Traveling! ✈️🌟