Looking for the raw HTTP API? Check out the API Reference for direct REST endpoints. Installation
Install the SDK
pip install orgo python-dotenv
Launch a computer-use agent
from orgo import Computer from dotenv import load_dotenv load_dotenv() # Create a computer computer = Computer() # Control it with natural language computer.prompt( "Open Firefox and search for AI news" )
Organize with Workspaces workspaces.py
workspaces.ts
from orgo import Computer # Create computer in a specific workspace computer = Computer( workspace = "production" ) # Create multiple computers in the same workspace agents = [] for i in range ( 3 ): agent = Computer( workspace = "agents" ) agents.append(agent)
Manual Control Mouse & Keyboard # Mouse actions computer.left_click( 100 , 200 ) computer.right_click( 300 , 400 ) computer.double_click( 500 , 300 ) computer.scroll( direction = "down" , amount = 3 ) # Keyboard input computer.type( "Hello world" ) computer.key( "Enter" ) computer.key( "ctrl+c" ) # Take screenshot screenshot = computer.screenshot() # Returns PIL Image screenshot.save( "screenshot.png" ) # Or get base64 base64_image = computer.screenshot_base64()
Execute Code # Run bash commands output = computer.bash( "ls -la" ) print (output) # Execute Python code result = computer.exec( "print('Hello from Python')" ) print (result) # Wait between actions computer.wait( 2.0 ) # Wait 2 seconds
These methods give you full control to implement your own custom computer-use agent. See the API reference for all available methods. AI Control By default, prompt() uses Orgo’s hosted AI agent:
computer.prompt( "Create a report on AI trends and save it as report.pdf" )
You can also use your own Anthropic API key:
computer.prompt( "Create a report on AI trends and save it as report.pdf" , provider = "anthropic" , api_key = "sk-ant-..." )
Advanced Options computer.prompt( "Research the latest AI developments and create a summary" , provider = "anthropic" , api_key = "sk-ant-..." , model = "claude-sonnet-4-5-20250929" , thinking_enabled = True , thinking_budget = 2048 , max_iterations = 50 , verbose = True , callback = lambda event , data : print ( f " { event } : { data } " ) )
Complete Example from orgo import Computer from dotenv import load_dotenv load_dotenv() # Create computer with custom specs computer = Computer( workspace = "research" , name = "research-agent" , ram = 8 , cpu = 4 ) try : # Track progress def on_progress ( event_type , event_data ): if event_type == "text" : print ( f "Agent: { event_data } " ) elif event_type == "tool_use" : print ( f "Action: { event_data.get( 'action' ) } " ) # Run task messages = computer.prompt( "Search for recent AI papers, summarize the top 3, and create a document" , callback = on_progress ) print ( "Task complete!" ) # Take screenshot screenshot = computer.screenshot() screenshot.save( "result.png" ) finally : computer.destroy()
Templates Pre-configure computers with installed software:
from orgo import Template, Computer # Create a template with pre-installed packages template = Template( "data-science" ) template.run( "pip install numpy pandas matplotlib jupyter" ) template.build() # Launch computers from the template computer = Computer( template = "data-science" )
Computer Specs computer = Computer( workspace = "ml-training" , name = "ml-trainer" , ram = 32 , cpu = 8 , os = "linux" , gpu = "a100-80gb" # Coming soon )
Defaults: linux, 4GB RAM, 2 CPU cores, no GPUValid RAM/CPU pairs: RAM CPU Best for 4 GB 2 cores Standard workflows (default) 8 GB 4 cores Heavy automation 16 GB 8 cores Development 32 GB 8 cores Large-scale processing 64 GB 16 cores Enterprise workloads
Computer Lifecycle # Check status status = computer.status() print ( f "Status: { status[ 'status' ] } " ) # Restart computer computer.restart() # Connect to existing computer existing = Computer( computer_id = "comp_xyz789" ) # Get computer URL print ( f "View at: { computer.url } " ) # Delete when done computer.destroy()
Computers automatically stop during inactivity to save resources. They restart automatically when you send commands.
Quiet Mode Disable console output for production:
# Disable all console output computer = Computer( workspace = "production" , verbose = False ) # Or for specific prompt calls computer.prompt( "Do something" , verbose = False )
Environment Variables ORGO_API_KEY = sk_live_... # Optional - only needed if using provider="anthropic" ANTHROPIC_API_KEY = sk-ant-...
Tips
Use workspaces to organize computers
dev = Computer( workspace = "development" ) test = Computer( workspace = "testing" ) prod = Computer( workspace = "production" )
try : computer.prompt( "Do task" ) finally : computer.destroy()
Take screenshots for debugging
screenshot = computer.screenshot() screenshot.save( "debug.png" )
Track progress with callbacks
def on_progress ( event , data ): print ( f " { event } : { data } " ) computer.prompt( "Task" , callback = on_progress)
Next Steps 
