8 Feb 2025

Create an AI Agent Using Browser-Use and Gemini API

Artificial Intelligence (AI) is transforming the way we interact with the web. AI agents can browse, extract, and analyze information, making them useful for research, automation, and productivity. In this guide, we will walk you through how to build an AI agent using Browser-Use and the Gemini API.

What is Browser-Use?

Browser-Use is an open-source project that enables AI-powered browsing. It allows your AI agent to navigate web pages, extract content, and perform interactions as a human would. It can be integrated into your own projects to create powerful automation solutions.

What is the Gemini API?

The Gemini API by Google provides powerful language models capable of understanding and generating human-like text. Integrating Gemini with Browser-Use enables an AI agent to comprehend web pages, summarize content, and generate insights.

Steps to Build Your AI Agent

1. Set Up Your Development Environment

Before we begin, install Python and Git if you haven’t already:

Once installed, open a terminal and set up a virtual environment:

2. Install Required Dependencies

Clone the Browser-Use repository and install the required dependencies:

Additionally, install requests to communicate with the Gemini API:

3. Set Up the Gemini API

To use the Gemini API, you need an API key from Google AI Studio. Follow these steps:

Sign up on Google AI Studio (if you haven’t already).
Get your API key from the dashboard.
Store it securely in an environment variable:

4. Build the AI Agent

Create a Python script (ai_agent.py) and add the following code:

import requests
import json

def fetch_gemini_response(prompt):
    url = "https://generativelanguage.googleapis.com/v1/models/gemini-pro:generateText"
    headers = {"Content-Type": "application/json"}
    params = {"key": "your_api_key_here"}
    data = {"prompt": {"text": prompt}, "temperature": 0.7}
    
    response = requests.post(url, headers=headers, params=params, json=data)
    return response.json()

def main():
    query = "Summarize the latest news on AI advancements."
    response = fetch_gemini_response(query)
    print("AI Agent Response:", response)

if __name__ == "__main__

Replace your_api_key_here with your actual Gemini API key.

5. Integrate Browser-Use for Web Scraping

Modify your script to use Browser-Use for extracting web content:

6. Run Your AI Agent

Execute your script:

Your AI agent will now fetch and summarize the latest news from Hacker News!

Additional Enhancements

Web UI for Your AI Agent: Use WebUI to create a front-end interface.
Deploy as an API: Use FastAPI or Flask to make your agent accessible via HTTP requests.
Automation with n8n: Automate workflows using n8n.
Enhance with Ollama & OpenRouter: Leverage Ollama and OpenRouter for multi-model integrations.

Conclusion

By combining Browser-Use with Gemini API, you can create an AI agent that intelligently browses the web, extracts insights, and automates tasks. This setup is ideal for research, content aggregation, and AI-powered assistants. Start building today and enhance your AI workflows!