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[Completed] SDS CP #22 - AI Travel Companion

Overview

This project involves creating an advanced AI-powered travel companion that leverages retrieval-augmented generation (RAG) to provide personalized travel assistance. The project will gather the latest ticket price data from airlines through web scraping, integrate this data with a knowledge base, and deploy the final application on Hugging Face Spaces. The AI Travel Companion will offer users dynamic ticket pricing, travel recommendations, and query-based assistance.

Objectives

Data Collection and Storage:

  • Gather data on popular travel destinations via web scraping.

  • Store the data in a structured database optimized for quick retrieval.

AI Travel Companion Development:

  • Develop a RAG pipeline that combines a travel destinations knowledge base with generative AI.

  • Implement functionality to answer user queries and provide personalized travel suggestions based on travel data and other contextual inputs.

Application Deployment:

  • Build an intuitive user interface for the travel companion.

  • Deploy the application on Hugging Face Spaces for global accessibility.


Scope of Works:

Phase 1: Setup (1 Week)

  • Setup of GitHub repo and project folders

  • Setup of virtual environments and installation of libraries

Phase 2: Application Logic Development (2 Weeks)

  • Choose the LLM you want to use (Either a frontier model or a model from huggingface)

  • Integrate it with Tavily to enhance user queries with real-time data

  • Model output should be a complete itinerary for the users travel destinations

Phase 3: Application UI Development (1 Week)

  • Build a web UI to interact with the model (Streamlit, Gradio, etc.)

Phase 4: Deployment (1 Week)

  • Deploy application to the cloud (Streamlit, Gradio, etc.)


Link to GitHub: https://github.com/SuperDataScience-Community-Projects/SDS-CP022-ai-travel-companion

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