Skip to main content

Python client for interacting with the CoffeeBlack visual reasoning API

Project description

CoffeeBlack SDK

Python client for interacting with the CoffeeBlack visual reasoning API.

Installation

You can install the package using pip:

# Install from PyPI
pip install coffeeblack

# Install from local directory
pip install -e .

# Or install from GitHub
pip install git+https://github.com/coffeeblack/sdk.git

Features

  • Find and interact with windows on your system
  • Take screenshots and send them to the CoffeeBlack API
  • Execute actions based on natural language queries
  • Reason about UI elements without executing actions
  • Find and launch applications with semantic search

Quick Start

import asyncio
import os
from coffeeblack import Argus

async def main():
    # Initialize the SDK with API key for authentication
    # You can provide your API key directly or through an environment variable
    api_key = os.environ.get("COFFEEBLACK_API_KEY")
    sdk = Argus(
        api_key=api_key,  # API key for authentication
        verbose=True,
        debug_enabled=True,
        elements_conf=0.2,
        rows_conf=0.4,
        model="ui-detect"  # Set the UI detection model to use (cua, ui-detect, or ui-tars)
    )
    
    # Define the browser name
    browser_name = "Safari" 
    
    try:
        # Open and attach to the browser
        await sdk.open_and_attach_to_app(browser_name, wait_time=2.0)

        # Execute an action based on a natural language query
        await sdk.execute_action("Type https://www.google.com into the url bar")
        
        # Press enter key
        await sdk.press_key("enter")
    
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    asyncio.run(main())

License

MIT

Documentation

For more detailed documentation, please visit https://docs.coffeeblack.ai

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

coffeeblack-0.1.8.tar.gz (44.0 kB view details)

Uploaded Source

Built Distribution

coffeeblack-0.1.8-py3-none-any.whl (46.5 kB view details)

Uploaded Python 3

File details

Details for the file coffeeblack-0.1.8.tar.gz.

File metadata

  • Download URL: coffeeblack-0.1.8.tar.gz
  • Upload date:
  • Size: 44.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.13

File hashes

Hashes for coffeeblack-0.1.8.tar.gz
Algorithm Hash digest
SHA256 4b7286d52242749f02f491a3969521eb466900d72c8e39a217666f230f046b3c
MD5 dceeca8e9b7562ea572b22a8f1eacfff
BLAKE2b-256 1b4b70315c55032ba297ae60558b11a22590a4d367338ae26980f4d8597e14c3

See more details on using hashes here.

File details

Details for the file coffeeblack-0.1.8-py3-none-any.whl.

File metadata

  • Download URL: coffeeblack-0.1.8-py3-none-any.whl
  • Upload date:
  • Size: 46.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.13

File hashes

Hashes for coffeeblack-0.1.8-py3-none-any.whl
Algorithm Hash digest
SHA256 b62936fc06195c0b2c73175708beca1529c529cc8aae3f6df0bb97fac5d5a0f7
MD5 efd890d6ef474c5f41f5e4ebb84e3a71
BLAKE2b-256 c15a1f3fcce703510024487aba22d13d190607ae1e171e05b9ce467471ccd3fb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page