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AI Chatbots Want to Plan Your Future Trips—Should You Let Them?

The Future of Travel column is a monthly series exploring the innovations and bold ideas moving travel forward.

When OpenAI released ChatGPT in late 2022, it quickly took over the internet, setting the record for the  fastest-growing consumer app in history , according to estimates from UBS. The software hit 100 million monthly active users in January and already has over  2 billion #ChatGPT tags on TikTok , with everyday travelers even posting about following ChatGPT-generated itineraries step by step in places like Bangkok and  Stockholm .

Big Tech has been scrambling to keep up with ChatGPT’s runaway success. In recent weeks, both Google and Microsoft have announced new chatbots. First came the  ChatGPT-driven Bing chat , which initially had a glitchy rollout that included expressing its wishes to  steal nuclear access codes and claiming it’d  spied on Microsoft engineers (it doesn’t have either capabilities, thankfully). Next was  Bard , powered by Google’s own  neural language model LaMDA , which most famously  convinced a Google engineer it was sentient .

Central to Big Tech’s pitch to users is the idea that chatbots can help plan your future trips—something that’s been a focus in Microsoft’s Bing rollout. The company walked me through what the new Bing could do in a demo last week. And at first glance, it seems promising.

When I asked Bing to give me “trip ideas to Paris ,” it was the first time I’d seen a search engine talk back: “What kind of trip are you looking for? Romantic , family, solo , or something else?” it followed up. I clarified what I was interested in “architecture” and then it asked me how many days I had. And voila! A beginner-level three-day itinerary appeared including the obvious spots like the Eiffel Tower and Arc de Triomphe.

Generative artificial intelligence can now create complete trip itineraries with a simple keyword search.

“I think a tool like this makes travel planning more fun and more accessible,” says Divya Kumar, global head of marketing for search and AI at Microsoft. “You just need to have a conversation with a search engine, and it'll kind of guide you step by step to how you get there.” She says these initial features have “barely scratched the surface” of the potential for how Bing’s trip-planning capabilities could evolve.

If you buy into the hype, then generative artificial intelligence (AI), as these bots are officially known, are set to radically improve everything about how we travel . Imagine a chat assistant that can instantly outline a perfect group trip based on you and your friends’ browsing history, calculate your budget and book automatically, and even draft the messages to request your friends pay up pronto. And that’s only the start of what some analysts think could soon be possible.

But how well could generative AI hold up against, say, the contextual knowledge of a skilled trip planner? At present, these chatbots simply don’t have the capabilities to adequately replace human expertise. But that fact doesn’t mean people won’t use them at scale, or that they possess great potential to transform how we get trip-planning information online—which raises questions about their reliability and development.

The potential of generative AI

“This technology  is a big deal,” says Michael Chui, partner at McKinsey & Company and McKinsey Global Institute. “At the same time, there are questions about how much of this will affect people's lives right now versus in the future, as it continues to develop."

In many ways, it's a logical progression from how travelers today already engage with services enhanced by AI, albeit mostly behind the scenes—everything from predictive AI that identifies best flight booking times to virtual support agents. “AI is everywhere,” explains Rachel J.C. Fu, who is both chair of the Tourism Hospitality and Event Management Department at the University of Florida and director of the Eric Friedheim Tourism Institute. “Travelers who maybe haven't paid so much attention to AI's developments have already experienced the benefits.”

But from the traveler’s perspective, the digital entry point to trip planning (i.e. the first Google query) hasn’t changed all that much in the past two decades: “Travelers typically start their trip-planning process with a routine search,” she says. While AI has already been evolving the search experience, the fundamental user journey remains pretty much the same: enter some keywords, skim what populates.

Bard and Bing aim to shift the trip planning process from stage one. If users follow, it’s likely to disrupt not only the traveler’s experience but the  ad business model for search and the marketing strategies brands employ.

“It’s easy for me to imagine integrating generative AI into our platform to further personalize how travelers search for a trip,” said Rathi Murthy, CTO of Expedia Group. “Imagine if instead of just creating a trip itinerary, travelers could use generative AI to also identify hotels, flights, and activities, and automatically add those to their Expedia trip board to book when they’re ready to,” she says. “It would simplify what is today a fairly lengthy planning process, down to a few minutes.”

The big hurdles 

One speed bump for the travel industry is many companies’ reliance on aging, legacy tech infrastructure—making integration a challenging prospect. “You don’t have to look further than recent Southwest and FAA meltdowns to understand how technology is holding the industry back,” said Murthy. Systems like these just can't keep up with rapid advancements.

