X (Twitter) AI Agent

X (Twitter) AI Agent is an AI web agent that interacts with tweets, built using Browser Use and Browserbase.

Demo

https://storage.googleapis.com/audio_bucket_studiaai/demo.mp4

Features

• 🤖 Autonomous - Auto-reply to tweets on X
• 🌐 It's free - Literally all free tools (Browser-use and Browserbase) with limits
• 📱 Simple-to-use UI - Even your grandma can use it lol
• 🔄 Observation - See your agent in action with agent browsing session playback

Architecture

The project is divided into two main components:

Client

A modern web application built with:

• Next.js 15 - React framework with server-side rendering
• TypeScript - For type safety and better developer experience
• Tailwind CSS - For styling and responsive design
• Radix UI - Accessible UI components
• Zustand - State management
• Framer Motion - For animations and transitions

Server

A Python backend built with:

• FastAPI - High-performance web framework for building APIs
• Browser-use - Library for browser automation with LLMs
• Browserbase - Browser infrastructure for reliable web automation
• LangChain - Framework for developing applications powered by language models
• Playwright - Under-the-hood browser automation library

How It Works

• You enter your X login credentials and click login, which creates a context (identified by the context id) for the agent to perform the login task (go to X.com and enter credentials and login).
• The first login step is provided in order to save login info (via cookies) for future agent tasks.
• Next the user will click the run agent button, this will initiate an agent run (with saved context data, i.e auth) that will perform the task of commenting on a post on your For You page on X.
• After the agent has performed the task, you will be able to view the session recording to see how the agent has performed the tasks.
• Please note that all data (agent session data and agent context id) has been stored locally for privacy.

Getting Started

Prerequisites

• (free) Browserbase API key + Browserbase Project ID (Get them at https://www.browserbase.com/settings)
• (free) OpenAI API (Get one at https://platform.openai.com/api-keys)

Installation

Client Setup

1. Navigate to the client directory:

cd client

2. Install dependencies:

npm install
# or
pnpm install

3. Configure environment variables (optional - can be done on the interface):

# Copy example env file
cp .env.example .env

# Then edit the .env file with your values:
OPENAI_API_KEY=
BROWSERBASE_API_KEY=
BROWSERBASE_PROJECT_ID=

NEXT_PUBLIC_BROWSERBASE_API_KEY=
NEXT_PUBLIC_BROWSERBASE_PROJECT_ID=
NEXT_PUBLIC_OPENAI_API_KEY=

4. Start the development server:

npm run dev
# or
pnpm dev

5. The client will be available at http://localhost:3000

Server Setup

1. Navigate to the server directory:

cd server

2. Create and activate a virtual environment using uv:

# Install uv if you don't have it
pip install uv

# Create and activate virtual environment
uv venv
source .venv/bin/activate  # On Windows, use .venv\Scripts\activate

3. Install dependencies with uv (faster):

uv pip install -r requirements.txt

4. Configure environment variables (optional - if you've configured them on the frontend):

# Copy example env file
cp .env.example .env

# Then edit the .env file with your values:
BROWSERBASE_API_KEY=your_browserbase_api_key
OPENAI_API_KEY=your_openai_api_key
BROWSERBASE_PROJECT_ID=your_browserbase_project_id

5. Start the FastAPI server:

uv run main.py

6. The server will be available at http://localhost:8000

Usage

1. Open your browser and navigate to http://localhost:3000
2. Enter your Browserbase API key, project ID and Open AI key
3. Click "Run Agent" to start a browser automation session
4. Watch the session recording after task is completed (default task for AI agent is to reply to only 1 tweet - this can be changed)
5. Customise the agent at utils.py in the server's api folder

API Endpoints

The server provides several API endpoints:

• POST http://localhost:8000/api/run-agent - Run an automation agent with specified keys
• POST http://localhost:8000/api/login-x - Run an automation agent to login to X (only needed once at the start)
• POST http://localhost:3000/api/session - Get session recording for session
• POST http://localhost:3000/api/live-view - Get live view url for session (expires after session ends)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the GPL License - see the LICENSE file for details. Please note the client directory has it's sub license (MIT) from Agent-UI.

Acknowledgments

• Browserbase for browser infrastructure
• Browser-use for browser automation with LLMs
• Agent-UI for agent's UI interface