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Build an AI Travel Assistant With Google Agent Development Kit (ADK)
Mar 06, 2026 6 Min Read 56 Views
(Last Updated)
Planning a trip can be exciting, but it can also involve a lot of research. People usually spend hours to search the best places to visit and compare hotels, read reviews, and how they will spend their time. This however very easy to get lost in browsing through various travel sites.
But now think of having an AI assistant that can plan your trip in seconds.
With modern AI agent frameworks, developers can build intelligent assistants that analyze travel requests and generate personalized recommendations. These assistants are capable of suggesting destinations to visit, hotels to stay in and even activities depending on the preferences of the user.
Here in this blog, you will get to know how to Build an AI Travel Assistant With Google Agent Development Kit (ADK). We will explore how AI agents work, how to create tools and agents, and how to run your travel assistant step by step.
Quick answer:
To Build an AI Travel Assistant With Google Agent Development Kit, developers create an AI agent that understands travel queries, connects to travel APIs, and generates personalized trip plans. Using tools like Python, ADK, and language models, the assistant can recommend destinations, estimate travel costs, and generate itineraries automatically.
Table of contents
- What is Google Agent Development Kit (ADK)?
- Key Features of an AI Travel Assistant
- Destination Recommendation
- Travel Itinerary Generation
- Hotel and Accommodation Recommendations
- Budget Estimation
- Real Time Travel information
- How AI Agents Work
- Interpretation of the User Query
- Planning the Solution
- Using Tools to Fetch Data
- Generating the Response
- Setting Up the Environment
- Install Google ADK
- Creating the Project Structure
- Creating an AI Agent
- Designing Tools of the AI Travel Assistant
- Tool 1: Fetch Location Co-ordinates.
- Tool 2: Find Hotels Near a Location
- Tool 3: Find Activity Locations
- Creating Specialized AI Agents
- Hotel Expert Agent
- Activities Expert Agent
- Places-to-Visit Expert Agent
- Travel Assistant Agent (Main Agent)
- Running the AI Travel Assistant
- Run the Web Interface
- Run the Command Line Interface
- Wrapping it up:
- FAQs
- What is Google ADK?
- What is an AI travel assistant?
- Do I need advanced AI knowledge to build this?
What is Google Agent Development Kit (ADK)?
Google Agent Development Kit (ADK) is a framework that is created to assist developers in building intelligent AI agents that can communicate with users, tools, and external sources of data.
Instead of writing complex AI systems from scratch, ADK provides a structured environment where developers can create agents capable of reasoning, planning, and performing tasks automatically.
An AI agent created based on ADK is capable of:
- Understand user queries using natural language processing
- Perform tasks such as searching APIs or retrieving information
- Decide according to the requests of the user.
- Combine multiple tools to complete complex workflows
- Produce human-like responses .
For example, when you Build an AI Travel Assistant With Google Agent Development Kit, the agent can analyze a user’s travel request and automatically perform multiple tasks such as finding destinations, suggesting hotels, and generating an itinerary.
This makes ADK an effective platform in the creation of smart assistants.
Key Features of an AI Travel Assistant
AI travel assistants are becoming increasingly popular because they simplify travel planning.
Here are some important capabilities your assistant can include.
Destination Recommendation
The AI assistant can recommend destinations depending on:
- Budget
- Travel dates
- User interests
- Weather conditions
Travel Itinerary Generation
Itinerary planning is one of the most helpful features in case you Build an AI Travel Assistant With Google Agent Development Kit.
The assistant can automatically create plan of the day-by-day traveling including:
- Attractions
- Activities
- Restaurants
- Employee transportation recommendations
Hotel and Accommodation Recommendations
The AI agent is also able to suggest a hotel or hostel on the basis of the preferences of the user.
It can filter results using:
- Price range
- Location
- Ratings
- Amenities
Budget Estimation
Travelers often want to know how much a trip might cost.
The AI assistant will be able to provide an approximation of travel budgets based on:
- Flight prices
- Accommodation costs
- Local transportation
- Activities
Real Time Travel information
An advanced assistant can also provide useful information such as:
- Weather forecasts
- Visa requirements
- Currency exchange rates
- Local safety tips
How AI Agents Work
Before learning how to Build an AI Travel Assistant With Google Agent Development Kit, it is helpful to understand how AI agents operate.
