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