elkimek

elkimek / honcho-self-hosted

Public

Self-host Honcho memory layer for Hermes Agent — OpenRouter + Venice, no code changes

92
5
100% credibility
Found Apr 02, 2026 at 74 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Shell
AI Summary

This repository offers setup files and a script to run Honcho, a memory system for AI agents like Hermes, on a personal Linux server for data privacy.

How It Works

1
🔍 Find Private AI Memory

You learn about a simple way to run AI conversation memory on your own computer, keeping all your personal details private instead of sharing with cloud services.

2
💻 Prepare Your Computer

Make sure you have a Linux machine ready, like a virtual server or home computer, with basic tools installed.

3
🚀 Launch with One Command

Run the easy setup helper that installs everything and gets your private memory system running in just a few minutes.

4
Pick Your Thinking Helper
☁️
Cloud Helper

Connect to a quick online service for AI thinking while keeping data local.

🏠
Local Helper

Use AI thinking powered by software on your own machine for total privacy.

5
✅ System Comes Alive

Watch as your private memory storage and thinkers start working smoothly on your computer.

6
🔗 Connect to Chat App

Update your AI chat tool, like Hermes, to use this new private memory instead of the public one.

🎉 Enjoy Private Recollections

Your AI now builds a deep understanding of you across chats, with every memory safely stored only on your machine.

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Star Growth

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AI-Generated Review

What is honcho-self-hosted?

This Shell-based project lets you self-host Honcho, the memory layer for Hermes Agent, keeping all conversation data and user profiles on your own server via Docker Compose, PostgreSQL, and Redis. It routes LLM inference to any OpenAI-compatible provider like OpenRouter or Venice—no code changes or forks needed, just drop in configs and run a one-liner setup script. Developers get a drop-in replacement for Plastic Labs' cloud, with full control over the deepening user model across sessions.

Why is it gaining traction?

It stands out with dead-simple deployment (under 3 minutes) and flexible LLM support, including backups and local servers like Ollama or vLLM, without sacrificing agent performance. Unlike managed services, your data stays local while tapping cloud models for observation extraction, recall, and consolidation—ideal for self-host GitHub alternatives or agent workflows. The no-fork approach hooks Hermes users tired of third-party data lock-in.

Who should use this?

Hermes Agent builders prioritizing data sovereignty, like indie devs running personal AI assistants or teams self-hosting GitHub Copilot-like agents on private infra. Privacy-focused users integrating with self-hosted GitHub runners, Codespaces alternatives, or enterprise setups who need persistent memory without vendor clouds. Suited for those experimenting with OpenRouter/Venice in agent pipelines.

Verdict

Grab it if you're on Hermes and want self-hosted memory without hassle—48 stars and 1.0% credibility score signal early maturity, but thorough docs and battle-tested upstream make it reliable for prototypes. Scale cautiously until more adoption hits.

(198 words)

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