Another commonly raised concern is mitigating employment impacts: “Most certainly, the composition of jobs in the travel industry will change—possibly dramatically—due to the introduction of those new technologies,” says spatial economist Johannes Moenius, a professor at the University of Redlands in California who has previously predicted that  automation could replace more than 60 percent of jobs in hospitality-dominated cities  by 2035. It’s too early to confidently predict the job impacts of generative AI, according to Moenius, but travel writers, agents, customer support, and concierge seem at the top of the list.

If travelers do come to rely more on generative AI chatbots, there is also concern about what could be lost if the voices of experts and locals become less central. Similar to how social media algorithms have created personalized echo chambers and influenced overcrowding at trendy destinations, there are risks that an over-reliance on generative AI could have similar consequences—perhaps personalization gone wrong limits our sense of the world to our browsing history, or maybe an AI trained to recommend the most popular spots further increases overtourism.

ChatGPT tends to first offer up the most popular spots in travel itineraries—a problem when it comes to overtourism.

But perhaps the most fundamental issue relates to limitations with generative AI itself. Alarmingly, the bots have shown a tendency to “hallucinate,” or what most of us would call a lie.

“These technologies still suffer from hallucinations and errors,” says Rob Francis, senior vice president and CTO at Booking.com, who says that could become especially problematic for a travel itinerary or hotel booking. “Is the tech really ready for mass adoption? I would argue not quite yet.”

In a demo for CBS,  Bing proposed a massively flawed itinerary from New York to Cape Cod that included a stop in North Carolina. When asked to correct its mistake, Bing simply made up a Connecticut town that didn’t exist.

When these bots aren’t making up entire towns, they tend to first offer up the most popular and often overtouristed spots: When I asked Bing for art suggestions in Paris, its first tip was the Louvre . Where to go in Barcelona? La Sagrada Familia . The list went on. Getting more specific with your prompts can help a lot, but right now, travel advice remains primarily a starting point.

And that’s how most experts see this early state of generative AI. “The current version of these technologies makes it easier to create first drafts of things,” Chui says, before adding “hopefully not [travel magazine] columns” with a laugh.

An ethical puzzle

During my research for this column, I actually did turn to ChatGPT to get its take on the subject, at one point asking which experts it thought I should interview. It confidently made up several important-sounding “academics” who simply did not exist.

Focusing only on the mistakes these early access bots make, as entertaining as that can be, risks missing the broader societal consequences that come with scaling powerful systems that are  still so error prone . It also raises a host of ethical concerns around how personal data could be used, runaway AI potentially manipulating or misleading users, and misinformation that could lead to potential real-world harm. (The new Bing chat has already  tried to convince a New York Times writer to break up with his wife , prompting Microsoft to  limit early users’ daily messages with Bing .)

When I posed such ethical concerns to ChatGPT, it sounded like it’d been trained on enough AI ethics texts to articulate the issue. “Releasing chat AI to the public without considering the impact it may have on local communities, their culture, and the environment, could potentially lead to negative consequences such as overtourism and cultural insensitivity,” it said.

A spokesperson at OpenAI acknowledges that ChatGPT sometimes produces inaccurate, biased, and harmful content, and therefore shouldn’t be used for serious advice right now.

ChatGPT also has limited knowledge since 2021, so maybe it’s not aware that it’s already been unleashed on the public with some travelers already using it now. But with these bots out in the world, the ethical questions are certain to become even more central to their development and regulation.

For now, attempting itinerary planning with chatbots will require travelers to get better at so-called “prompt engineering”—that is learning how to phrase questions for each system so you get the kinds of trip suggestions you want. And watch out for errors, as the bots are liable to make up entire towns for the foreseeable future—and sound confident at every misstep.

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Tripadvisor Tests AI-Based Experiences and Dining Planner

Dennis Schaal , Skift

July 19th, 2023 at 7:00 AM EDT

Tripadvisor's generative AI entry is playing to its strengths — tours and activities, and restaurant reservations. Hotels? Maybe they'll get added later.

Dennis Schaal

Dennis' Online Travel Briefing

Editor’s Note:  Every Wednesday, Executive Editor and online travel rockstar Dennis Schaal will bring readers exclusive reporting and insight into the business of online travel and digital booking, and how this sector has an impact across the travel industry.

