b037627d84 Feat/daemon setup (#148)
* feat: add .mcp.json for MCP server configuration

- Introduced `.mcp.json` with server details for managing MCP integrations
- Defines `readme` server with HTTP type and URL endpoint configuration

* fix: Update skills submodule with Telegram error handling improvements

- Fixed setup flow showing false success when TDLib errors occurred
- Improved async error handling in setup steps
- Added client reset mechanisms for error recovery
- Enhanced error messaging for better user experience
- Cleaned up excessive debug logging while maintaining error logs

Resolves issue where Telegram setup showed success modal despite underlying TDLib errors.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Add daemon lifecycle management system to frontend UI

This implementation integrates the Rust daemon's health monitoring and lifecycle management into the React frontend. Key features include real-time health indicators, automatic start/error recovery, and detailed control panels, enhancing both user experience and operational reliability.

* Enhance daemon health monitoring with detailed logging, event tracking, and state management improvements.

* Add extensive logging for Tauri socket lifecycle and event listeners

This update improves troubleshooting and debugging by adding detailed logs throughout Tauri socket initialization, event listener setup, and error handling processes.

* Define global Tauri interface types in TypeScript

* Fix daemon service management and health communication issues

This comprehensive fix resolves two critical daemon-related issues:

1. **Launchctl "Input/output error" fix**:
   - Add intelligent state checking before service operations
   - Only load LaunchAgent if not already loaded
   - Treat "already running" as success, not failure
   - Add helper functions for cross-platform service state detection
   - Implement idempotent service start operations

2. **Daemon health communication fix**:
   - Add ALPHAHUMAN_DAEMON_INTERNAL environment variable to external service plist
   - Force external daemon to use file-based communication (daemon_state.json)
   - Implement file watching bridge in main app to emit Tauri events
   - Ensure frontend receives proper health updates from external daemon

**Key Changes**:
- Enhanced `start()` function with state checking across all platforms
- Added `is_service_loaded_macos()`, `is_service_enabled_linux()`, `is_task_exists_windows()`
- Modified macOS plist to include `ALPHAHUMAN_DAEMON_INTERNAL=false`
- Added `watch_daemon_health_file()` function for external daemon communication
- Updated daemon mode detection logic for cross-platform consistency
- Added comprehensive logging for service management operations

**Expected Results**:
- No more "Input/output error" when clicking daemon start button
- External daemon status shows "connected" instead of "disconnected"
- Idempotent service operations (safe to run multiple times)
- Single daemon process prevents resource conflicts
- Cross-platform daemon service reliability

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Add `ALPHAHUMAN_DAEMON_INTERNAL` env variable to configuration documentation

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-02-26 19:55:53 +04:00
2026-02-20 13:03:15 +04:00
2026-02-04 18:05:04 +05:30
2026-02-26 19:55:53 +04:00
2026-02-20 13:03:15 +04:00
2026-02-26 19:55:53 +04:00
2026-02-26 19:55:53 +04:00
2026-02-26 19:55:53 +04:00
2026-02-11 02:50:50 +05:30
2026-02-26 19:55:53 +04:00
2026-02-20 13:03:15 +04:00
2026-02-20 13:03:15 +04:00
2026-02-16 17:10:06 +05:30
2026-02-03 15:26:38 +05:30
2026-02-20 13:03:15 +04:00
2026-02-21 10:57:37 +04:00
2026-02-20 13:03:15 +04:00
2026-02-20 13:03:15 +04:00
2026-02-03 15:26:38 +05:30
2026-02-16 17:10:06 +05:30
2026-02-16 17:10:06 +05:30
2026-02-16 17:10:06 +05:30

AlphaHuman Mk1

Your most productive co-worker
A user-friendly (GUI-first) AI agent. AlphaHuman uses the Neocortex Mk1 model to co-ordinate memories & realtime-data, cheaper and faster than other models.

Early Beta Platforms Latest Release

About · vs OpenClaw · Download · Getting Started · Architecture · Changelog

The Tet

"The Tet. What a brilliant machine" — Morgan Freeman in Oblivion

AlphaHuman is a personal AI assistant that helps you manage high-volume communication without reading everything yourself. It connects to your messaging platforms and productivity tools, understands conversations in context, and produces clear, actionable outputs you can use immediately.

AlphaHuman is not a chatbot, browser extension, or cloud-only service. It is a native application that runs on your device, connects to your tools, and works only when you ask it to. Think of it as a second brain that sits across your communication and productivity stack.

AlphaHuman vs OpenClaw

AlphaHuman is designed to be simpler to deploy, cheaper to run, and more intelligent in how it uses models and memory.

OpenClaw AlphaHuman
Runtime Node.js (TypeScript) Tauri (Rust + React), native binary
Inference Single-tier or manual routing Custom two-tier: task-routed (summarize/vibe/memory → cheap; complex/tools → premium)
Memory Often external (Pinecone, Lucid, etc.) or markdown-only Custom hybrid: SQLite FTS5 + vector similarity, optional encryption, no external vector DB
Tunneling Third-party (ngrok, Cloudflare, Tailscale) or none Custom tunneling — secure app-to-backend path without vendor lock-in
Cost Typically one premium model for everything Lower — Tier 1 for most ops; Tier 2 only when needed
Intelligence General-purpose agent loop Smarter — vibe detection, interest-based escalation, constitution-driven behavior, session-aware memory
Deployment Server/Node process, high memory footprint Native desktop/mobile app, Rust socket manager, smaller footprint

OpenClaw is a strong open-source agent framework. We chose to build a custom stack so we could own inference routing, memory, and tunneling end-to-end and optimize for cost and clarity.


Download

Early Beta — AlphaHuman is under active development. Expect rough edges.

Platform Variant Download
macOS Apple Silicon (M1/M2/M3/M4) .dmg (aarch64)
macOS Intel .dmg (x64)
Windows x64 .msi
Linux Debian / Ubuntu .deb (amd64)
Linux Fedora / RHEL .rpm (x86_64)
Linux Universal .AppImage
Android Coming soon
iOS Coming soon

Browse all releases: github.com/alphahumanai/alphahuman/releases

Getting Started

  1. Download the installer for your platform from the releases page
  2. Install the app (drag to Applications on macOS, or use your package manager on Linux)
  3. Connect a source — follow the in-app onboarding to link Telegram, Notion, Gmail, or other services
  4. Run your first request — ask the AI to summarize what you missed, extract action items, or surface key decisions


Made with love in India 🇮🇳

AlphaHuman is in early beta. Features may change, break, or disappear. Use at your own risk.

S
Description
No description provided
Readme GPL-3.0
220 MiB
Languages
Rust 59.1%
TypeScript 37.9%
JavaScript 1.6%
Shell 1.2%
CSS 0.1%