AI agents typically follow a sequence of steps when responding to a request.
1. Interpretation of the User Query
The initial one is to understand the query of the user. Large language models are applied by AI agents to understand natural language queries and determine the intention of the user.
Example, when a user requests services such as hotels in Tokyo within reach of tourist attraction sites, then the AI agent understands that the user wants hotel details of places within proximity of a tourist attraction site.
2. Planning the Solution
Once the AI agent has learned about the request, it knows what it should do. It can choose to get location information, find hotel listings or get information on local attractions.
3. Using Tools to Fetch Data
AI agents tend to use third-party tools to gather information. These tools are able to communicate with APIs, databases or outside services to get the real world data.
For example, the agent can find the location coordinates of a place or the name of the nearest hotels using the Google Maps API.
4. Generating the Response
After the AI agent has collected all the information needed, it comes up with a structured response for the user. The answer can be in the form of hotel suggestions, activity suggestions, and traveling advisory.
This only takes a few seconds and this makes the travelling planning process to be much faster.
Setting Up the Environment
You should install necessary tools and libraries in order to Build an AI Travel Assistant With Google Agent Development Kit.
Install Google ADK
Before building the travel assistant, you need to install the Google ADK library.
Run the following command in your terminal:
| pip install google-adk |
This will download and install the ADK framework allowing you to start creating AI agents in Python.
Creating the Project Structure
A well-organised structure should be followed in all the AI projects. The Google ADK applications are generally of a simple directory structure.
| ai_travel_planner │ ├── agent.py ├── .env └── __init__.py |
Each files are significant to the project.
- .env file : The environment variables include API keys that are needed to access outside services and are stored in the .env file. Having sensitive data in this file means that you are not hard coded in your main program.
- init.py file : The file allows Python to consider the directory as a module. It is also capable of importing and accessing easily the agent definitions by various components of the project.
- agent.py file : This is the primary file in which we specify the tools and the AI agents employed in the travel assistant. The majority of the application logic is implemented here.
Creating an AI Agent
In Google ADK, AI agents can be created using the Agent() or LlmAgent() classes.
These functions determine the way the AI agent acts and what the tool it can use is.
Below is a simple example of creating an AI agent.
| from google.adk.agents import Agent travel_agent = Agent( name=”travel_assistant”, model=”gemini-2.0-flash”, description=”AI agent that helps users plan travel”, instruction=”Recommend hotels, places to visit, and activities.” ) |
This code creates a basic AI agent called travel_assistant.
The parameters define:
- The name of the agent
- The language model used
- The purpose of the agent
- Instructions guiding how the agent should behave
Designing Tools of the AI Travel Assistant
AI agents have tools as their building blocks. They enable the agent to act and obtain real-life data.
In the case of the travel assistant project, we develop three valuable tools.
Tool 1: Fetch Location Co-ordinates.
This is the tool translates a name of a location into geographic coordinates like latitude and longitude. It utilizes Google Geocoding API in order to do this conversion.
The coordinates enable the AI agent to find nearby hotels and attractions in an accurate manner.
| import requests def get_lat_lng(location): api_key = “YOUR_GOOGLE_MAPS_API_KEY” url = “https://maps.googleapis.com/maps/api/geocode/json” params = { “address”: location, “key”: api_key } response = requests.get(url, params=params) data = response.json() if data[“status”] == “OK”: loc = data[“results”][0][“geometry”][“location”] return loc[“lat”], loc[“lng”] return None, None |
Tool 2: Find Hotels Near a Location
This application is used to access hotel data around a given place. It applies to Google places API to search hotels in a specified radius.