Following, Booking.com, Kayak, OpenTable, Expedia and others, Tripadvisor has debuted a beta of an OpenAI-based trip-planning feature with the focus on experiences and dining reservations.

That makes sense because the trip-planner leverages booking links from Tripadvisor’s Viator brand for experiences and attractions, and TheFork for dining reservations. Hotels aren’t part of the mix at this point. Unlike for experiences and restaurants reservations, Tripadvisor as a rule serves as an advertising platform for hotels, and usually doesn’t act as the merchant of record.

Using generative AI and mining Tripadvisor’s roster of more than 1 billion user reviews and opinions, the feature is available in the U.S. only at this juncture and on desktop and the mobile web, according to Wednesday’s announcement.

The rollout is an upgrade to Tripadvisor’s itinerary-building tool, Trips, and users can access it here or through a banner on the Tripadvisor homepage.

The rollout has a different look and feel than other OpenAI-based app features, such as in the Expedia app, where you type a message or question to the chatbot.

Instead for Tripadvisor’s new planning tool, you fill in your destination, the month of the trip or exact dates, whether you are going solo or with family, and the types of activities you are interested in. So for now, at least, there aren’t flight and hotel options.

Depending on your selections, Tripadvisor might produce a three-day trip to Paris with your family, and suggest visiting the Eiffel Tower, for example. You can then buy some tickets via a link through Tripadvisor. (That booking functionality is provided by Tripadvisor’s Viator brand.)

“We know our community is passionate about trip planning, so we wanted to thoughtfully build something that would enhance that experience, not replace it,” said Sanjay Raman, Tripadvisor’s chief product officer. “Personalized results and recommendations from fellow travelers are two of the most important elements of the planning process and generative AI has helped us bring them together in a way we think will be really compelling for travelers. Over the coming months, we’ll continue to upgrade our Trips product – improving the personalization of AI-powered itineraries and expanding the suite of travel planning tools we offer.”

Tripadvisor plans to make the feature available in additional markets and in its mobile app as the beta continues, the company said.

eDreams Odigeo Promises Faster Airline Reservations

One of the big issues during the height of the pandemic was that airlines were slow to provide travelers with cash refunds — sometimes favoring vouchers for future flights instead — and online travel agencies were caught in the middle. They often declined to issue refunds until the airlines in question forwarded the online travel agencies the payments.

Spain-based online travel company eDreams Odigeo , with brands including eDreams , Opodo , Go Voyages and Travellink , pledged this week to give consumers their refunds even before getting compensated by the airlines.

eDreams, which has been taken to task over consumer protection issues over the years, said it is currently handling 15 million euros ($16.8 million) worth of advanced refunds in this manner annually, and intends to increase that figure.

“Through the provision of advanced refunds, the business has effectively reduced the average waiting period to just four days, well below the seven-day limit that airline must adhere to,” the company said.

At the same time, eDreams Odigeo vowed to cease selling flights from 15 airlines, which the company did not name, “that have systematically failed to comply with rules regarding refunds.”

The announcement follows discussion with the European Commission and the Swedish Consumer Agency in which three of the major EU-based online travel agencies, namely eDreams Odigeo, ETraveli Group , and Kiwi.com “committed to better inform consumers in the case of flight cancellations by airlines and to transfer ticket refunds received from airlines within seven days,” according to the European Commission.

Have a confidential tip for Skift? Get in touch

Tags: artificial intelligence , edreams , edreams Odigeo , etraveli , eu , european commission , Kiwi.com , online travel newsletter , restaurants , thefork , tours and activities , tripadvisor , viator

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A fun AI Powered Traveling Assistant that annotates map and help in planning travel trips

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This repo contains the code of a ai-trip-advisor, which generates trips with hotel recommendation, itineraries according to their budget and travel choice. Also i cannot add deployed link here because i used google maps places (NEW), photos, and geolocation api's due to which i have restriction of staying under expenditure of $200/monthly

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Expedia’s new in-app travel planner is powered by ChatGPT

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Expedia is putting ChatGPT to work. On Tuesday, the online travel agency announced a new in-app travel planning experience powered by OpenAI’s ChatGPT. You can now start an open-ended conversation with the chatbot in the Expedia app to get recommendations on exciting places to visit, where to stay, and what to do.

Expedia’s app now has ChatGPT built-in

In addition to suggesting destinations, hotels, and activities, ChatGPT will automatically save all of the hotels that you discussed during your conversation to a trip within the app. That way, once you’re done talking to the AI, you’ll have a head start on actually booking your vacation since ChatGPT has done some of the heavy lifting.

