This is a submission for the Google x Kaggle 5-Day Generative AI Event.
Our project demonstrates how to build an interactive airline assistant using Generative AI techniques including:
- RAG (Retrieval-Augmented Generation) for FAQ responses
- Embeddings-based similarity using
text-embedding-004 - Gemini 2.0 Flash for intent classification and smart field extraction
- Multi-turn interaction logic with running state
- A clean Gradio chat interface
The assistant interacts with users just like a real airline support agent:
- 🧠 Understands your input using AI-based classification
- 📘 Answers travel questions (e.g., "Can I bring a cat on the plane?")
- 🗃️ Differentiates between FAQ and personal information
- 📝 Collects key fields: name, flight number, issue, and email
- 🧠 Stores information across turns using a persistent user state
To run this notebook, you must add your Google Generative AI API key:
- Go to "Add-ons" > "Secrets" (in Kaggle)
- Add a new secret named:
GOOGLE_API_KEY
- Paste your Gemini API key as the value (from https://makersuite.google.com/app/apikey)
| Component | Description |
|---|---|
text-embedding-004 |
Generates vector embeddings for FAQ retrieval |
cosine similarity |
Finds the best-matching FAQ question |
Gemini Flash |
Classifies whether the user input is a question or a personal detail |
Field extraction |
AI-based slot-filling logic (e.g., extracting names from messy input) |
State tracking |
Stores each user field (name, flight, issue, email) during chat |
Gradio |
Provides an interactive chatbot interface for users |
This project simulates how a real-world AI-powered airline assistant might behave — blending FAQ search with intelligent form-filling, all within a lightweight notebook.
It showcases how we can combine LLMs, embeddings, and interface tools to build useful, responsive GenAI apps.
notebook.ipynb– full interactive assistantassets– demo pictures
Huge thanks to Kaggle, Google, and the GenAI team for organizing the event!