In modern work environments, information is scattered across multiple platforms. We often find ourselves switching between websites repeatedly, copying and pasting data, and compiling reports—a tedious process that not only consumes time but also leads to inefficiencies in manual integration. Enter Suna, a project that skyrocketed to the top of GitHub Trending yesterday, offering a solution to this exact problem. By leveraging natural language conversations, Suna integrates powerful features like browser automation, file management, web scraping, and API integration, making it effortless to handle complex tasks such as market research, itinerary planning, and data analysis. Within just three days, Suna gained over 5.5K stars, skyrocketing from 780 stars on April 23rd to 6.4K stars today! It’s incredibly popular among users and developers alike!
Project Overview
Suna is an open-source, general-purpose AI agent platform. Built with a Python/FastAPI backend, Next.js/React frontend, and Docker-isolated environments, it combines Chromium browsers, Redis for data persistence, and LiteLLM (supporting LLMs like Claude and GPT-4o) to deliver robust task automation capabilities. It supports multimodal operations, covering browser interactions, file handling, data scraping, and system task execution, making it ideal for research, analysis, and workflow automation. All actions are executed within isolated Docker sandboxes, ensuring maximum security.
Key Features
- • Intelligent Browser Automation: Simulates human actions using Chromium browsers—navigating pages, filling forms, clicking elements, and extracting data.
- • Powerful File Management: Create, edit, and save Word, Excel, Markdown, and other document formats.
- • Web Crawling & Extended Search: Efficiently scrapes, retrieves, and consolidates multi-source information.
- • Command-Line Operations: Directly interact with your file system or run Shell commands.
- • API Integration: Connect to third-party services for extended functionality.
- • Secure Isolation: All operations run in independent Docker containers for enhanced safety.
Getting Started with Suna
Suna offers two usage options: an online demo and local custom deployment.
Online Demo
Visit: https://www.suna.so
Use Case #1
“Analyze the market situation of a health industry company based in the UK. Provide key competitors, market size, strengths, weaknesses, and their website URLs. Generate a PDF report upon completion.”
Use Case #2
“I need to find the best beauty centers in Rome, but I want to discover them through open forums discussing this topic. Use Google to search for discussions about beauty centers in Rome, scrape forum posts, and generate a list of five beauty centers along with their top reviews.”
Local Deployment Steps
Suna uses a decoupled front-end and back-end architecture, requiring both components to be deployed separately.
Step 1: Clone the Repository
git clone https://github.com/kortix-ai/suna.git
cd sunaStep 2: Configure the Backend
cd backend
cp .env.example .env
NEXT_PUBLIC_URL="http://localhost:3000"
# Supabase credentials
SUPABASE_URL=your_supabase_url
...
# Redis credentials
REDIS_HOST=your_redis_host
REDIS_PORT=6379
REDIS_PASSWORD=your_redis_password
REDIS_SSL=True
# Daytona credentials
DAYTONA_API_KEY=your_daytona_api_key
...
# OpenAI API
OPENAI_API_KEY=your_openai_api_key
...Step 3: Set Up Supabase Database
# Login to Supabase CLI
supabase login
# Link to your project
supabase link --project-ref your_project_reference_id
# Push database migrations
supabase db pushStep 4: Configure the Frontend
cd ../frontend
cp .env.example .env.local
NEXT_PUBLIC_SUPABASE_URL=your_supabase_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key
NEXT_PUBLIC_BACKEND_URL="http://localhost:8000/api"
NEXT_PUBLIC_URL="http://localhost:3000"Step 5: Install Dependencies
# Install frontend dependencies
cd frontend
npm install
# Install backend dependencies
cd ../backend
pip install -r requirements.txtStep 6: Start the Services
# Start frontend
cd frontend
npm run dev
# Start backend
cd backend
python api.pyFinal Thoughts
Suna is a game-changing AI agent that transforms fragmented workflows into seamless automation—all for free and open source! Tasks that used to require step-by-step execution can now be completed with a single prompt. For example:
- • “Collect today’s news highlights from a specific website and compile them into a PDF.”
- • “Search for a product across three e-commerce platforms, compare prices, and generate a Markdown table.”
- • “Find next week’s weather forecast for a city and save it as an Excel file.”
Suna handles everything autonomously: browsing → searching → navigating pages → extracting data → organizing files → saving locally. You barely need to lift a finger. If you’re looking to cut 80% of repetitive tasks and let AI handle data collection, organization, and output, Suna is definitely worth trying immediately!
GitHub Project Link: https://github.com/kortix-ai/suna
Reproduction without permission is prohibited：AI LAB » Open-source AI agent goes viral! Suna: Gained over 5.5K stars in just 3 days, a magical automation tool driven by natural conversations!