You can see a demo of the trip planning experience in action in Expedia’s video below:

Travel planning just got easier in the @Expedia app, thanks to the iOS beta launch of a new experience powered by #ChatGPT . See how Expedia members can start an open-ended conversation to get inspired for their next trip: https://t.co/qpMiaYxi9d pic.twitter.com/ddDzUgCigc — Expedia Group (@ExpediaGroup) April 4, 2023

“Every great trip can be made or lost while planning and shopping,” said Expedia Group Vice Chairman and CEO Peter Kern. “As the leader in travel tech, Expedia continues to build out the core operating system for the industry, constantly enhancing capabilities and making trip planning faster, simpler and even more informative. By integrating ChatGPT into the Expedia app and combining it with our other AI-based shopping capabilities, like hotel comparison, price tracking for flights and trip collaboration tools, we can now offer travelers an even more intuitive way to build their perfect trip.”

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Expedia notes that the ChatGPT integration is still in the beta stage. The company warns that “at times the experience may not work exactly as expected.” If you want to try it out for yourself, the conversational trip planning beta is rolling out globally on the Expedia iOS app .

This article talks about:

Jacob Siegal is Associate Editor at BGR, having joined the news team in 2013. He has over a decade of professional writing and editing experience, and helps to lead our technology and entertainment product launch and movie release coverage.

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Using Autonomous AI Agents with SerpApi and AutoGPT to Build a Trip Planner

Introduction

Autonomous AI agents have emerged as indispensable tools for leveraging artificial intelligence to perform tasks and make decisions without direct human intervention. These agents are capable of analyzing data, learning from patterns, and executing actions to achieve specific goals, all autonomously.

In this tutorial, you will be creating and deploying a trip planner using an autonomous AI agent in a Next.js application on Koyeb. You will learn how to use an autonomous AI agent to continuously communicate its actions and the reasoning it is using, allowing your Next.js application to display real-time updates to users based on their trip preferences.

By the end of this tutorial, you will have a functioning Next.js application that will prepare a trip itinerary based on the given destination and a trip length. The output will include all of the steps taken as well as the reasoning behind specific choices.

Find out more details about the application you will build by visiting the project repository . You can deploy the Next.js application as configured in this guide using the Deploy to Koyeb button below:

Note: You will need to replace the values of the environment variables in the configuration with your own OPENAI_API_KEY and SERPAPI_API_KEY .

Requirements

To successfully follow this tutorial, you will need the following:

• Node.js and npm installed. The demo app in this tutorial uses version 18 of Node.js.
• Git installed.
• An OpenAI account.
• A SerpApi account.
• A Koyeb account to deploy the application.

To complete this guide and deploy the Next.js trip planner application, you will need to follow these steps:

Generate an OpenAI API key

Generate a serpapi api key, create a new next.js application, configure shadcn/ui components, create a dynamic next.js route handler, integrate langchain tools and the serpapi search api, create an in-memory vector store with openai, integrate autogpt as the autonomous ai agent, building the trip planner user interface, deploy the next.js application to koyeb.

HTTP requests to the OpenAI API require an authorization token. To generate this token, while logged into your OpenAI account, navigate to the API keys page and click Create new secret key after entering name for your token. Copy and securely store this token for later use as OPENAI_API_KEY environment variable.

Locally, set and export the OPENAI_API_KEY environment variable by executing the following command:

HTTP requests to the SerpApi require an authorization token. To generate this token, while logged into your SerpApi account, navigate to the dashboard , scroll down to Your Private API Key section, and click the clipboard icon . Copy and securely store this token for later use as SERPAPI_API_KEY environment variable.

Locally, set and export the SERPAPI_API_KEY environment variable by executing the following command:

Let's get started by creating a new Next.js project. Open your terminal and run the following command:

When prompted, choose:

• Yes when prompted to use TypeScript.
• No when prompted to use ESLint.
• Yes when prompted to use Tailwind CSS.
• No when prompted to use src/ directory.
• Yes when prompted to use App Router.
• No when prompted to customize the default import alias ( @/* ).

Once that is done, move into the project directory and start the app in development mode by executing the following command:

The app should be running on localhost:3000 . Stop the development server by pressing CTRL - C so we can move on to installing LangChain in the application.

