Gemini 2.5 + LangGraph + Replit = AI Superpowers in Your Browser.

Thanks to Paul Couvert’s tutorial, you can now deploy a fullstack AI agent—powered by Google’s Gemini 2.5—without ever leaving your browser. Whether you’re a developer or an AI enthusiast, this is one of the easiest ways to get started with conversational agents using LangGraph on Replit.

Let’s walk through the process in just five simple steps.

Step 1: Import the Repo on Replit

Go to Replit.com
Click Create Repl → Import from GitHub
Paste this GitHub repository link:

arduinoCopyEdithttps://github.com/google-gemini/gemini-fullstack-langgraph-quickstart

You’ve now cloned the full Gemini agent project into your own workspace.

Step 2: Install Dependencies and Configure the Backend

Once the import is complete:

Terminal Commands:

Run the following commands in the Replit shell:

bashCopyEditpip install -e ./backend && npm install --prefix frontend
make dev

API Configuration:

In the backend folder, locate the .env.example file
Rename it to .env
Open it, remove the comment symbol (#), and paste in your Google API key

Step 3: Update the Frontend Configuration

To ensure the frontend connects properly:

Open the file:
arduinoCopyEditfrontend/vite.config.ts
Replace the entire content of the file with the updated version found at this link:
Pastebin – Updated Vite Config

Step 4: Edit and Customize Your Agent

At this point, your agent is functional. To personalize it:

Use the Replit AI Assistant to make changes using plain English. For example:

“Add a greeting message when the agent starts”
“Enable the agent to summarize long articles”
“Connect it to a weather API”

The assistant can automatically generate the necessary code updates.

Bonus: Skip Manual Setup

If you’d prefer to skip all manual steps, Paul Couvert has provided a pre-configured version:

Visit: Gemini Fullstack Agent on Replit
Click “Remix this app”
Add your API key in the backend/.env file
Start the app

No command line or config edits needed.

What This Agent Can Do

This setup enables you to run a Gemini 2.5-powered agent that supports:

Natural language conversations
Multi-step reasoning
API-based tool usage
Custom instructions or task flows

With LangGraph as the underlying orchestration framework, the agent is modular, scalable, and easy to modify.

Final Thoughts

Building and deploying an AI agent used to be a complex process. Now, with the combination of Replit, LangGraph, and Gemini 2.5, you can get started in under 10 minutes. Whether you want to create a smart chatbot, a research assistant, or a task automation tool, this setup is an excellent starting point.

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