The tool then ranks the results according to ratings and user reviews in order to give the most appropriate recommendations.
| def get_hotels(lat, lng): api_key = “YOUR_GOOGLE_MAPS_API_KEY” url = “https://maps.googleapis.com/maps/api/place/nearbysearch/json” params = { “location”: f”{lat},{lng}”, “radius”: 2000, “type”: “lodging”, “key”: api_key } response = requests.get(url, params=params) return response.json() |
Tool 3: Find Activity Locations
Tourists tend to look at the activities that they will be able to do in a destination. This application is used to find destinations of certain activities like museums, restaurants, parks, or adventure sites.
| def get_activity_places(location, keyword): lat, lng = get_lat_lng(location) api_key = “YOUR_GOOGLE_MAPS_API_KEY” url = “https://maps.googleapis.com/maps/api/place/nearbysearch/json” params = { “location”: f”{lat},{lng}”, “radius”: 5000, “keyword”: keyword, “key”: api_key } response = requests.get(url, params=params) return response.json() |
With the combination of such findings, the AI assistant is capable of giving the user a variety of activity suggestions.
Creating Specialized AI Agents
We do not develop a single big AI system, but we have many specialized agents that perform various tasks.
Hotel Expert Agent
The hotel professional agent is interested in the recommendation of lodgings. It analyses hotel information and recommends the highest-rated ones are the ones close to the destination of the user.
| from google.adk.agents import LlmAgent hotel_agent = LlmAgent( name=”hotel_expert”, model=”gemini-2.0-flash”, description=”Suggests hotels near the requested location”, instruction=”Recommend highly rated hotels near the location.” ) |
This agent is used to provide reliable hotel recommendations to the travelers basing on ratings and location.
Activities Expert Agent
The activities expert agent focuses on activities that a traveler can engage in within a city. Sightseeing tours, adventure sports, local food experiences and entertainment activities are some of the experiences that it recommends.
| activity_agent = LlmAgent( name=”activity_expert”, model=”gemini-2.0-flash”, description=”Suggests activities for travelers”, instruction=”Recommend popular activities and experiences.” ) |
This assists users to find exciting activities that suit them.
Places-to-Visit Expert Agent
This agent targets landmarks and tourist attraction sites. It has famous places as its recommendation which include monuments, museums, cultural sites, and natural attractions.
| places_agent = LlmAgent( name=”places_expert”, model=”gemini-2.0-flash”, description=”Suggests tourist attractions”, instruction=”Recommend popular places to visit.” ) |
The agent also makes sure that travelers do not fail to see crucial destinations of an area that one is visiting.
Travel Assistant Agent (Main Agent)
The last step is the development of the major travel assistant agent. This agent is the one that integrates all the rest of the agents and is the one that serves the user.
| root_agent = Agent( name=”ai_travel_planner”, model=”gemini-2.0-flash”, description=”Travel assistant that recommends hotels and attractions”, sub_agents=[hotel_agent, activity_agent, places_agent] ) |
The travel assistant is able to interpret the request whenever a user ask a question and then select the best expert agents. It then obtains information on those agents and creates a comprehensive response.
Running the AI Travel Assistant
Once everything is set up, you can run the travel assistant using ADK.
Run the Web Interface
| adk web |
This launches a web interface where you can interact with the travel assistant in a browser.
Run the Command Line Interface
| adk run ai_travel_planner |
This allows you to chat with the assistant directly from the terminal.
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Wrapping it up:
In today’s tech-savvy world, developing AI agents is a major focus for software engineers. Thanks to the new tools like Google’s Agent Development Kit (ADK), building intelligent systems that will automate the processing of user input, use various tools, and automatically create meaningful output has never been easier.
In this blog, we created interfaces for travel-related data, applications that recommend hotels, places to visit and things to do while traveling. Working on these types of projects at this early stage in their development allows developers to better understand how AI agents are used in real-world applications to provide them with the opportunity to create other, more sophisticated and robust AI-driven applications.
FAQs
1. What is Google ADK?
Google Agent Development Kit is a framework used to build AI agents that can perform tasks using large language models and external tools.
2. What is an AI travel assistant?
An AI travel assistant helps you in planning your trips by suggesting destinations, hotel rooms, best site seeings and many more.
3. Do I need advanced AI knowledge to build this?
No, you don’t need advance ai knowledge, you need a good understanding of Python and an understanding of APIs to get started.
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About the Author
Vishalini Devarajan
An Aerospace Engineer turned content writer, I focus on making complex concepts easy to understand through well-structured, reader-friendly blogs. Whether it’s a technical topic or a non-technical one, I love creating content that is clear, engaging, and impactful.
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