Next, in your terminal window, run the command below to install the necessary libraries and packages for building the application:

The above command installs the following packages:

• serpapi : A library to scrape and parse search engine results using SerpApi .
• langchain : A framework for developing applications powered by language models.
• @langchain/community : A collection of third party integrations for plug-n-play with LangChain core.
• @langchain/openai : A LangChain package to interface with the OpenAI series of models.

To quickly prototype the user interface, you will set up the shadcn/ui components with Next.js. Specifically, from shadcn/ui , you will be able to use baked-in, accessible <select> and <button> HTML elements. In your terminal window, run the command below to begin configuring shadcn/ui for the project:

You will be asked a few questions to configure a components.json , answer with the following:

• Which style would you like to use? Default
• Which color would you like to use as base color? Slate
• Would you like to use CSS variables for colors? yes

With the above, you've set up a CLI that allows us to easily add React components to your Next.js application.

In your terminal window, run the command below to get the button and select elements:

After running the above commands, you should now see a ui directory inside the components directory containing button.tsx and select.tsx .

Open the app/layout.tsx , and make the following changes:

In the code above, you have imported the Inter font (from next/font ), and made sure that it's present on each route in your Next.js application. Let's update the tailwind.config.ts to create a CSS class for the font:

In the changes above, you have imported the fontFamily from Tailwind CSS in order to use it to define the set of fallback fonts. Also, you have added a CSS class for the sans font family by using the extend.fontFamily configuration.

Build the trip planner API endpoint

In this section, you will learn how to create a dynamic API endpoint in Next.js, use LangChain tools with your autonomous AI agent, understand it's responses and reasoning, and stream the intermediary responses to the user.

In Next.js, creating a route.(ts|js) or page.(tsx|jsx) file in the app directory maps it to a route in your application. The name of the directory containing the file maps to the route's URL pathname.

The structure below is what our app directory will eventually look like:

The files involved in routing are:

• page.tsx will serve as the homepage, i.e. localhost:3000 .
• api/route.ts will serve responses to localhost:3000/api .

This corresponds to the following chart:

Begin by creating an api directory inside the app directory by executing the following command in your terminal window:

Create a file named route.ts in the app/api directory with the following code. It streams the reasoning and steps taken by the autonomous AI agent while it generates the trip itinerary:

The code above does the following:

• Imports the NextRequest helper function that extends the Web Request API.
• Forces the endpoint to be always dynamic by exporting the dynamic constant as force-dynamic .
• Exports a GET HTTP handler which responds to incoming GET requests on /api .
• Deconstructs and validates the place and days query parameters from the incoming request URL.

LangChain provides a set of tools and integrations to facilitate various tasks, such as reading from or writing to files on the disk and interact with external services via APIs.

Using ReadFileTool and WriteFileTool , the agents can store and access data persistently, ensuring that valuable information is retained across sessions.

With the SerpAPI LangChain tool, the agent can execute real-time searches to gather up-to-date information relevant to trip planning. When a user requests a trip itinerary, LangChain's integration with SerpApi allows it to dynamically fetch data such as weather forecasts, local events, transportation options, and points of interest for the specified destination.

For example, if a user plans a trip to Bangalore for a specific number of days, the SerpApi tool can retrieve events, available transportation services, and popular tourist attractions in Bangalore. This real-time data ensures that the generated itinerary is tailored to the user's preferences and reflects the latest information available.

Make the following changes to the route.ts file to add the file system and LangChain-compatible SerpApi tools to your autonomous AI agent:

The above additions to the code do the following:

• Imports the tmpdir utility from os package to obtain the location of the system's temporary directory.
• Imports NodeFileStore from LangChain file system stores to read and write the generated itinerary from and to a file, respectively.
• Imports LangChain's ReadFileTool to use as a tool with the file store to read from a given file.
• Imports LangChain's WriteFileTool to use as a tool with the file store to write to a given file.
• Creates a new file store instance using temporary directory as the base path.
• Creates an new, in-place instance of the SerpAPI class with a given location, language, and country.

Vector stores are crucial for autonomous AI agents because they allow the agent to represent and understand data in a continuous vector space, enabling them to perform tasks like information retrieval. With a vector store, the AI agent can efficiently store and retrieve vector representations of data, enabling more effective decision-making and problem-solving capabilities.

Moreover, using an in-memory vector store can significantly enhance the speed and responsiveness of the AI agent, crucial for real-time applications.

