Get an AI assistant that actually does your work - ready in 10 minutes

Last updated on 
Get an AI assistant that actually does your work - ready in 10 minutes

While everyone's refreshing their email for Manus invites, you could have an autonomous AI agent running on your machine before lunch. Here's how.

What we're building

Agent Zero is an open-source autonomous agent that can:

  • Write and execute code across multiple languages
  • Control browsers for web automation
  • Create sub-agents for complex tasks
  • Build its own tools when needed
  • Learn from interactions

Think ChatGPT with hands and a memory.

Quick note: If you'd rather skip the manual setup complexity, our CloudStation template offers one-click deployment that handles all the configuration automatically. But if you want to understand how Agent Zero works under the hood or need a custom local setup, this guide will save you hours of troubleshooting.

Prerequisites

  • Python 3.11 or 3.12 (3.13 has compatibility issues)
  • 2GB disk space
  • macOS, Linux, or Windows with WSL2
  • An LLM API key (Anthropic, OpenAI, or free with Ollama)

Step 1: Clone and setup

git clone https://github.com/frdel/agent-zero.git
cd agent-zero

Step 2: Python environment

python3 -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt

If you hit dependency issues with Python 3.13:

python3.12 -m venv venv  # Use 3.12 specifically

Step 3: Browser automation

playwright install

This downloads Chromium drivers (~300MB). Required for web scraping and automation features.

Step 4: Configure your LLM

Copy the example config:

cp example.env .env

Edit .env and add ONE of these:

Option A: Anthropic Claude (recommended)

API_KEY_ANTHROPIC=sk-ant-xxxxx
CHAT_MODEL_ANTHROPIC=claude-3-5-sonnet-20241022

Option B: OpenAI

API_KEY_OPENAI=sk-xxxxx
CHAT_MODEL_OPENAI=gpt-4o

Option C: Free with Ollama (local models)

# Install Ollama first
curl -fsSL https://ollama.com/install.sh | sh  # Linux
brew install ollama  # macOS

# Start Ollama
ollama serve

# In another terminal, pull a model
ollama pull llama3.2

# No API key needed - it runs locally

Step 5: Launch

python run_ui.py

Navigate to http://localhost:50001

Your agent is ready.

First tasks to try

1. Code generation with execution

Create a Python script that analyzes CSV files for outliers and generates a visualization

Watch it write, execute, debug, and show you the plot.

2. Web automation

Research the top 5 Python web frameworks and create a comparison table with pros/cons

It'll search, read docs, and build the analysis.

3. Tool creation

I frequently need to resize and compress images. Build me a tool for this.

It creates a reusable utility and saves it for future use.

Advanced configuration

Custom port

Edit .env:

WEB_UI_PORT=8080

docker build -t agent-zero .
docker run -p 50001:80 -v ./memory:/app/memory agent-zero

Memory persistence

Agent Zero stores learned patterns in ./memory/. Back this up to preserve your agent's knowledge.

Performance tuning

For faster responses with Claude:

CHAT_MODEL_ANTHROPIC=claude-3-5-haiku-20241022  # Faster, cheaper

Common issues

"No module named 'playwright'"

pip install playwright
playwright install

"API rate limit exceeded" Add rate limiting to .env:

RATE_LIMIT_DELAY=2  # Seconds between API calls

"Permission denied on execution" Enable Docker mode in the UI settings for sandboxed execution.

What makes this different

Most "AI agents" are just prompt chains. Agent Zero has:

  1. Real execution environment - It runs actual code, not just generates it
  2. Persistent memory - Learns from every interaction
  3. Tool creation - Builds custom utilities for repeated tasks
  4. Multi-agent orchestration - Spawns specialized sub-agents

Example session:

You: Build a web scraper that monitors HackerNews for AI agent posts
Agent 0: I'll create a monitoring system for you...
[Creates scraper.py, sets up scheduling, adds notification system]
[Tests it, finds a bug, fixes it]
[Saves as reusable tool]

You: Great, also monitor Reddit r/singularity
Agent 0: I'll extend the existing monitor...
[Reuses previous code, adds Reddit support]
[Integrates both sources into unified system]

Production considerations

Security: Agent Zero executes code. In production:

  • Use Docker isolation
  • Run on isolated VMs
  • Limit file system access
  • Monitor API usage

Scaling: For teams or heavy usage:

  • Deploy multiple instances
  • Use Redis for shared memory
  • Implement queue system for tasks

Alternative: If you want managed hosting, CloudStation handles all this (but local gives you full control).

Building your own tools

Agent Zero can extend itself. Example custom tool:

# tools/my_tool.py
def analyze_logs(log_file):
    """Custom tool for log analysis"""
    # Agent Zero will discover and use this
    pass

Place in tools/ directory. The agent automatically integrates it.

Next steps

  1. Join the Discord for examples and help
  2. Check GitHub issues for known limitations
  3. Star the repo if you find it useful

The best AI agent is the one you can use today. While others wait for invites, you're already building.

Deploy locally in 10 minutes, or on CloudStation in 60 seconds if you prefer managed hosting.