The AI-Driven Itinerary Planner revolutionizes the travel planning experience by integrating advanced AI technologies to generate personalized and adaptive travel itineraries. This system leverages a Large Language Model (LLM), Retrieval-Augmented Generation (RAG), and real-time web scraping, dynamically adjusting itineraries based on real-time data such as pricing and available attractions.
- Personalized Itineraries: Generates travel plans that are tailored to user preferences and budget, enhancing the travel experience significantly.
- Dynamic Adaptation: Continuously updates travel plans based on real-time changes in pricing and availability.
- Efficiency: Reduces the itinerary planning time by over 95%, streamlining the process to under an hour.
- User Satisfaction: Provides budget-conscious recommendations, significantly increasing user satisfaction.
- LLM (Llama2-7b): Understands and generates language-based responses tailored to user inputs.
- Retrieval-Augmented Generation (RAG): Enhances the itinerary suggestions with real-time, contextually relevant data from Chroma DB.
- Web Scraping: Utilizes BeautifulSoup to fetch real-time updates on travel-related information such as hotel prices and availability.
This project integrates various components including a chatbot interface for interaction, a backend leveraging Llama2-7b for processing and generating itineraries, and a web scraping module to fetch the latest data required for updating the travel plans.
To set up this project locally:
- Clone the repository:
git clone https://github.com/VaradhKaushik/travel-planner.git
- Install dependencies:
pip install -r requirements.txt
- Run the application:
python app.py
Interact with the chatbot by specifying your travel preferences such as destination, duration, budget, and interests. The system will generate a personalized travel plan that adapts in real-time based on available data.
Contributions are welcome! For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the MIT License - see the LICENSE.md file for details.
- Northeastern University for providing the academic environment to develop this project.
- Co-contributor Alexander Seljuk for significant contributions to the web scraping module.
- All open-source software and APIs utilized in this project.
- Varadh Kaushik - [email protected]
- LinkedIn - https://www.linkedin.com/in/varadh-kaushik/
- Project Link: https://github.com/VaradhKaushik/travel-planner