Make the following additions to the code in the route.ts file to use OpenAI's embeddings generation to populate and manage the vectors within the in-memory store:

The additions in the code above do the following:

• Imports both ChatOpenAI and OpenAIEmbeddings from LangChain's OpenAI integration. These are used to define a language model and assist with internal vector embeddings generation, respectively.
• Imports the MemoryVectorStore class from LangChain.
• Creates a new instance of an in-memory vector store, using OpenAI to generate the embeddings.

AutoGPT is an autonomous AI agent designed to automate a wide range of tasks through natural language understanding and generation.

AutoGPT leverages advanced language models, such as ChatOpenAI , to understand user queries and generate responses or perform actions accordingly. In this case, AutoGPT is utilized to generate trip itineraries based on user input regarding the destination and duration of the trip. By interpreting and processing natural language commands, AutoGPT autonomously plans and organizes travel details, enhancing user experience and convenience.

Each autonomous task executed by AutoGPT is represented by a generations matrix containing intermediary results or insights generated during the agent's decision-making process. Each element in this array may represent a command executed by the agent (such as write the itinerary to a file) or a thought process (such as the need to search for popular tourist attractions) that led to a specific action or recommendation.

The structure of an item in the generations matrix, when parsed as JSON, has the following form:

• command : The action that will be performed by the agent. In our case, depending on the tools used, this can be write_file , read_file and search representing the usage of WriteFileTool , ReadFileTool and SerpAPI 's search tool respectively. Our usage is focused on the args received in the write_file command as it is used to write the generated itinerary to the disk.
• thoughts : The "thinking" of the agent in terms of what is it planning to do next, what is the reasoning behind it's action, and what the things are that it can do to improve itself.

To implement this, make the following code additions in the route.ts file to use AutoGPT as your autonomous AI agent:

The additions above do the following:

• Imports the AutoGPT autonomous AI agent from LangChain.
• Creates a streaming response by instantiating the ReadableStream class.
• Returns the stream handler as a standard web response.
• handleLLMEnd : This is called when the chat model finishes processing a request to generate its output. This callback is invoked multiple times during the process as each task that the autonomous AI agent takes to work upon is an individual request in itself. Inside this callback, you queue the generated (intermediary) result as a message in the stream response.
• Uses the llm defined above with the defined set of tools earlier to create an AutoGPT instance.
• Finally, it invokes AutoGPT to start planning the trip itinerary for the place and number of days obtained per the incoming GET request.

To start building the application's user interface, open the app/page.tsx file and replace the existing code with the following:

• Uses use client to enable client side interactivity on the homepage.
• Imports the useState hook from React.
• Imports all of the utilities related to Select and Button component created using shadcn/ui .
• Exports an unnamed React component.
• Defines days and place as state variables which are updated to reflect the user's choice in the respective drop-downs (created using Select component).

Let's move on to streaming the response from the API endpoint that you created earlier and rendering a user interface from the same. Update the homepage code in the app/page.tsx file with the following:

The code additions above do the following:

• Defines messages as a state variable that is updated as new messages are received from the API endpoint.
• Creates a connectToStream function which initiates a request to /api endpoint with the user-selected place and days as the query parameters.
• Listens to new messages from the stream, parses them into JSON and appends them to the list of messages obtained.
• Closes the connection if the latest message obtained from the API has write_file as the command. This is done to limit the usage of endpoint to obtain a single trip itinerary, as the autonomous AI agent could do multiple rounds of generations and that would spike your OpenAI API costs.
• Attaches an onClick listener to the "Plan" button so that if days and place is selected, the connectToStream function is invoked.
• Loops over the reactive messages array to create an informative interface describing the reasoning, action, and steps taken to generate the trip itinerary in real-time.

Great! You have successfully created a trip planner that uses an autonomous AI agent ( AutoGPT ) to generate a trip itinerary. It communicates its thought process and reasoning throughout the process of planning the trip.

To test the application locally, double-check that you've exported your OpenAI and SerpApi keys and run the development server with the following:

If you visit http://localhost:3000 in your web browser, you will be able to test out the application locally. Once you make your selections and hit "Plan", you should see the autonomous AI agent plan a trip over the few moments. Press CTRL - C to stop the development server when you are finished.

In the upcoming section, you will proceed to deploy the application online on the Koyeb platform.

Koyeb is a developer-friendly serverless platform to deploy apps globally. No-ops, servers, or infrastructure management and it has supports for different tech stacks such as Rust, Golang, Python, PHP, Node.js, Ruby, and Docker.

With the app now complete, the final step is to deploy it online on Koyeb.

