8000 GitHub - SaraSaadoun/Travelita: AI-powered travel assistant designed to simplify trip planning by generating personalized itineraries, enabling interactive Q&A, allowing dynamic adjustments, and identifying landmarks from images with real-time mapping.
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AI-powered travel assistant designed to simplify trip planning by generating personalized itineraries, enabling interactive Q&A, allowing dynamic adjustments, and identifying landmarks from images with real-time mapping.

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🌍 Travelita – AI-Powered Travel Assistant ✈️

πŸ“Œ About the Project

Travelita is an AI-powered travel assistant designed to simplify trip planning by generating personalized itineraries, enabling interactive Q&A, allowing dynamic adjustments, and identifying landmarks from images with real-time mapping.

LinkedIn Post & Demo: View here

πŸš€ Features

  • Personalized Itineraries – Tailored travel plans based on user preferences.
  • Q&A with Your Plan – Ask questions and get real-time insights.
  • Dynamic Adjustments – Modify plans instantly with AI-powered optimization.
  • Landmark Recognition – Id 8000 entify landmarks from images and get location details.
  • Email Integration – Send plans via email effortlessly.

Feature 1: Travel Plan Generator #1

Travel Plan Generator #1

Feature 1: Travel Plan Generator #2

Travel Plan Generator #2

Feature 2: Customization of your Travel Plan

Customization of your Travel Plan

Feature 3: QnA with your Travel Plan

QnA with your Travel Plan

Feature 4: Landmark Detection #1

Landmark Detection #1

Feature 4: Landmark Detection #2

Landmark Detection #2

Feature 5: Chat with your Landmark

Chat with your Landmark

πŸ—οΈ Tech Stack

πŸ”Ή Agentic System

  • Crew AI & Phidata – For structured agentic workflows.

πŸ”Ή Language Models

  • Google Gemini Pro & Llama-3.3-70b – Powering intelligent trip customization.

πŸ”Ή Retrieval-Augmented Generation (RAG)

  • FAISS & Sentence Transformers – For advanced Q&A and travel insights.

πŸ”Ή Computer Vision & Landmark Recognition

  • Google Landmark Detection Model – Recognizing landmarks from images.
  • TensorFlow Hub & PIL – For image classification and processing.
  • Geopy & Google Maps API – Fetching real-world locations and coordinates.

πŸ”Ή Frontend & Deployment

  • Streamlit – Interactive user interface.
  • Google Calendar API – Seamlessly syncing travel plans.

πŸ› οΈ Setup & Installation

  1. Clone this repository:

    git clone https://github.com/your-repo/travelita.git
    cd travelita
  2. Create venv:

    conda create -n travelita python=3.11 -y
  3. Activate venv:

     conda activate travelita
  4. Install Requirements:

    pip install -r requirements.txt
  5. Run Streamlit App:

    streamlit run app.py

πŸŽ“ Team Members

  • Sara Hamza
  • Mariam Ashraf
  • Esraa Mohamed
  • Habiba Ahmed
  • Alaa Hussein
  • Amira Ahmed

πŸ™Œ Acknowledgments

Thank you to Dr. Mohamed Zorkany for his mentorship and guidance throughout this training.

πŸ’‘ Contributions & Feedback

We’d love to hear your thoughts! Feel free to open issues, submit PRs, or reach out.

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AI-powered travel assistant designed to simplify trip planning by generating personalized itineraries, enabling interactive Q&A, allowing dynamic adjustments, and identifying landmarks from images with real-time mapping.

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