# HolaOS — Proactive AI Agent That Learns Your Workflow

> A local-first agent OS that learns your working context within minutes, maintains persistent memory across sessions, and proactively assists with tasks based on your patterns and preferences.

## Install

Save as a script file and run:

# HolaOS — Proactive AI Agent That Learns Your Workflow

## Quick Use
```bash
npm install -g holaos

# Initialize and start learning your workspace
holaos init --workspace ~/projects/my-app

# Start the agent runtime
holaos start

# The agent begins observing and building context
# Interact via the system tray app or CLI
holaos ask "what did I work on yesterday?"
```

## Introduction
HolaOS is an agent operating system that sits alongside your development workflow, continuously learning your patterns, project context, and preferences. Unlike chat-based assistants that start fresh each session, HolaOS maintains persistent memory and proactively surfaces relevant information or suggests actions based on what it has learned about how you work.

## What HolaOS Does
- Observes your development activity to build persistent context
- Maintains long-term memory across sessions and projects
- Proactively suggests actions based on learned workflow patterns
- Answers questions about your codebase, recent changes, and decisions
- Integrates with editors, terminals, and browser via MCP protocol

## Architecture Overview
HolaOS runs as an Electron desktop app with a background TypeScript runtime. The runtime monitors configured workspaces for file changes, git activity, and terminal commands. Events are processed into a structured memory store using embedding-based indexing. A proactive engine periodically evaluates the current context against learned patterns and surfaces suggestions. Communication with LLM providers happens through a local proxy that manages API keys and context windows.

## Self-Hosting & Configuration
- Available as an Electron app for macOS, Windows, and Linux
- Configure watched workspaces and data retention in the settings panel
- Supports any OpenAI-compatible LLM provider including local Ollama endpoints
- Memory data stored locally in `~/.holaos/` with optional encryption
- Privacy controls let you exclude specific directories or file types from observation

## Key Features
- Persistent cross-session memory that never forgets your project context
- Proactive suggestions surfaced via system notifications
- Multi-workspace support for switching between projects
- Privacy-first design with all data stored locally
- MCP-compatible for integration with coding agents and IDE extensions

## Comparison with Similar Tools
- **GitHub Copilot** — reactive code completion; HolaOS is proactive and context-persistent
- **Cursor** — IDE with AI features; HolaOS is IDE-agnostic and focuses on workflow memory
- **Khoj** — personal AI second brain; HolaOS emphasizes proactive suggestions over search
- **Mem0** — memory layer for LLMs; HolaOS is a full agent runtime, not just a memory API

## FAQ
**Q: What data does HolaOS observe?**
A: File changes, git commits, and terminal commands in configured workspaces. Browser activity and communication apps are never monitored.

**Q: How much storage does the memory use?**
A: Typical projects generate 10-50MB of memory data per month. Retention policies can be configured to auto-prune older entries.

**Q: Can I use it without cloud LLMs?**
A: Yes, HolaOS works fully offline with Ollama. The proactive engine adapts its suggestion quality to the capability of the local model.

**Q: Is the observed data sent anywhere?**
A: No. All observation data stays in your local `~/.holaos/` directory. LLM queries include only the relevant context snippet, not your full history.

## Sources
- https://github.com/holaboss-ai/holaOS

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Source: https://tokrepo.com/en/workflows/asset-ff35c88c
Author: Script Depot