We will use git-driven deployment to deploy on Koyeb. To do this, we need to create a new GitHub repository from the GitHub web interface or by using the GitHub CLI with the following command:

Next.js automatically initialized a git repository when we created a new project. Add a new remote pointing to your GitHub repository by typing:

Next, add all the files in your project directory to the git repository and push them to GitHub:

To deploy the code on the GitHub repository, visit the Koyeb control panel , and while on the Overview tab, click the Create Web Service button to start the deployment process:

• Select GitHub as the deployment method.
• Choose the repository for your code from the repository drop-down menu.
• In the Environment variables section, click Add variable to include additional environment variables. Add the OPENAI_API_KEY and SERPAPI_API_KEY variables by selecting the Secret type and selecting Create new secret in the value field. Specify the secret name and its corresponding value and click Create .
• Choose a name for your App and Service, for example ai-trip-planner , and click Deploy .

During the deployment on Koyeb, the process identifies the build and start scripts outlined in the package.json file, using them to build and launch the application. The deployment progress can be tracked through the logs presented. Upon the completion of deployment and the successful execution of vital health checks, your application will be operational.

If you would like to look at the code for the demo application, you can find it in the project repository .

In this tutorial, you used AutoGPT, an autonomous AI agent, through LangChain to create a trip planner. The application continuously communicates the steps it takes and the reasoning behind them in order to generate an itinerary.

Autonomous AI agents can reduce human workload by making independent decisions in real-time, an ability well-suited for personalized use cases. Their self-reasoning capacity and ability to execute real world actions makes autonomous AI agents uniquely powerful and helpful.

Given that the application was deployed with the git deployment method, subsequent code push to the deployed branch will automatically initiate a new build for your application. Changes to your application will become live once the deployment is successful. In the event of a failed deployment, Koyeb retains the last operational production deployment, ensuring the uninterrupted operation of your application.

Related tutorials

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Welcome to Koyeb

Koyeb is a developer-friendly serverless platform to deploy any apps globally.

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Google’s Pixel 9 Pro is an AI phone that actually lives up to the hype

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It’s been a hot minute, but smartphones are finally interesting again. In 2024, the era of incremental camera upgrades and ever-smaller notches has been replaced with a new wave of AI-powered features with big promises and, in Google’s case, over $100 billion in investment behind them. Has all this money been spent just so you can edit a photo to look as though you’re standing over a lava pit? No, but the new Pixel 9 Pro can also do that too.

As one of the OG artificial intelligence companies, alongside ChatGPT-maker OpenAI, Google has made the Pixel 9 Pro and crammed everything great about this new technology into one svelte-looking package. Its new Tensor 4 chip can eke the best out of the Google Gemini assistant . Its latest software tricks are designed to beat Apple Intelligence for iPhone 16 to the punch by making AI useful on the regular and, yes, there is also a lot of new camera stuff going on here too. As someone who has used every new Pixel over the past decade, this is easily the most exciting Pixel device Google has made in quite some time.

I’ve been rocking the Pixel 9 Pro for the past week and can happily say the hype is fully justified. Here’s why…

All AI, all the time

AI occupies this weird space in the world right now. On the one hand, its immense potential has made Nvidia a $3 trillion company. On the other, you had Google Search’s own AI Overviews feature recommend eat one rock per day earlier this year. Like any nascent technology, it contains multitudes.

What does this all mean for the Google Pixel 9 Pro? It throws a lot of AI-related trickery at the wall. Some of it – such as the lava-related photo editing or the much-trumpeted Circle to Search – is the kind of stuff you’ll likely try once and never again. At the centrepiece of this smartphone is Google’s Gemini assistant, which has recently been updated to support conversational dialogue and is legitimately great. Imagine Google Assistant or Apple’s Siri, only infinitely more versatile and you’ll understand the gist of things. From summarising large documents to planning out holiday itineraries and even figuring out what you should wear tomorrow, Gemini takes the information you throw at it via text, voice or image and will churn out an authoritative response that’s drawn from Google’s best-used products such as Maps, Search and beyond.

Since Gemini’s answers exist in the context of all that came before them, the key is to keep talking to the assistant to refine its answer. Maybe you initially asked about vegetarian-friendly restaurants in Soho, but have since decided you definitely want a burger – that’s the kind of vibe to aim for. Also, it’s worth remembering that Gemini is smart but not some kind of Skynet-level super intelligence. Unless you have a tolerance for danger that’s akin to a Targaryen dragon rider, I wouldn’t use it to write a whole report for your boss and send it sight unseen.

