Skip to main content

Local AI CLI using local llm gpt-oss:20b

Project description

easylocai

Fully autonomous agentic workflows running locally—no APIs, no data leaks

run_sample.gif

Overview

Easylocai is an On-Device Autonomous Agent designed for secure, offline task execution. Unlike cloud-dependent assistants, it leverages the gpt-oss:20b model to perform complex reasoning and actions entirely on your local machine.

By implementing a sophisticated Plan-Execute-Replan orchestration, Easylocai can decompose ambiguous goals into actionable steps, execute them using Model Context Protocol (MCP) tools, and autonomously refine its strategy based on real-time feedback.

Features

  • Privacy-First Autonomy: 100% local execution using gpt-oss:20b via Ollama. Your code and data never leave your machine.

  • Agentic Orchestration: A robust multi-agent loop (Plan → Execute → Replan) that ensures high success rates for long-horizon tasks.

  • MCP Tool Integration: Seamlessly connects with Model Context Protocol (MCP) servers to interact with your local file system, terminal, and APIs.

Requirements

To ensure stable performance of the autonomous agent, your system must meet the following criteria:

System Requirements

  • Minimum 16GB RAM (32GB or more recommended for optimal performance)
  • Sufficient disk space for model storage and operation

OS

  • OS: macOS (Strictly supported)

Software Requirements

  • Runtime: Python 3.12. It is recommended to use pyenv.
  • LLM Engine: Ollama must be installed and running.
    • Model: gpt-oss:20b (Make sure to run ollama pull gpt-oss:20b before starting).

Install & Execution

(1) Installation

First-time install

pipx install easylocai

Reinstall or upgrade

pipx upgrade easylocai

(2) Initialization

configuration file is generated at ~/.easylocai/config.json after initialization.

easylocai init

If you want to force re-initialization, use --force flag: WARNING: config file will be reset to default and all existing MCP server configurations.

easylocai init --force

(3) Configuration

MCP server configuration

  • file_name: ~/.config/easylocai/config.json
  • example
    {
      "mcpServers": {
        "filesystem": {
          "command": "npx",
          "args": [
            "-y",
            "@modelcontextprotocol/server-filesystem",
            "."
          ]
        },
        "notion_api": {
          "command": "docker",
          "args": [
            "run",
            "--rm",
            "-i",
            "-e", "NOTION_TOKEN",
            "mcp/notion"
          ],
          "env": {
            "NOTION_TOKEN": "<token>"
          }
        }
      }
    }
    

(4) Execution

Run default workflow

easylocai

Run flag workflow variant

easylocai --flag={flag}

References

  • Development: docs/DEVELOPMENT.md for development setup, testing, and key code patterns.
  • Architecture: docs/ARCHITECTURE.md for agentic workflow architecture, component responsibilities, and data flow diagrams.

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

easylocai-0.2.0.tar.gz (523.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

easylocai-0.2.0-py3-none-any.whl (70.0 kB view details)

Uploaded Python 3

File details

Details for the file easylocai-0.2.0.tar.gz.

File metadata

  • Download URL: easylocai-0.2.0.tar.gz
  • Upload date:
  • Size: 523.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.11

File hashes

Hashes for easylocai-0.2.0.tar.gz
Algorithm Hash digest
SHA256 103f0c16fc39925212b3ae2ae1335fc0dc7cb3baa2add49248018375c1a7cbf3
MD5 f993ac353e7723b596d4ef0108d5bb37
BLAKE2b-256 e0cfab8f0a759bd8124661ed626081f3ef6c8ef1786990200ac147d3211a2527

See more details on using hashes here.

File details

Details for the file easylocai-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: easylocai-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 70.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.11

File hashes

Hashes for easylocai-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e8d5af03580c56c13e52227ac8cf2d632ca7b12a7c9e778efbae8d0ea77f7d33
MD5 c7e3d8f5540d6553173c0c0ccb97deb0
BLAKE2b-256 37bc053b1242a31cbc6c5505cd02c03ca51a73b913231dccf07bce5455325aa5

See more details on using hashes here.

Supported by

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