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What is GCA?

Hi, this is an open source framework to build vertical AI agent. We just support many llms and new technologies like mcp. You can build your own vertical ai agent army in few commands with the stucturized API.

Playground of GCA | NEW

With playground.gca.dev you are ready to test and create your own strategies for creating an Vertical AI Agent.

• Playground sessions limited to <b>10 minute</b>.

GPT Computer Assistant(GCA)

GCA is an AI agent framework designed to make computer use across Windows, macOS, and Ubuntu. GCA enables you to replace repetitive, small-logic-based tasks worker to an AI. There is an really important potential that we believe. Whether you’re a developer, analyst, or IT professional, GCA can empower you to accomplish more in less time.

Imagine this:

• <b>Extract the tech stacks of xxx Company</b> | Sales Development Representer
• <b>Identify Relevant tables for Analysis for xxx</b> | Data Analytics
• <b>Check the logs to find core cause of this incident</b> | Technical Support Engineer
• <b>Making CloudFlare Security Settings</b> | Security Specialist

These examples shows how GCA is realize the concept of <b>Vertical AI Agents</b> solutions that not only replicate human tasks, GCA also in the beyond of human speed at same cases.

How GCA Works?

GCA is a Python-based project that runs on multiple operating systems, including Windows, macOS, and Ubuntu. It integrates external concepts, like the Model Context Protocol (MCP), along with its own modules, to interact with and control a computer efficiently. The system performs both routine and advanced tasks by mimicking human-like actions and applying computational precision.

1. Human-like Actions:

GCA can replicate common user actions, such as:

• <b>Clicking</b>: Interact with buttons or other UI elements.
• <b>Reading</b>: Recognize and interpret text on the screen.
• <b>Scrolling</b>: Navigate through documents or web pages.
• <b>Typing</b>: Enter text into forms or other input fields.

2. Advanced Capabilities:

Through MCP and GCA’s own modules, it achieves tasks that go beyond standard human interaction, such as:

• <b>Updating dependencies</b> of a project in seconds.
• <b>Analyzing entire database</b> tables to locate specific data almost instantly.
• <b>Automating cloud security</b> configurations with minimal input.

Prequisites

• Python 3.10

Using GCA.dev Cloud

<b>Installation</b>

pip install gpt-computer-assistant

Single Instance:

from gpt_computer_assistant import cloud

# Starting instance
instance = cloud.instance()

# Show Screenshot
instance.current_screenshot()

# Asking and getting result
result = instance.request("Extract the tech stacks of gpt-computer-assitant Company", "i want a list")
print(result)


instance.close()

Self-Hosted GCA Server

Docker

Pulling Image

• If you are using ARM computer like M Chipset macbooks you should use ARM64 at the end.

docker pull upsonic/gca_docker_ubuntu:dev0-AMD64

Starting container

docker run -d -p 5901:5901 -p 7541:7541 upsonic/gca_docker_ubuntu:dev0-AMD64

LLM Settings&Using

from gpt_computer_assistant import docker

# Starting instance
instance = docker.instance("http://localhost:7541/")

# Connecting to OpenAI and Anthropic
instance.client.save_models("gpt-4o")
instance.client.save_openai_api_key("sk-**")
instance.client.save_anthropic_api_key("sk-**")

# Asking and getting result
result = instance.request("Extract the tech stacks of gpt-computer-assitant Company", "i want a list")
print(result)

instance.close()

Local

<b>Installation</b>

pip install 'gpt-computer-assistant[base]'
pip install 'gpt-computer-assistant[api]'

<b>LLM Settings&Using</b>

from gpt_computer_assistant import local

# Starting instance
instance = local.instance()

# Connecting to OpenAI and Anthropic
instance.client.save_models("gpt-4o")
instance.client.save_openai_api_key("sk-**")
instance.client.save_anthropic_api_key("sk-**")

# Asking and getting result
result = instance.request("Extract the tech stacks of gpt-computer-assitant Company", "i want a list")
print(result)

instance.close()

Adding Custom MCP Server to GCA

instance.client.add_mcp_server("websearch", "npx", ["-y", "@mzxrai/mcp-webresearch"])

Roadmap

Capabilities

At this time we have many infrastructure elements. We just aim to provide whole things that already in ChatGPT app.

Predefined Agents

If you enable it your assistant will work with these teams:

Contributors