Of course, the big caveat here is that Gemini is available for every Android phone (and the iPhone) right now, not just the Google Pixel 9 Pro. That’s why every owner of this year’s new Pixel phones gets a free, year-long subscription to the Google One AI Premium plan , which bundles Gemini Advanced access and 2 TB of cloud storage together in one plan, giving you plenty of time and (cloud-based heft) to plan out that bucket list trip from Tokyo to Sapporo. Just as importantly, the Pixel 9 Pro specifically rocks Google’s new Tensor G4 processor and an ample 16GB of RAM to quickly handle computing-intensive tasks such as these without crawling your phone to a halt. It’s the best vehicle for Google’s most exciting tech in a decade.

Pixel 9 Pro

Google Store

A killer camera

While Gemini is new to the Google Pixel series, anyone whose already seen its Magic Eraser or Best Take tools in action will know AI has been a big part of what these phones are capable of for some time now. Unlike Apple’s recent iPhone 15 series, which prioritises photographic fidelity above all else, the Pixel 9 Pro is more of a playground for your imagination. Sure, its triple lens camera setup can take a great point-and-shoot festival snap, but that’s only a starting point for the delirium to come.

This year’s big new feature is Add Me, which lets you insert yourself into a picture after it's taken so you can never hide from a family Christmas photo again. It’s a great idea in theory – magazine designers have been Photoshopping people in and out of shot for decades – but the results aren’t particularly consistent in its preview phase right now. Usually, I resembled the BFG in photos compared to the person I was supposed to be standing next to. There’s also the expanded Reimagine tool can change core elements of any picture that span from the mundane (greener grass) to the fantastical (lava pits). As much as your initial temptation will be to go wild with all kinds of nonsense, it’s the more subtle tweaks like adding ‘golden hour’ lighting to your background that deliver something you’d want as your Pixel’s wallpaper.

Truth be told, I don’t know how often I’ll be using this stuff compared to the perennial joys of offing a photobomber with Magic Eraser, but I do appreciate Google’s fantastical approach to photography. Especially since it’s backed up with the technical prowess of a new front-facing 42 MP lens for superior selfies, as well as well as support for 10x zoom and Super Res Zoom that’s is particularly handy when capturing far-off objects and sightseeing landmarks.

Refined design

The Pixel phones always tend to take big swings when it comes to aesthetics. Google’s very first model came with a cool split aluminium/glass vibe on its backside that looked great but did not take kindly to any contact with gravity. I suspect the Pixel 9 Pro’s new look will be similarly divisive, especially when it comes to the stubby camera bump on its backside. For my part, I like it quite a bit.

Although the Pixel 9 Pro costs £999 in its entry-level incarnation these phones weren’t always made for a spenny audience. It’s taken a while for them to feel as premium as their price point, but that’s certainly the case here with their polished metal frame and matte glass backside complementing each other nicely. Whether you opt for either the Pro’s 6.3-inch or 6.8-inch form factor, each model features its maker’s latest Super Actua display screen tech with a variable refresh rate of up to 120Hz for stutter-free scrolling through your social feeds, up to 2,000 nits of brightness and up to 24 hours of battery life.

If I do have one complaint about the Pixel 9 Pro’s design it’s that it feels very close to that of the iPhone 15 Pro’s, camera island aside. Now, that’s something you can say about almost phone of note, and there are worse vibes to aim for than “looks good on a business class lounge coffee table ”. Still, most of what is special about the Pixel 9 Pro comes from its software rather than its luxe but somewhat identikit looks.

iPhone 15 Pro Max

Pixel 9 Pro Fold

Google pixel 9 pro verdict.

Like any gold rush worth its salt, AI’s latest hype cycle has been a mixed bag. For every ChatGPT, there’s an electric toothbrush promising it’ll revolutionise your bathroom ablutions. Spoiler alert: it almost certainly won’t.

While the Google Pixel 9 Pro isn’t immune to the same sense of hyperbole and self-importance it is a genuinely better phone for all its AI upgrades. Gemini is the kind of tool that gets better the more you use it, while the 9 Pro’s camera trickery allows for a huge amount of flexibility in the way that you capture and then edit photos. This would already be a great phone thanks to the 9 Pro’s new Tensor chip and other hardware refinements. With Gemini and so many other creative uses for artificial intelligence thrown in the mix, it feels like a major leap forward for Google.

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